5. Geo Services Guide

This guide covers the details of geo data management and retrieval in rasdaman. The rasdaman Array DBMS is domain agnostic; the specific semantics of space and time is provided through a layer on top of rasdaman, historically known as petascope. It offers spatio-temporal access and analytics through APIs based on the OGC data standard Coverage Implementation Schema (CIS) and the OGC service standards Web Map Service (WMS), Web Coverage Service (WCS), and Web Coverage Processing Service (WCPS).


While the name petascope addresses a specific component we frequently use the name rasdaman to refer to the complete system, including petascope.

5.1. OGC Coverage Standards Overview

For operating rasdaman geo services as well as for accessing such geo services through these APIs it is important to understand the mechanics of the relevant standards. In particular, the concept of OGC / ISO coverages is important.

In standardization, coverages are used to represent space/time varying phenomena, concretely: regular and irregular grids, point clouds, and general meshes. The coverage standards offer data and service models for dealing with those. In rasdaman, focus is on multi-dimensional gridded (“raster”) coverages.

In rasdaman, the OGC standards WMS, WCS, and WCPS are supported, being reference implementation for WCS. These APIs serve different purposes:

  • WMS delivers a 2D map as a visual image, suitable for consunmption by humans

  • WCS delivers n-D data, suitable for further processing and analysis

  • WCPS performs flexible server-side processing, filtering, analytics, and fusion on coverages.

These coverage data and service concepts are summarized briefly below. Ample material is also available on the Web for familiarization with coverages (best consult in this sequence):

5.1.1. Coverage Data

OGC CIS specifies an interoperable, conformance-testable coverage structure independent from any particular format encoding. Encodings are defined in OGC in GML, JSON, RDF, as well as a series of binary formats including GeoTIFF, netCDF, JPEG2000, and GRIB2).

By separating the data definition (CIS) from the service definition (WCS) it is possible for coverages to be served throuigh a variety of APIs, such as WMS, WPS, and SOS. However, WCS and WCPS have coverage-specific functionality making them particularly suitable for flexible coverage acess, analytics, and fusion.

5.1.2. Coverage Services

OGC WMS delivers 2D maps generated from styled layers stacked up. As such, WMS is a visualization service sitting at the end of processing pipelines, geared towards human consumption.

OGC WCS, on the other hand, provides data suitable for further processing (including visualization); as such, it is suitable also for machine-to-machine communication as it appears in the middle of longer processing pipelines. WCS is a modular suite of service functionality on coverages. WCS Core defines download of coverages and parts thereof, through subsetting directives, as well as delivery in some output format requested by the client. A set of WCS Extensions adds further functionality facets.

One of those is WCS Processing; it defines the ProcessCoverages request which allows sending a coverage analytics request through the WCPS spatio-temporal analytics language. WCPS supports extraction, analytics, and fusion of multi-dimensional coverage expressed in a high-level, declarative, and safe language.

5.2. OGC Web Services Endpoint

Once the petascope geo service is deployed (see rasdaman installation guide) coverages can be accessed through the HTTP service endpoint /rasdaman/ows.

For example, assuming that the service IP address is 123.456.789.1 and the service port is 8080, the following request URLs would deliver the Capabilities documents for OGC WMS and WCS, respectively:


5.3. OGC Coverage Implementation Schema (CIS)

A coverage consists mainly of:

  • domain set: provides information about where data sit in space and time. All coordinates expressed there are relative to the coverage’s Coordinate Reference System or Native CRS. Both CRS and its axes, units of measure, etc. are indiciated in the domain set. Petascope currently supports grid topologies whose axes are aligned with the axes of the CRS. Along these axes, grid lines can be spaced regularly or irregularly.

  • range set: the “pixel payload”, ie: the values (which can be atomic, like in a DEM, or records of values, like in hyperspectral imagery).

  • range type: the semantics of the range values, given by type information, null values, accuracy, etc.

  • metadata: a black bag which can contain any data: the coverage will not understand these, but duly transport them along so that the connection between data and metadata is not lost.

Further components include Envelope which gives a rough, simplified overview on the coverage’s location in space and time and CoverageFunction which is unused by any implementation known to us.

5.3.1. Coverage CRS

Every coverage, as per OGC CIS, must have exactly one native Coordinate Reference System (CRS), which is given by a URL. Resolving this URL should deliver the CRS definition. The OGC CRS resolver is an example of a public service for resolving CRS URLs; the same service is also bundled in every rasdaman installation, so that it is avialable locally. More details on this topic can be found in the CRS Management chapter.

Sometimes definitions for CRSs are readily available, such as the 2-D WGS84 with code EPSG:4326 in the EPSG registry. In particular spatio-temporal CRSs, however, are not always readily available, at least not in all combinations of spatial and temporal axes. To this end, composition of CRS is supported so that the single Native CRS can be built from “ingredient” CRSs by concatenating them into a composite one. For instance, a time-series of WGS84 images would have the following Native CRS:


Coordinate tuples in this CRS represent an ordered composition of a temporal coordinate expressed in ISO 8601 syntax, such as 2012-01-01T00:01:20Z, followed by latitude and longitude coordinates, as per EPSG:4326.

The native CRS of a coverage domain set can be determined in severay ways:

  • in a WCS GetCapabilities response, the wcs:CoverageSummary/ows:BoundingBox@crs attribute;

  • in a WCS DescribeCoverage response, the srsName attribute in the gml:domainSet element; Furthermore, the axisLabels attribute contains the CRS axis names according to the CRS sequency, and the uomLabels attribute contains the units of measure for each corresponding axis.

  • in WCPS, the function crsSet(e) returns the CRS of a coverage expression e;

The following graphics illustrates, on the example of an image timeseries, how dimension, CRS, and axis labels affect the domain set in a CIS 1.0 RectifiedGridCoverage.



This handling of coordinates in CIS 1.0 bears some legacy burden from GML; in the GeneralGridCoverage introduced with CIS 1.1 coordinate handling is much simplified.

5.3.2. Range Type

Range values can be atomic or (possibly nested) records over atomic values, described by the range type. In rasdaman the following atomic data types are supported; all of these can be combined freely in records of values, such as in hyperspectral images or climate variables.

Table 5.1 Mapping of rasdaman base types to SWE Quantity types

rasdaman type


Quantity types


8 bit



8 bit



8 bit



16 bit


unsigned short = ushort

16 bit



32 bit


unsigned long = ulong

32 bit



32 bit



64 bit



64 bit



128 bit


5.3.3. Nil Values

Nil (null) values, as per SWE, are supported by rasdaman in an extended way:

  • null values can be defined over any data type

  • nulls can be single values

  • nulls can be intervals

  • a null definnition in a coverage can be a list of all of the above alternatives.

Full details can be found in the null values section.


It is highly recommended to NOT define single null values over floating-point data as this causes numerical problems well known in mathematics. This is not related to rasdaman, but intrinsic to the nature and handling of floating-point numbers in computers. A floating-point interval around the desired float null value should be preferred (this corresponds to interval arithmetics in numerical mathematics).

5.3.4. Errors

Errors from OGC requests to rasdaman are returned to the client formatted as ows:ExceptionReport (OGC Common Specification). An ExceptionReport can contain multiple Exception elements. For example, when running a WCS GetCoverage or a WCPS query which execute rasql queries in rasdaman, in case of an error the ExceptionReport will contain two Exception elements:

  1. One with the error message returned from rasdaman.

  2. Another with the rasql query that failed.

For example:

    <ows:Exception exceptionCode="RasdamanRequestFailed">
        <ows:ExceptionText>The Encode function is applicable to array arguments only.</ows:ExceptionText>
    <ows:Exception exceptionCode="RasdamanRequestFailed">
        <ows:ExceptionText>Failed internal rasql query: SELECT encode(1, "png" ) FROM mean_summer_airtemp AS c</ows:ExceptionText>

5.4. OGC Web Coverage Service

WCS Core offers the following request types:

  • GetCapabilities for obtaining a list of coverages offered together with an overall service description;

  • DescribeCoverage for obtaining information about a coverage without downloading it;

  • GetCoverage for downloading, extracting, and reformatting of coverages; this is the central workhorse of WCS.

WCS Extensions in part enhance GetCoverage with additional functionality controlled by further parameters, and in part establish new request types, such as:

  • WCS-T defining InsertCoverage, DeleteCoverage, and UpdateCoverage requests;

  • WCS Processing defining ProcessCoverages for submitting WCPS analytics code.

You can use http://localhost:8080/rasdaman/ows as service endpoints to which to send WCS requests, for example:


See example queries in the WCS systemtest which send KVP (key value pairs) GET request and XML POST request to Petascope.

5.4.1. Subsetting behavior

In general, subsetting in petascope behaves similarly to subsetting in gdal, with a couple of deviations necessary for n-D. Specifically, subsetting follows the next rules:

  • Slicing (geoPoint): the grid slice with index corresponding to the requested slicing geo point is returned. This is computed as follows:

    gridIndex = floor((geoPoint - minGeoLowerBound) / axisResolution)
  • Trimming (geoLowerBound:geoUpperBound): the lower bound of the grid interval is determined as in the case of slicing. The number of returned grid points follows gdal:

    • If axis resolution is positive (e.g. Long axis):

      gridLowerBound = floor((geoLowerBound - minGeoLowerBound) / axisResolution)
      numberOfGridPixels = floor(((geoUpperBound - geoLowerBound) / axisResolution) + 0.5)
      gridUpperBound = gridLowerBound + numberOfGridPixels - 1
    • If axis resolution is negative (e.g. Lat axis):

      gridLowerBound = floor((geoUpperBound - maxGeoLowerBound) / axisResolution)
      numberOfGridPixels = floor((geoLowerBound - geoUpperBound) / axisResolution) + 0.5)
      gridUpperBound = gridLowerBound + numberOfGridPixels - 1


    If a trimming subset is applied on an axis with (geoUpperBound - geoLowerBound) / axisResolution < 0.5, then lower grid bound is translated by the slicing formula and upper grid bound is set to lower grid bound.

For example, a 2D coverage has Long (X) and Lat (Y) axes with CRS EPSG:4326. The resolution for axis Long is 10 and the resolution for axis Lat is -10. The geo bounds of axis Long are [0:180] and the geo bounds of axis Lat are [0:90].

  • Calculate slicing on Long axis by geo coordinates to grid coordinates:

    - Long(0):          returns [0]
    - Long(9):          returns [0]
    - Long(10):         returns [1]
    - Long(15):         returns [1]
    - Long(20):         returns [2]
    - Long(40):         returns [4]
    - Long(49.99999):   returns [4]
    - Long(50.0):       returns [5]
  • Calculate trimming on Long axis by geo coordinates to grid coordinates:

    - Long(0:5):         returns [0:0]
    - Long(0:10):        returns [0:0]
    - Long(0:14.999):    returns [0:0]
    - Long(0:15):        returns [0:1]
    - Long(0:24.999):    returns [0:1]
    - Long(0:25.0):      returns [0:2]
    - Long(9,11): returns [0:0]

5.4.2. CIS 1.0 to 1.1 Transformation

Under WCS 2.1 - ie: with SERVICE=2.1.0 - both DescribeCoverage and GetCoverage requests understand the proprietary parameter OUTPUTTYPE=GeneralGridCoverage which formats the result as CIS 1.1 GeneralGridCoverage even if it has been imported into the server as a CIS 1.0 coverage, for example:



5.4.3. Polygon/Raster Clipping

WCS and WCPS support clipping of polygons expressed in the WKT format format. Polygons can be MultiPolygon (2D), Polygon (2D) and LineString (1D+). The result is always a 2D coverage in case of MultiPolygon and Polygon, and is a 1D coverage in case of LineString.

Further clipping patterns include curtain and corridor on 3D+ coverages from Polygon (2D) and Linestring (1D). The result of curtain clipping has the same dimensionality as the input coverage whereas the result of corridor clipping is always a 3D coverage, with the first axis being the trackline of the corridor by convention.

In WCS, clipping is expressed by adding a &CLIP= parameter to the request. If the SUBSETTINGCRS parameter is specified then this CRS also applies to the clipping WKT, otherwise it is assumed that the WKT is in the Native coverage CRS. In WCPS, clipping is done with a clip function, much like in rasql.

Further information can be found in the rasql clipping section. Below we list examples illustrating the functionality in WCS and WCPS. Clipping Examples

  • Polygon clipping on coverage with Native CRS EPSG:4326, for example:

    • WCS:

      ▶ show

    • WCPS:

      ▶ show

  • Polygon clipping with coordinates in EPSG:3857 (from subsettingCRS parameter) on coverage with Native CRS EPSG:4326, for example:

    • WCS:

      ▶ show

    • WCPS:

      ▶ show

  • Linestring clipping on a 3D coverage with axes X, Y, ansidate, for example:

    • WCS:

      ▶ show

    • WCPS:

      ▶ show

  • Multipolygon clipping on 2D coverage, for example:

    • WCS:

      ▶ show

    • WCPS:

      ▶ show

  • Curtain clipping by a Linestring on 3D coverage, for example:

    • WCS:

      ▶ show

    • WCPS:

      ▶ show

  • Curtain clipping by a Polygon on 3D coverage, for example:

    • WCS:

      ▶ show

    • WCPS:

      ▶ show

  • Corridor clipping by a Linestring on 3D coverage, for example:

    • WCS:

      ▶ show

    • WCPS:

      ▶ show

  • Corridor clipping by a Polygon on 3D coverage, for example:

    • WCS:

      ▶ show

    • WCPS:

      ▶ show


Subspace clipping is not supported in WCS or WCPS.

5.4.4. Areas of validity on irregular axes

By default, coefficients on an irregular axes act as single points: subsetting on such an axis must specify exactly the coefficient (slice), or contain the coefficient itself in the lower/upper bounds (trim).

It is possible to customize this behavior when importing data by specifying areas of validity which extend the coefficients from single points into intervals with a start and an end; this concept is also known as footprints or sample space. Refer to the corresponding import documentation <wcst_import-areas-of-validity> on how to specify the areas of validity.

The areas of validity specify a closed interval [start, end] around each coefficient on an irregular axis, such that start <= coefficient <= end. Areas of validity may not overlap.

The start and end may be specified with less than millisecond precision, e.g. "2010" and "2012-05". In this case they are expanded to millisecond precision internally such that start is the earliest possible datetime starting with "2010" (i.e. "2010-01-01T00:00:00.000Z") and end is the latest possible datetime starting with "2012-05" (i.e. "2012-05-31T23:59:59.999Z"). The same semantics applies in subsetting in queries, see Temporal subsets.

The effect on subsetting is as follows:

  • ‘’slicing’’: a coordinate C will select the coefficient with area of validity that intersects C. For example if the coefficient is "2010" (resolved when importing in petascope as "2010-01-01T00:00:00.000Z") and its area of validity has start "2009-01-01" and end "2011-12-31", then slicing at coordinate "2009-05-01" will return the coefficient, as will at "2010-12-31", and anything else between the start and (not including) the end.

  • ‘’trimming’’: an interval lo:hi will select all coefficients with areas of validity that intersect or are contained in the [lo,hi] interval.

If a coverage was imported with custom areas of validity, they will be listed in the WCS DescribeCoverage response under XML element <ras:covMetadata>. A <ras:axes> element contains <ras:axis> child element for each coverage axis wth areas of validity which are then listed as <ras:areasOfValidity> children with start and end attributes, e.g:

▶ show

5.4.5. WCS-T

Currently, WCS-T supports importing coverages in GML format. The metadata of the coverage is thus explicitly specified, while the raw cell values can be stored either explicitly in the GML body, or in an external file linked in the GML body, as shown in the examples below. The format of the file storing the cell values must be

In addition to the WCS-T standard parameters petascope supports additional proprietary parameters, covered in the following sections.


For coverage management normally WCS-T is not used directly. Rather, the more convenient wcst_import Python tool is recommended for Data Import. Inserting coverages

Inserting a new coverage into the server’s WCS offerings is done using the InsertCoverage request.

Table 5.2 WCS-T Standard Parameters

Request Parameter






service standard



2.0.1 or later

WCS version used




Request type to be performed




URl pointing to the coverage to be inserted

One of inputCoverageRef or inputCoverage is required



A coverage to be inserted

One of inputCoverageRef or inputCoverage is required


new | existing

Indicates wheter to use the coverage’s id (“existing”) or to generate a new unique one (“new”)

No (default: existing)

Table 5.3 WCS-T Proprietary Enhancements

Request Parameter





GDAL supported base data type (eg: “Float32”) or comma-separated concatenated data types, (eg: “Float32,Int32,Float32”)

In cases where range values are given in the GML body the datatype can be indicated through this parameter. Default: Byte.



rasdaman tiling clause, see Storage Layout Language

Indicates the array tiling to be applied during insertion


The response of a successful coverage request is the coverage id of the newly inserted coverage. For example: The coverage available at http://schemas.opengis.net/gmlcov/1.0/examples/exampleRectifiedGridCoverage-1.xml can be imported with the following request:


The following example shows how to insert a coverage stored on the server on which rasdaman runs. The cell values are stored in a TIFF file (attachment:myCov.gml), the coverage id is generated by the server and aligned tiling is used for the array storing the cell values:

    &TILING=aligned[0:500,0:500] Updating Coverages

Updating an existing coverage into the server’s WCS offerings is done using the UpdateCoverage request.

Table 5.4 WCS-T Standard Parameters

Request Parameter






service standard



2.0.1 or later

WCS version used




Request type to be performed




Identifier of the coverage to be updated




URl pointing to the coverage to be inserted

One of inputCoverageRef or inputCoverage is required



A coverage to be updated

One of inputCoverageRef or inputCoverage is required


AxisLabel(geoLowerBound, geoUpperBound)

Trim or slice expression, one per updated coverage dimension


The following example shows how to update an existing coverage test_mr_metadata from a generated GML file by wcst_import tool:

    &INPUTCOVERAGEREF=file:///tmp/4514863c_55bb_462f_a4d9_5a3143c0e467.gml Deleting Coverages

The DeleteCoverage request type serves to delete a coverage (consisting of the underlying rasdaman collection, the associated WMS layer (if exists) and the petascope metadata). For example: The coverage test_mr can be deleted as follows:


5.4.6. Renaming a coverage

The /rasdaman/admin/coverage/update non-standard API allows to update a coverage id and the associated WMS layer if one exists (v10.0+). For example, the coverage test_mr can be renamed to test_mr_new as follows:


5.4.7. Update coverage metadata

Coverage metadata can be updated through the interactive rasdaman WSClient on the OGC WCS > Describe Coverage tab, by selecting a text file (MIME type must be one of text/xml, application/json, or text/plain) containing the new metadata; Note that to be able to do this it is necessary to login first in the Admin tab.

The non-standard API for this feature is at /rasdaman/admin/coverage/update which operates through multipart/form-data POST requests. The request should contain 2 parts:

  1. the coverageId to update, and

  2. the path to a local text file to be uploaded to the server.

For example, the below request will update the metadata of coverage test_mr_metadata with the one in a local XML file at /home/rasdaman/Downloads/test_metadata.xml by using the curl tool:

curl --form-string "COVERAGEID=test_mr_metadata"
     -F "file=@/home/rasdaman/Downloads/test_metadata.xml"

5.4.8. Update coverage’s null values

Coverage’s null values can be updated via the non-standard API at /rasdaman/admin/coverage/nullvalues/update endpoint with two mandatory parameters:

  • coverageId: the name of the coverage to be updated

  • nullvalues: null values of coverage’s band(s) with the format corresponding to rasql, see syntax doc.


Value of nullvalues must be encoded in clients properly for special characters such as: [, ], {, }.

Example of using curl tool to update null values of a 3-bands coverage:

curl 'http://localhost:8080/rasdaman/admin/coverage/nullvalues/update'
    -d 'COVERAGEID=test_rgb&NULLVALUES=[35, 25:35, 35:35]'
    -u rasadmin:rasadmin

5.4.9. Update coverage range type

The rangeType of a coverage can be updated via the /rasdaman/admin/coverage/rangetype/update endpoint API with two mandatory parameters:

  • coverageId: the name of the coverage to be updated

  • rangeType: XML string describes coverage’s bands in (Sensor Web Enablement) SWE standards, with root element is <swe:dataRecord>>.

Example of using curl tool to update coverage’s range type of a 2-bands coverage to one band as swe:Quantity and one band as swe:Category:

        <swe:field name="Band1">
            <swe:Quantity definition="http://www.opengis.net/def/dataType/OGC/0/UnsignedInt">
                <swe:label>Band 1 label</swe:label>
                <swe:description>Band 1 description</swe:description>
                        <swe:nilValue reason="Null by no data">25</swe:nilValue>
                <swe:uom code="10^0"/>
        <swe:field name="Band2">
            <swe:Category definition="Band 2 definition which is an attribute">
                        <swe:nilValue reason="Null value from interval">25:35</swe:nilValue>
                        <swe:nilValue reason="Null value from a single value">57</swe:nilValue>
                <swe:codeSpace xlink:href="http://code.list.org/"/>
curl -u rasadmin:rasadmin 'http://localhost:8080/rasdaman/admin/coverage/rangetype/update' \
     -d "COVERAGEID=test_cov&RANGETYPE=$xml"

5.4.10. Convert irregular axis to regular axis

This feature allows to convert a suitable irregular axis to a regular axis, when the irregular axis has equal distances between its coefficients. Typical use case is to convert an irregular time axis with daily / hourly coefficients to regular time axis with time step (time resolution) = day / hour.

The endpoint API is /rasdaman/admin/coverage/update with three mandatory parameters:

  • coverageId: name of the coverage to be updated

  • axis: name of the irregular axis to be converted

  • newtype: only possible value is RegularAxis

Example of using the curl command-line tool to convert the axis ansi in a coverage test_cov to a regular axis:

curl -u rasadmin:rasadmin 'http://localhost:8080/rasdaman/admin/coverage/update' \
     -d "COVERAGEID=test_cov&axis=ansi&newtype=RegularAxis"

5.4.11. Update regular axis’ origin

This feature allows to update an existing regular axis’ origin in a coverage, which effective changes the geo lower and upper bounds of this axis. It is used in the case when the geo bounds of an regular axis are shifted to some unwanted values after coverage imported, and the admin wants to update them to proper values.

The endpoint API is /rasdaman/admin/coverage/update with three mandatory parameters:

  • coverageId: name of the coverage to be updated

  • axis: name of the regular axis to be updated

  • origin: the new origin of the axis. It can be in ISO Datetime format (e.g. "1960-12-31T12:00:00.000Z") if axis is temporal or number (e.g. 23.5) in other cases.


    New geo bounds are calculated in petascope based on the origin like below.

    • If axis’ resolution is positive (e.g. lon, E, X, AnsiDate,…) then:

      • newGeoLowerBound = origin - 0.5 * resolution

      • newGeoUpperBound = newGeoLowerBound + total_grid_pixels * resolution

    • If axis’ resolution is negative (e.g. lat, N, Y,…) then:

      • newGeoUpperBound = origin + 0.5 * abs(resolution)

      • newGeoLowerBound = newGeoUpperBound + total_grid_pixels * resolution

Example of using the curl command-line tool to update origin of axis ansi with resolution=1 day in a coverage test_cov. Before updating, extent of axis is: ["1960-12-31T12:00:00.000Z":"2024-06-24T12:00:00.000Z"]. After udpating, extent of axis is: ["1960-01-01T00:00:00.000Z":"2024-06-25T00:00:00.000Z"].

curl -u rasadmin:rasadmin 'http://localhost:8080/rasdaman/admin/coverage/update' \
     -d 'COVERAGEID=test_cov&axis=ansi&origin="1961-01-01T12:00:00.000Z"'

5.4.12. INSPIRE Coverages

The INSPIRE Download Service is an implementation of the Technical Guidance for the implementation of INSPIRE Download Services using Web Coverage Services (WCS) version 2.0+.

In order to achieve INSPIRE Download Service compliance, the following enhancements have been implemented in rasdaman for WCS GetCapabilities response.

  • Under <ows:OperationsMetadata> there is a new section for INSPIRE metadata for the service. For example, the result below contains two INSPIRE coverages cov_1 and cov_2.

    ▶ show

  • Service Metadata URL field (<inspire_common:URL>), a URL containing the location of the metadata associated with the WCS service which is configured by setting inspire_common_url in petascope.properties.

  • Under <inspire_common:SupportedLanguages> section, the supported language is fixed to eng (English) only.

  • A coverage is considered INSPIRE coverage, if it has a specific URL set by metadataURL attribute. All INSPIRE coverages is listed in the list of XML elements <inspire_dls:SpatialDataSetIdentifier>. The example above contains two INSPIRE coverages, each <inspire_dls:SpatialDataSetIdentifier> element containing an attribute metadataURL to provide more information about the coverages. The value for <inspire_common:Namespace> elements of each INSPIRE coverage is derived from the service endpoint. Create an INSPIRE coverage

Controlling whether a local coverage is treated as an INSPIRE coverage can be done by:

  • Manually sending a request to /rasdaman/admin/inspire/metadata/update with two mandatory parameters:

    • COVERAGEID - the coverage to be converted to an INSPIRE coverage

    • METADATAURL - a URL to an INSPIRE-compliant catalog entry for this coverage; if set to empty, i.e. METADATAURL= then the coverage is marked as non-INSPIRE coverage.

    For example, the coverage test_inspire_metadata can be marked as INSPIRE coverage as follows:

    curl --user rasadmin:rasadmin -X POST \
         --form-string 'COVERAGEID=test_inspire_metadata' \
         -F 'METADATAURL=https://inspire-geoportal.ec.europa.eu/16.iso19139.xml' \
  • Via wcst_import.sh, in an ingredients files with inspire section contains the settings for importing INSPIRE coverage:

    • metadata_url - If set to non-empty string, then the importing coverage will be marked as INSPIRE coverage. If set to empty string or omitted, then the coverage will be updated as non-INSPIRE coverage.

    For example, the coverage cov_3 will be imported as INSPIRE coverage with this configuration in the ingredients file:

    ▶ show

5.4.13. Check if a coverage exists

Rasdaman offers non-standard API to check if a coverage exists in a simpler and faster way than doing a GetCapabilities or a DescribeCoverage request. The result is a true/false string literal.



5.4.14. GetCapabilities response extensions

The WCS GetCapabilities response contains some rasdaman-specific extensions, as documented below.

  • The <ows:AdditionalParameters> element of each coverage contains some information which can be useful to clients:

    • sizeInBytes - an estimated size (in bytes) of the coverage

    • sizeInBytesWithPyramidLevels - an estimated size (in bytes) of the base coverage plus sizes of its pyramid coverages; only available if this coverage has pyramid

    • axisList - the coverage axis labels in geo CRS order


    ▶ show

5.4.15. DescribeCoverage rasdaman metadata

Rasdaman may generate specific metadata in the DescribeCoverage response for a particular coverage; this section documents the structure of this metadata.

  1. If areas of validity were defined during the import of a coverage, then they will be listed under an <axes> element for each affected axis. More details on the metadata structur can be found here.

  2. If global metadata was specified explicitly or harvested automatically from input files during data import (docs), it will be listed in this section with multiple elements per metadata key/value pair. Each element has a name under the ras: namespace set to the key, and text content set to the value. For example, explicit metadata in the ingredients file specified like this:

    "metadata": {
      "global": {
        "title": "ERA5-Land monthly averaged data from 1950 to present",
        "data_type": "Gridded"

    will appear as follows in the DescribeCoverage:

      <ras:title>ERA5-Land monthly averaged data from 1950 to present</ras:title>
  3. If a color palette table was specified explicitly or harvested automatically from input files during data import (docs), it will be listed under a <ras:colorPaletteTable> element. An example of color palette table and metadata (see previous point) collected from the input file:

    ▶ show

    Listed with gdalinfo, the file has the following metadata:

    ▶ show

  4. If band and axis metadata has been specified explicitly or harvested automatically from input files during data import (docs), they will be listed under <ras:bands> and <ras:axes> elements respectively. An axis A will be a separate element <ras:A>, containing the axis metadata elements; it works the same for the coverage bands. For example, the import ingredients configuration listed in the example here will result in the following DescribeCoverage structure:

    ▶ show

5.4.16. GetCoverage request Interpolation

There are two supported formats for interpolation parameter in WCS GetCoverage requests:

  • Full URI, e.g. http://www.opengis.net/def/interpolation/OGC/1.0/bilinear

  • Short hand format, e.g. bilinear

5.4.17. CRS notation

When a CRS is used in WCS / WCPS request for doing subsetting or projecting to an output CRS, these notations below are supported:

  • Full CRS URL, e.g. http://localhost:8080/rasdaman/def/crs/EPSG/0/4326 (standardized format)

  • Shorthand CRS with authority, version and code, e.g. EPSG/0/4326

  • Shorthand CRS with authority and code, e.g. EPSG:4326

5.5. OGC Web Coverage Processing Service (WCPS)

The OGC Web Coverage Processing Service (WCPS) standard defines a protocol-independent language for the extraction, processing, analysis, and fusion of multi-dimensional gridded coverages, often called datacubes.

5.5.1. General

WCPS requests can be submitted in both abstract syntax (example) and in XML (example).

For example, using the WCS GET/KVP protocol binding, a WCPS request can be sent through the following ProcessCoverages request:


The following subsections list enhancements rasdaman offers over the OGC WCPS standard. A brief introduction to the WCPS language is given in the WCPS cheatsheet; further educational material is available on EarthServer.

5.5.2. Polygon/Raster Clipping

The non-standard clip() function enables clipping in WCPS. The signature is as follows:

clip( coverageExpression, wkt [, subsettingCrs ] )


  • coverageExpression is an expression of result type coverage, e.g. dem + 10;

  • wkt is a valid WKT (Well-Known Text) expression, e.g. POLYGON((...)), LineString(...);

  • subsettingCrs is an optional CRS URL in which the wkt coordinates are expressed, e.g. "http://localhost:8080/rasdaman/def/crs/EPSG/0/4326". Clipping Examples

  • Polygon clipping with coordinates in EPSG:4326 on coverage with native CRS EPSG:3857:

    ▶ show

  • Linestring clipping on 3D coverage with axes X, Y, datetime.

    ▶ show

  • Linestring clipping on 2D coverage with axes X, Y.

    ▶ show

    In this case with WITH COORDINATES extra parameter, the geo coordinates of the values on the linestring will be included as well in the result. The first two bands of the result holds the coordinates (by geo CRS order), and the remaining bands the original cell values. Example output for the above query:

    .. code-block:: text

    “-28.975 119.975 90”,”-28.975 120.475 84”,”-28.475 120.975 80”, …

  • Multipolygon clipping on 2D coverage.

    ▶ show

  • Curtain clipping by a Linestring on 3D coverage

    ▶ show

  • Curtain clipping by a Polygon on 3D coverage

    ▶ show

  • Corridor clipping by a Linestring on 3D coverage

    ▶ show

  • Corridor clipping by a Polygon on 3D coverage (geo CRS: EPSG:4326) with input geo coordinates in EPSG:3857.

    ▶ show

5.5.3. Auto-ratio for spatial scaling

The scale() function allows to specify the target extent of only one of the spatial horizontal axes, instead of requiring both. In such a case, the extent of the unspecified axis will be determined automatically while preserving the original ratio between the two spatial axes.

For example in the request below, the extent of Lat will be automatically set to a value that preserves the ratio in the output result:

▶ show

5.5.4. Non-scaled axes are optional

The scale() function will implicitly add the full domains of unspecified non-spatial axes of a given coverage, with the effect that they will not be scaled in the result. This deviates from the OGC WCPS standard, which requires all axes to be specified with target domains, even if the resolution of an axis should not be changed in the result.

In the example query below, a 3D coverage is scaled only spatially because only the spatial axes E and N are specified in the target scale intervals, while the ansi non-spatial axis is omitted.

▶ show

5.5.5. Extensions on domain functions

The domain interval can be extracted from a domain and imageCrsDomain. Both the interval - ie: [lowerBound:upperBound] - and lower as well as upper bound can be retrieved for each axis.



with .lo or .hi returning the lower bound or upper bound of this interval.

Further, the third argument of the domain() operator, the CRS URL, is optional. If not specified, domain() will use the CRS of the selected axis (ie, the second argument) instead.

For example, the coverage AvgLandTemp has 3 dimensions with grid bounding box of (0:184, 0:1799, 0:3599), and a geo bounding box of ("2000-02-01:2015-06-01", -90:90, -180:180). The table below lists various expressions and their results:

Table 5.5 Non-standard domain operations



imageCrsdomain($c, Long)


imageCrsdomain($c, Long).lo


imageCrsdomain($c, Long).hi


domain($c, Long)


domain($c, Long).lo


domain($c, Long).hi


5.5.6. LET clause

An optional LET clause allows binding alias variables to valid WCPS query sub-expressions; subsequently the alias variables can be used in the return clause instead of repeating the aliased sub-expressions.

The syntax in context of a full query is as follows:

LET $variable := assignment [ , $variable := assignment ]


assignment ::= coverageExpression | [ dimensionalIntervalList ]

An example with the first case:

for $c in (test_mr)
let $a := $c[i(0:50), j(0:40)],
    $b := avg($c) * 2
  encode( scale( $c, { imageCrsDomain( $c ) } ) + $b, "image/png" )

The second case allows to conveniently specify domains which can then be readily used in subset expression, e.g:

for $c in (test_mr)
let $dom := [i(20), j(40)]
  encode( $c[ $dom ] + 10, "itext/json" )

5.5.7. min and max functions

Given two coverage expressions A and B (resulting in compatible coverages, i.e. same domains and types), min(A, B) and max(A, B) calculate a result coverage with the minimum / maximum for each pair of corresponding cell values of A and B.

For multiband coverages, bands in the operands must be pairwise compatible; comparison is done in lexicographic order with the first band being most significant and the last being least significant.

The result coverage value has the same domain and type as the input operands.

5.5.8. Positional parameters

Positional parameters allow to reference binary or string values in a WCPS query, which are specified in a POST request in addition to the WCPS query. Each positional parameter must be a positive integer prefixed by a $, e.g. $1, $2, etc.

The endpoint to send WCPS query by POST with extra values is:


with the mandatory parameter query and optional positional parameters 1, 2, etc. The value of a positional parameter can be either a binary file data or a string value. Example

One can use the curl tool to send a WCPS request with positional parameters from the command line; it will read the contents of specified files automatically if they are prefixed with a @.

For example, to combine an existing coverage $c with two temporary coverages $d and $e provided by positional parameters $1 and $2 into a result encoded in png format (specified by positional parameter $3):

curl -s "http://localhost:8080/rasdaman/ows?SERVICE=WCS&VERSION=2.0.1&REQUEST=ProcessCoverages" \
     --form-string 'query=for $c in (existing_coverage), $d in (decode($1)), $e in (decode($2))
         return encode(($c + $d + $e)[Lat(0:90), Long(-180:180)], "$3"))' \
     -F "1=@/home/rasdaman/file1.tiff" \
     -F "2=@/home/rasdaman/file2.tiff" \
     -F "3=png" > test.png

5.5.9. Decode Operator in WCPS

The non-standard decode() operator allows to combine existing coverages with temporary coverages created in memory from input files attached in the request body via POST.

Only 2D geo-referenced files readable by GDAL are supported. One way to check if a file $f is readable by GDAL is with gdalinfo $f. netCDF/GRIB files are not supported. Syntax

The syntax is


where ${positional_parameter) refers to files in the POST request. See the previous section for more details on positional parameters. Example

See example on positional parameters.

5.5.10. Case Distinction

Conditional evaluation based on the cell values of a coverage is possible with the switch expression. Although the syntax is a little different, the semantics is very much compatible to the rasql case statement, so it is recommended to additionally have a look at its corresponding documentation. Syntax

  CASE condExp RETURN resultExp
  [ CASE condExp RETURN resultExp ]*
  DEFAULT RETURN resultExpDefault

where condExp and resultExp are either scalar-valued or coverage-valued expressions. Constraints

  • All condExp must return either boolean values or boolean coverages

  • All resultExp must return either scalar values, or coverages

  • The domain of all condition expressions must be the same

  • The domain of all result expressions must be the same (that means same extent, resolution/direct positions, crs) Evaluation Rules

If the result expressions return scalar values, the returned scalar value on a branch is used in places where the condition expression on that branch evaluates to True. If the result expressions return coverages, the values of the returned coverage on a branch are copied in the result coverage in all places where the condition coverage on that branch contains pixels with value True.

The conditions of the statement are evaluated in a manner similar to the IF-THEN-ELSE statement in programming languages such as Java or C++. This implies that the conditions must be specified by order of generality, starting with the least general and ending with the default result, which is the most general one. A less general condition specified after a more general condition will be ignored, as the expression meeting the less general expression will have had already met the more general condition.

Furthermore, the following hold:

  • domainSet(result) = domainSet(condExp1)

  • metadata(result) = metadata(condExp1)

  • rangeType(result) = rangeType(resultExp1). In case resultExp1 is a scalar, the result range type is the range type describing the coverage containing the single pixel resultExp1. Examples

  case $c < 10 return {red: 0;   green: 0;   blue: 255}
  case $c < 20 return {red: 0;   green: 255; blue:   0}
  case $c < 30 return {red: 255; green: 0;   blue:   0}
  default      return {red: 0;   green: 0;   blue:   0}

The above example assigns blue to all pixels in the $c coverage having a value less than 10, green to the ones having values at least equal to 10, but less than 20, red to the ones having values at least equal to 20 but less than 30 and black to all other pixels.

  case $c > 0 return log($c)
  default     return 0

The above example computes log of all positive values in $c, and assigns 0 to the remaining ones.

  case $c < 10 return $c * {red: 0;   green: 0;   blue: 255}
  case $c < 20 return $c * {red: 0;   green: 255; blue: 0}
  case $c < 30 return $c * {red: 255; green: 0;   blue: 0}
  default      return      {red: 0;   green: 0;   blue: 0}

The above example assigns blue: 255 multiplied by the original pixel value to all pixels in the $c coverage having a value less than 10, green: 255 multiplied by the original pixel value to the ones having values at least equal to 10, but less than 20, red: 255 multiplied by the original pixel value to the ones having values at least equal to 20 but less than 30 and black to all other pixels.

5.5.11. CIS 1.0 to CIS 1.1 encoding

For output format application/gml+xml WCPS supports delivery as CIS 1.1 GeneralGridCoverage by specifying an additional proprietary parameter outputType in the encode() function, e.g:

for c in (test_irr_cube_2)
return encode( c, "application/gml+xml",
                  "{\"outputType\":\"GeneralGridCoverage\"}" )

5.5.12. Query Parameter

For specifying the WCPS query in a request, in addition to the query parameter the non-standard q parameter is also supported. A request must contain only one q or query parameter.


5.5.13. Describe Operator in WCPS

The non-standard describe() function delivers a “coverage description” of a given coverage without the range set, in either GML or JSON. Syntax

describe( coverageExpression, outputFormat [ , extraParameters ] )


  • outputFormat is a string specifying the format encoding in which the result will be formatted. Formats are indicated through their MIME type identifier, just as in encode(). Formats supported:

    • application/gml+xml or gml for GML

    • application/json or json for JSON

  • extraParameters is an optional string containing parameters for fine-tuning the output, just as in encode(). Options supported:

    • "outputType=GeneralGridCoverage" to return a CIS 1.1 General Grid Coverage structure Semantics

A describe() operation returns a description of the coverage resulting from the coverage expression passed, consisting of domain set, range type, and metadata, but not the range set. As such, this operator is the WCPS equivalent to a WCS DescribeCoverage request, and the output adheres to the same WCS schema.

The coverage description generated will follow the coverage’s type, so one of Rectified Grid Coverage (CIS 1.0), ReferenceableGridCoverage (CIS 1.0), or General Grid Coverage (CIS 1.0).

By default, the coverage will be provided as Rectified or Referenceable Grid Coverage (in accordance with its type); optionally, a General Grid Coverage can be generated instead through "outputType=GeneralGridCoverage". As JSON is supported only from OGC CIS 1.1 onwards this format is only available (i) if the coverage is stored as a CIS 1.1 General Grid Coverage (currently not supported) or (ii) this output type is selected explicitly through an extraParameter.

Efficiency: The describe() operator normally does not materialize the complete coverage, but determines only the coverage description making this function very efficient. A full evaluation is only required if coverageExpression contains a clip() performing a curtain, corridor, or linestring operation. Examples

  • Determine coverage description as a CIS 1.0 Rectified Grid Coverage in GML, without evaluating the range set:

    for $c in (Cov)
    return describe( $c.red[Lat(10:20), Long(30:40), "application/gml+xml" )
  • Deliver coverage description as a CIS 1.1 General Grid Coverage in GML, where range type changes in the query:

    for $c in (Cov)
    return describe( { $c.red; $c.green; $c.blue }, "application/gml+xml",
                                        "outputType=GeneralGridCoverage" )
  • Deliver coverage description as a CIS 1.1 General Grid Coverage, in JSON:

    for $c in (Cov)
    return describe( $c, "application/json", "outputType=GeneralGridCoverage" ) Specific Exceptions

  • Unsupported output format

  • This format is only supported for General Grid Coverage

  • Illegal extra parameter

5.5.14. Flip Operator in WCPS

The non-standard FLIP function enables reversing values from an axis belonging to a coverage expression. The output coverage expression has no changes in the grid domains, base type and dimensionality, but with reversed values and geo bounds of the selected axis; if this axis is irregular then its list coeffcients is reversed as well. See more details in rasql.


flipExp: FLIP coverageExpression ALONG axisLabel

axisLabel: identifier

A FLIP expression consists of coverageExpression which denotes the input coverage, and one axisLabel of the coverage to flip values.


The following examples illustrate the syntax of the FLIP operator.

  • Flipping the 2D coverage expression on its Long axis, by using:

    for $c in (test_mean_summer_airtemp)
               FLIP $c[Lat(-30:-15), Long(125:145)] ALONG Long
             , "image/png")
  • Flipping the 3D coverage expression on its unix time axis, by using:

    for $c in (test_wms_3d_time_series_irregular)
                FLIP $c[Lat(40:90), Long(80:140)] + 20 ALONG unix
              , "json")

5.5.15. Sort Operator in WCPS

The SORT operator enables the user to sort a coverage expression along an axis. The sorting is done by slicing the array of the coverage along that axis, calculating a slice rank for each of the slices, and then rearranging the slices according to their ranks, in an ascending or descending order.

The sorting causes no change in the spatial domain, base type, or dimensionality. This means that the resulting array is the original array but with its values sorted at the sorting axis. See more details in rasql.


After sorting, the geo domains (and coefficients for irregular axis) of the sorted axis are not changed, even though the grid values associated with geo coordinates are changed.


sortExp: SORT coverageExp ALONG sortAxis [listingOrder] BY cellExp

coverageExp: a general coverage expression
sortAxis: identifier.
listingOrder: ASC (default if omitted) | DESC
cellExp: an expression that produces scalar ranks for each slice
along the sortAxis.


One should not do subset (slice/trim) on the sortAxis in the cellExp


The following examples illustrate the syntax of the SORT operator.

  • Sort the 2D coverage expression on its Lon axis according to the coverage values at each longitude index and -40 latitude in ascending order:

    for $c in (test_mean_summer_airtemp)
               SORT $c ALONG Lon BY $c[Lat(-40)]
             , "image/png")
  • Sort the 3D coverage expression on its unix time axis in descending order by the sum of each time slice along it:

    for $c in (test_wms_3d_time_series_irregular)
         SORT $c.Red + 30 ALONG unix DESC BY add($c)
      , "json")

5.5.16. Calendar capabilities

Since v10.3, rasdaman supports quite flexible and powerful methods for addressing temporal coordinates in WCS / WCPS subsetting and other operations. A common use case is aggregating data over a time series per temporal unit, e.g. per day, month, year, etc. Temporal coordinates

Temporal coordinates must be specified in ISO datetime format; the full format including all components is YYYY-MM-DDTHH:MM:SS.SSSZ, explained as follows:

  • YYYY: year

  • MM: month

  • DD: day

  • T: separator between date and time components

  • HH: hour

  • SS: second

  • SSS: milisecond

  • Z: UTC timezone (GMT +0); imported coverages has a fixed timezone UTC currently, there is no support to change to different timezone when importing data

Not all components must be specified: at minimum YYYY is required.

The last component in the datetime value determines its granularity; for example, the granularity of "2015-01-02" is day, while "2015-02" has granularity month. The granularity modifies the range of a datetime string in a subset. For example, the datetime value "2015-01" with granularity month has a time range from lower bound "2015-01-01T00:00:00:000Z" (first moment of January, 2015) to upper bound "2015-01-31T23:59:59:999Z" (last moment of January, 2015). Shifting temporal coordinates

It is possible to add or subtract a time period from a datetime value, thereby shifting the granularity as well. The shift period is specified separated by a whitespace after the datetime string. It is composed of several parts in sequence:

  • Initial designator P (for Period): required

  • Number of years followed by Y

  • Number of months followed by M

  • Number of days followed by D

  • Time designator (separator) T required only if any time components are specified

  • Number of hours followed by H

  • Number of minutes followed by M

  • Number of seconds followed by S

If any number is negative then the preceding datetime is shifted backward instead of forward as usual; non-required parts can be omitted.

For example, time("2015-01-01 P2Y") shifts the input datetime forward by 2 years to time("2017-01-01"). Concatenating time components

Individual time components can be concatenated into a full datetime string with the . operator. Each component is either a string or a temporal function which returns a string. For example time("2015" . "01" . "01") is a slice which will be resolved as time("2015-01-01"). Temporal subsets

The semantics of slices and trims in temporal subsets is clarified subsequently.

Slicing generally selects a single index on a coverage axis. In temporal slices, however, we have to keep in mind the granularity of the datetime value.

  • If the time range defined by the granularity of the slice coordinate encompases exactly one grid index, then this index is returned.

  • Otherwise an error is returned, if it does not contain any grid index or contains more than one index. In this case it may be necessary to adjust the slicing to one with larger or smaller granularity, e.g. from "2015-01" with month granularity to "2015-01-01" with day granularity.

Trimming corresponds to selecting all the indices between a lower and upper bounds. On a temporal axis, the lower bound is converted to the full ISO datetime format as before, while the upper bound is converted up to the last moment of the granularity of the datetime value. For example, a trim time("2015-01-01":"2015-01-03") is first expanded internally to time("2015-01-01T00:00:00.000Z":"2015-01-03T23:59:59.999Z") before it is used to subset the time axis.

For example, selecting only data in January 2023 could be done with time("2023-01":"2023-01"); note that it is not necessary to specify any further time components, e.g. day. Time axis iterator

Coverage constructors and condensers have an OVER clause where iterator variables over the coordinates of a coverage axis (potentially a subset) can be specified. In case of a temporal axis, lists of temporal coordinates are built from coverage domain information or time string literals. Afterwards, when the constructor or condenser are evaluated, the iterator variable goes over the list in sequence.

There are two ways to specify the temporal coordinates for iteration:

  1. iterVar axis( "lowerBound" : "upperBound" [ : "step" ] )

    Here lowerBound and upperBound are datetime values. The step is an optional parameter with same format as specified earlier in Shifting temporal coordinates, which indicates that the iterVar steps from the lower to the upper bound in step increments. If step is omitted, then it is derived from the granularity of the lowerBound. For example, over $pt date("2014" : "2023" : "P1Y" ) is identical to over $pt date("2014" : "2023"), as the granularity of the lower bound is P1Y; the iterated time coordinates will be "2014", "2015", …, "2023".

  2. iterVar axis( "dateTime1", "dateTime2", ... )

    Here iterVar goes through a list of explicitly specified datetime values. For example, this query will build a coverage of maximum values of the data slices at days explicitly listed in the over clause:

    for c in (testCov)
    return encode(
      coverage result
      over $pt t("2023-01-01", "2023-01-02", "2023-01-03")
      values max ( c[t($pt : $pt)] )
    , "csv")
  3. iterVar axis( timeTruncator(...) )

    The set of coordinates to iterate through is in this case generated by a time truncator function. Time truncator functions

Time truncators allow to extract the actually present time coordinates, at a particular granularity, from a particular coverage under inspection. They are used typically in axis iterators of coverage constructor / general condenser.

They are a family of functions tr: list<datetime> -> list<datetime> which reduce accuracy beyond the chosen granularity from all time stamps passed and returns a set without duplicated values of matched datetimes; tr is one of allyears, allmonths, alldays, allhours, allminutes, allseconds.

If $c is a coverage alias in a for clause, and its axis time extends from 2022-11-01 to 2023-03-31, then:

  • allyears($c.domain.date) = "2022", "2023"

  • allmonths($c.domain.date) = "2022-11", …, "2023-03"

  • alldays($c.domain.date) = "2022-11-01", …, "2023-03-31"

  • allhours($c.domain.date) = "2022-11-01T00", …, "2023-03-30T23", "2023-03-31T00"

  • allminutes($c.domain.date) = "2022-11-01T00:00", …, "2023-03-30T23:59", "2023-03-31T00:00"

  • allseconds($c.domain.date) = "2022-11-01T00:00:00.000", .., "2023-03-30T23:59.999", "2023-03-31T00:00.000"

To iterate through all Januars in possible years on the time axis of a coverage, we can write a query as follows:

for $c in (test_365_days_irregular)
return encode(

    coverage result
    over $pt date( allmonths( domain($c, time) ) )
    values $c[date($pt . "-01" : $pt . "-01")],


Here, allyears( domain($c, time) ) may return a list of "2022" and "2023"; then for each $pt, date($pt . "-01" : $pt . "-01") will be resolved as:

  • First iteration: date("2022-01" : "2022-01")

  • Second iteration: date("2023-01" : "2023-01") Time extractor functions

Time extractors allow to extract time components by a specified granularity in the used function name. They are used typically in axis iterators of coverage constructor / general condenser.

They are a family of functions s: list<datetime> -> list<numbers> which return a set without duplicated values of time components contained in the input list; s is one of years, months, days, hours, minutes, seconds.

If $c is a coverage alias in a for clause, and its axis time extends from 2022-11-01 to 2023-03-31, then:

  • years(domain($c, time)) = "2022", "2023"

  • months(domain($c, time)) = "01", "02", "03", "11", "12"

  • days(domain($c, time)) = "01", …, "31"

  • hours(domain($c, time)) = "00", …, "23"

  • minutes(domain($c, time)) = "00", …, "59"

  • second(domain($c, time)) = "00.000", .., "59.999"

For example, if the time axis is irregular with two indexes at "2023-01-01" and "2023-08-01", then months( domain($c, time) ) in the query below returns "01" and "08", and the iterated subsets in date("2023-" .  $m) will be "2023-01" and "2023-08":

for $c in (test_cov)
return encode(
       coverage temp_cov
       OVER $m date( months( domain($c, time) ) )
       VALUES $c[date("2023-" .  $m)],

Another example: the time axis has daily coefficients over years 2020, 2021, 2022, 2023; this query will return all coefficients in February 2020:

for $c in (test_cov)
return encode(
       coverage temp_cov
       OVER $d date( days( domain($c[time("2020-02":"2020-02")], time) ) )
       VALUES $c[date("2020-02-" . $d)],

Here, days( domain($c[time("2020-02":"2020-02")], time) returns a set of 01","02",...,"29", and for each $d in the set date("2020-02-" . $d) will be resolved as:

  • First iteration: date("2020-02-01")

  • Second iteration: date("2020-02-02)

  • Last iteration: date("2020-02-29) Incompatibilites

Prior to this calendar feature, subsets on a temporal axis is done like below:

  • Slice: e.g. time("2015-01-01"), then this value is converted to ISO datetime format "2015-01-01T00:00:00.000Z" and the slice is applied on the time axis. If this axis is irregular and it does not contain the coefficient at the above exact datetime, then petascope throws an exception because the coefficient is not found.

  • Trim: e.g. time("2015-01":"2015-12"), then the subset is converted to ISO datetime format as "2015-01-01T00:00:00:000Z":"2015-12-01T00:00:00:000Z" and if time axis is irregular, then petascope will find any coefficients between these subsets and return them.

5.5.17. Polygonize function

This operation is useful in geographical context, providing ability to layer additional information on existing maps, for example. For more details, see also rasql polygonize.

When the result includes multiple files, as is the case with ESRI Shapefile, the files will be compressed into a single zip archive.


polygonize(covExp, targetFormat)
polygonize(covExp, targetFormat, connectedness)


covExp: coverage expression
targetFormat: StringLit
connectedness: integerLit


The following WCPS query vectorizes a 2D geo-referenced coverage into shape file format:

for $c in (test_mean_summer_airtemp)
    polygonize($c, "ESRI Shapefile")

5.6. OGC Web Map Service (WMS)

The OGC Web Map Service (WMS) standard provides a simple HTTP interface for requesting overlays of geo-registered map images, ready for display.

With petascope, geo data can be served simultaneously via WMS, WMTS, WCS, and WCPS. Further information:

This section mainly covers rasdaman extensions of the OGC WMS standard.

5.6.1. GetMap extensions Transparency and background color

By adding a parameter transparent=true to WMS requests the returned image will have NoData Value=0 in the metadata indicating to the client that all pixels with value 0 value should be considered transparent for PNG encoding format. Example:

▶ show

When transparent=false or omitted in a WMS GetMap request, by default the response has white color for no-data pixels. To colorize no-data pixels the GetMap request should specify BGCOLOR=<hexcolor>, where <hexcolor> is in format 0xRRGGBB, e.g. 0x0000FF for blue color:

▶ show


  • BGCOLOR is valid only with a layer containing 1, 3 or 4 bands.

  • BGCOLOR does not work together with range constructor defined in a WMS style via rasql / WCPS fragments.

  • BGCOLOR is ignored when transparent=true. Interpolation

If in a GetMap request the output CRS requested is different from the coverage’s native CRS, petascope will duly reproject the map applying resampling and interpolation. The algorithm used can be controlled with the non-standard GetMap parameter interpolation=${method}; default is nearest-neighbour interpolation. See Geographic projection for the methods available and their meaning. Example:

▶ show Random parameter

Normally, Web Browser cache the WMS requests from a WMS client (e.g. WebWorldWind). In order to bypass that, one needs to add append extra parameter random with its value equals to a random number for all WMS GetMap requests. For example:

▶ show

In petascope, this random parameter is stripped when petascope receives a W*S request containing this parameter, hence, if the request is already processed, the result stored in the cache will be returned as usual.

5.6.2. nD Coverages as WMS Layers

Petascope allows to import a 3D+ coverage as a WMS layer. To this end, the ingredients file used for wcst_import must contain wms_import": true. For 3D+ coverages this works with recipes regular_time_series, irregular_time_series, and general_coverage. This example shows how to define an irregular_time_series 3D coverage from 2D TIFF files.

Once the coverage is created, GetMap requests can use the additional (non-horizontal) axes for subsetting according to the OGC WMS 1.3.0 standard.

Table 5.6 WMS Subset Parameters for Different Axis Types

Axis Type

Subset parameter






dim_AxisName=… (e.g dim_pressure=…)

According to the WMS 1.3.0 specification, the subset for non-geo-referenced axes can have these formats:

  • Specific value (value1):

  • Range values (min/max):

  • Multiple values (value1,value2,value3,…):

  • Multiple range values (min1/max1,min2/max2,…):


A GetMap request always returns a 2D result. If a non-geo-referenced axis is omitted from the request it will be considered as a slice on the upper bound along this axis. For example, in a time-series the most recent timeslice will be delivered.


5.6.3. GetLegendGraphic request

WMS GetLegendGraphic allows to get a legend PNG/JPEG image associated with a style of a layer. Admin can set a legend image for a style via a style creation request.

Required request parameters:

  • format - data format in which the legend image is returned; only image/png and image/jpeg are supported.

  • layer - the WMS layer which contains the specified style.

  • style - the style which contains the legend image.


    Any further extra parameters will be ignored by rasdaman.

This request, for example, will return the legend image for style color of layer cov1:


When a style of a layer has an associated legend graphic, WMS GetCapabilities will have an additional <LegendURL> XML section for this style. For example:

▶ show

5.6.4. Layer Management

Non-standard API for WMS layer management are listed below.

Layers can be easily created from existing WCS coverages in two ways:

  • Create a new WMS layer from an existing coverage MyCoverage:


    During coverage import this can be done with the wms_import option in the ingredients file.

  • Remove a WMS layer directly:


    Indirectly a layer will be removed when deleting the associated WCS coverage

5.6.5. Style Behavior

When a client sends GetMap requests, the rules below define (in conformance with the WMS 1.3 standard) how a style is applied to the requested layers:

  • If no styles are defined then rasdaman returns the data as-is, encoded in the requested format.

  • If some styles are defined, e.g. X, Y, and Z, then:

    • If the client specifies a style Y, then Y is applied.

    • If the client does not specify a style, then:

      • If the admin has set a style as default, e.g. Z, then Z is applied.

      • Otherwise, if no style has been set as default, then the first style from the list of styles (X) is applied.

5.6.6. Style Management

Styles can be created for layers using rasql and WCPS query fragments. This allows users to define several visualization options for the same dataset in a flexible way. Examples of such options would be color classification, NDVI detection etc. The following HTTP request will create a style with the name, abstract and layer provided in the KVP parameters below


Tomcat version 7+ requires the query (WCPS/rasql fragment) to be URL-encoded correctly. This site offers such an encoding service. Style Definition

A style of a WMS layer can be created via the /rasdaman/admin/layer/style/add endpoint, while an existing style can be updated via the /rasdaman/admin/layer/style/update endpoint. Both endpoints understand the following parameters:

  • COVERAGEID - an existing WMS layer to which the style to be created or updated belongs (mandatory);

  • STYLEID - the style name, must be unique among all the styles of one layer (mandatory);

  • TITLE - an optional style title as human-understandable text;

  • ABSTRACT - an optional description of the what the style does

  • One of the following (optional):

    • RASQLTRANSFORMFRAGMENT - a rasql query expression applied to the map tiles before being returned to the client;

    • WCPSQUERYFRAGMENT - a WCPS query expression applied to the map tiles before being returned to the client;

  • COLORTABLETYPE + COLORTABLEDEFINITION - an optional color table for coloring the map tiles before returning to the client.

At least a query fragment, or a color table, or both, must be specified in the request.

Additionally the updating endpoint supports the following optional parameters:

  • NEWSTYLEID - the style specified with STYLEID will be renamed to the new id specified by this parameter.

  • DEFAULT - if set to true then this style is set as the default of the layer (more details here); if not specified, it is false by default.

  • LEGENDGRAPHIC - associate a PNG/JPEG legend image to this style, specified in Base64 string format; clients can get the legend with a GetLegendGraphic request (more details here). The legend can be removed by setting this parameter to empty, i.e. LEGENDGRAPHIC=.

Below the supported values for COLORTABLETYPE are explained:

  • ColorMap: check Coloring Arrays for more details; the color table definition must be a JSON object, for example:

    ▶ show

  • GDAL: The color table definition must be a JSON object containing 256 color arrays in a colorTable array, example:

    ▶ show

  • SLD: The color table definition must be valid Styled Layer Descriptor XML and contain a ColorMap element. Note that rasdaman will only consider the first sld:ColorMap element in the SLD document, any other SLD elements will be ignored. Check Coloring Arrays for details about the supported types (ramp (default), values, intervals), example ColorMap with type="values":

    ▶ show Style Removal

Removing a style from an existing WMS layer can be done via the /rasdaman/admin/layer/style/remove endpoint, e.g.

/rasdaman/admin/layer/style/remove?COVERAGEID=MyCoverage&STYLEID=mystyle Examples

  • Create a style with a WCPS query fragment and set this style as default style:

    ▶ show

    Variable $c will be replaced by a layer name when sending a GetMap request containing this layer’s style.

  • Create a style with a rasql query fragment:

    ▶ show

    Variable $Iterator will be replaced with the actual name of the rasdaman collection and the whole fragment will be integrated inside the regular GetMap request.

  • Multiple layers can be used in a style definition. Besides the iterators $c in WCPS query fragments and $Iterator in rasql query fragments, which always refer to the current layer, other layers can be referenced by name using an iterator of the form $LAYER_NAME in the style expression.

    Example: create a WCPS query fragment style referencing 2 layers ($c refers to layer sentinel2_B4 which defines the style):

    ▶ show

    Then, in any GetMap request using this style the result will be obtained from the combination of the 2 layers sentinel2_B4 and sentinel2_B8:

    ▶ show

    The WCPS query fragment must follow one of these patterns in order to allow petascope to instantiate the fragment into a full valid query for any WMS request bbox:

    • If no subsets are in the style, just use $c and $otherLayerName as usual in the fragment query.

    • If there is a subset, usually a slice on non-XY axes for 3D+ coverages, then the subsets must follow the pattern $c[axisLabel(geoSubset),..] or $otherLayerName[axisLabel(geoSubset),..].

  • WMS styling supports colorizing the result of GetMap request when the style is requested by applying a color table definition to it. A style can contain either one or both a query fragment and color table definitions. The request supports two parameters for this purpose: COLORTABLETYPE with valid values ColorMap, GDAL and SLD, and COLORTABLEDEFINITION containing the corresponding definition.

    ▶ show

5.6.7. Pyramid Management

The following WMS requests are used to manage downscaled coverages, which are primarily created as pyramid levels of a particular base coverage. Internally they are used for efficient zooming in/out in WMS, and downscaling when using the scale() function in WCPS or scaling extension in WCS.

Only regular axes, typically spatial X and Y, can be downscaled for this purpose.

Below the API for pyramid management are covered:

  • Create a pyramid member coverage c for a base coverage b with given scale factors for each axis. Only regular axes can have a scale factor > 1. E.g. to create a downscaled coverage cov_3D_4 of a 3D coverage cov_3D that is 4x smaller for Lat and Long regular axes (Time is irregular axis, hence, scale factor must be 1):

    ▶ show

    wcst_import can execute create pyramid requests automatically when importing data with the scale_levels or scale_factors options in the ingredients file; more details here.

  • Add a list of existing coverage c, d, e, … as pyramid member coverages of a base coverage b. The scale factors for each axis of the pyramid member coverage will be calculated implicitly based on axis resolutions. If harvesting=true (default is false), recursively collect pyramid members of c, d, e, … and add them as pyramid member of b. E.g. to add a downscaled coverage cov_3D_4 (4x smaller) and its pyramid members recursively as pyramid member coverages of base coverage cov_3D:

    ▶ show

    wcst_import provides several options for conveniently adding pyramid members in the ingredients file.

  • Remove a list of existing pyramid member coverage c, d, e, … from a base coverage b. The coverages c, d, e, … will still exist, until they are removed with a WCS-T DeleteCoverage request. E.g. to remove pyramid member cov_3D_4 from base coverage cov_3D:

    ▶ show

  • List all pyramid member coverages associated with a base coverage in JSON-formatted output. E.g. to list the pyramid members of Sentinel2_10m:

    ▶ show

    Example output:

    ▶ show

5.6.8. Testing a WMS Setup

A rasdaman WMS service can be tested with any conformant client through a GetMap request like the following:

▶ show

5.6.9. Errors and Workarounds Cannot load new WMS layer in QGIS

In this case, the problem is due to QGIS caching the WMS GetCapabilities from the last request so the new layer does not exist (see clear cache solution).

5.7. OGC Web Map Tile Service (WMTS)

The OGC Web Map Tile Service (WMTS) standard provides a simple HTTP interface for requesting overlays of geo-registered map images as small tiles, ready for display. WMTS works like a subset of OGC Web Map Service (WMS) standard and it provides extra functionalities from the imported WMS Layer. See more details for processing WMS requests in rasdaman.

rasdaman supports WMTS with the following request types in key-value pairs (KVP) format:

  • GetCapabilities for obtaining a list of layers and their associated TileMatrixSets offered together with an overall service description;

  • GetTile for downloading a 2D image (called Tile) as a small subset from a requesting Layer. This request works mostly as same as WMS GetMap request with some extra parameters for selecting the requested tile.

5.7.1. GetCapabilities extension

This request is used to describe the general information (e.g. service owner, contacts,…) about the server, and most importantly are the advertised WMTS Layers with supported styles and associated TileMatrixSet objects.

  • A TileMatrixSet contains the list of pyramid members (each member is called TileMatrix in WTMS standard) in a CRS (typically EPSG:4326) of an associated layer.

  • A TileMatrix is a 2D matrix of Tiles, each Tile is a 2D image and it has the fixed size: 256 x 256 pixels. To obtain a Tile from a TileMatrix, one needs two zero-based indices: TileRow in the height dimension and TileCol in the width dimension. In case, a dimension (width/height) of a TileMatrix is less than 256 pixels, then, this dimension contains only 1 Tile with the number of pixels from this dimension. For example, a pyramid member has grid domains 36 x 20 pixels, then, the associated TileMatrix contains only 1 Tile with size 36 x 20 pixels.

Each layer has a mandatory reference to a TileMatrixSet in CRS EPSG:4326; if layer’s native CRS is not EPSG:4326, then, it has an extra reference to another TileMatrixSet in this CRS (e.g. EPSG:32633).

The naming convention for TileMatrixSet is: LayerName:EPSG:code. For example a WMTS layer’s, called germany_temperature has a native CRS EPSG:32633, then it has references to two TileMatrixSets: 1. germany_temperature:EPSG:4326 and 2. germany_temperature:EPSG:32633.

The WTMS GetCapabilities parameters are described in the below table:

Table 5.7 WMTS GetCapabilities Standard Parameters

Request Parameter






Service standard




WMTS version used




Request type to be performed


For example, a WMTS GetCapabilities request in KVP format:

▶ show

5.7.2. GetTile extension

This request is used to get a 2D small subset (called a Tile; typically it has fixed size 256 x 256 pixels) of a requesting layer. The result is encoded in supported formats (image/png and image/jpeg).

Based on the result of WMTS GetCapabilities request, one can pick the proper TileMatrixSet and TileMatrix (pyramid member) referenced by a layer to get the best detailed result at a zoom level with good performance.


Unlike WMS GetMap request, WMTS GetTile request only supports processing on a layer and an optional associated style of this layer.

The WTMS GetTile parameters are described in the below table:

Table 5.8 WMTS GetTile Standard Parameters

Request Parameter






service standard




WMTS version used




Request type to be performed




A layer name to be requested




A style name (can be null) of the layer to be requested




Encoded format (image/png or image/jpeg) of the output




A TileMatrixSet name to be requested




A TileMatrix name to be requested




A row index of the requesting TileMatrix




A column index of the requesting TileMatrix


Other dimensions


Value allowed for this dimension (e.g. TIME, ELEVATION…)


For example, a WMTS GetTile request in KVP format to get a tile, encoded in image/png from a TileMatrixSet in CRS EPSG:4326:

▶ show

5.8. Experimental API

The following sections cover API supported by rasdaman, which are still experimental in their standardization or implementation. As the corresponding specifications have not been released in stable version and are mostly still in flux, the implementation in rasdaman my be out of sync to some extent.

5.8.1. OGC API - Coverages (OAPI)

The OGC API family of standards is organized by resource type. OGC API - Coverages specifies the fundamental API building blocks for interacting with coverages. The spatial data community uses the term ‘coverage’ for homogeneous collections of values located in space/time, such as spatio-temporal sensor, image, simulation, and statistics data.

Following the /rasdaman/oapi endpoint prefix, several features from OGC API - Coverages are supported:

  • Collection listing:

    • /collections - returns the list of names of the collections hosted by the server

    • /collections/{collectionId} - returns the collection object identified by {collectionId}

  • Coverage access:

    • /collections/{coverageId} - returns the full coverage with the specified {coverageId}

    • /collections/{coverageId}?subset={subset}&f={format} - returns the coverage subsetted by {subset} and encoded in {format}; typically called coverage subsetting

    • collections/test_rgb/coverage?properties={selectedBands}&f={format} - returns the coverage with bands subsetted by {selectedBands}``and encoded in ``{format}; typically called range subsetting

    • collections/scale-X&f={format} with X is one of factor|size|axes - returns the scaled coverage encoded in {format}; typically called coverage scaling

  • Coverage component access:

    • /collections/{collectionId}/domainset - returns the domain set of the coverage with the specified id

    • /collections/{collectionId}/rangetype - returns the range type of the coverage with the specified id

    • /collections/{collectionId}/rangeset - returns the range set of the coverage with the specified id

    • /collections/{collectionId}/metadata - returns the metadata of the coverage with the specified id

  • Coverage processing by WCPS:

    • /wcps?Q={encodedQuery} - sends an encoded WCPS query to the OAPI endpoint and return the result accordingly to the query

5.8.2. openEO

openEO is an API that allows users to connect to Earth observation cloud back-ends in a simple and unified way. The capabilities are similar to the OGC WCPS standard.

Rasdaman supports (partially) openEO API (1.2.0) at endpoint /rasdaman/openeo. In particular the following features are supported:

  • /processes - returns the list of predefined processes

  • /process_graphs - returns the list of custom user-defined processes

  • /process_graphs/{processGraphId} - insert / update a user-defined process via POST HTTP request

  • /process_graphs/{processGraphId} - delete a user-defined process via DELETE HTTP request

  • /result - synchronously send a process description in JSON format via a POST HTTP request and get back the result from rasdaman

For authentication the /rasdaman/credentials/basic endpoint allows authenticate via basic header mechanism, which returns a token that can be used in further openEO requests.

5.8.3. OGC GeoDataCube (GDC)

Rasdaman partially supports the OGC GeoDataCube (GDC) specification at endpoint /rasdaman/gdc. Following features are supported:

  • OGC API Coverages: subsetting, range subsetting, scaling (see OGC API - Coverages (OAPI))

  • openEO: authentication, predefined and user-defined processes, and synchronous process execution (see openEO)

5.9. Data Import

Raster data in a variety of formats, such as TIFF, netCDF, GRIB, etc. can be imported in rasdaman through the wcst_import.sh utility. Internally it is based on WCS-T requests, but hides the complexity and maintains the geo-related metadata in its so-called petascopedb while the raster data get imported into the rasdaman array store.

Building large time-series / datacubes, mosaics, etc. and keeping them up-to-date as new data become available is supported for a large variety of data formats and file/directory organizations.

The systemtest contains many examples for importing different types of data. Note that the ingest.template.json are template files which cannot be directly imported, as several variables need to be set first.

5.9.1. Introduction

The wcst_import.sh tool is based on two concepts:

  • Recipe - A recipe defines how a set of data files can be combined into a well-defined coverage (e.g. a 2-D mosaic, regular or irregular 3-D timeseries, etc.);

  • Ingredients - A JSON file that configures how the recipe should build the coverage (e.g. the server endpoint, the coverage name, which files to consider, etc.).

To execute an ingredients file in order to import some data:

$ wcst_import.sh path/to/my_ingredients.json

Alternatively, wcst_import.sh can be started in the background as a daemon:

$ wcst_import.sh path/to/my_ingredients.json --daemon start

or as a daemon that is “watching” for new data at some interval (in seconds):

$ wcst_import.sh path/to/my_ingredients.json --watch <interval>

For further informations regarding the usage of wcst_import.sh:

$ wcst_import.sh --help

The workflow behind is depicted approximately on Figure 5.1.


Figure 5.1 Data importing process with wcst_import.sh

An ingredients file showing all possible options (across all recipes) can be found here in the same directory there are several examples of different recipes.

The following recipes are provided in the rasdaman repository:

For each one of these there is an ingredients example under the ingredients/ directory, together with an example for the available parameters Further on each recipe type is described in turn, starting with the common options shared by all recipes.


It is required to run only one wcst_import.sh process for registering / importing files to one specific coverage. Running multiple wcst_import.sh processes for building multiple different coverages are allowed (the maximum number of processes is equivalent to the number of rasservers configured in rasmgr.conf file).

5.9.2. Common Options

Some options are commonly applicable to all recipes. We describe these options for each top-level section of an ingredient file: config, input, recipe, and hooks. config section

  • service_url - The endpoint of the WCS service with the WCS-T extension enabled

  • service_is_local - true if the WCS service endpoint runs locally on the same machine, false otherwise. When set to false, the data to be imported will be uploaded to the remote host. This may also be done even when the WCS service endpoint runs locally but has no read permissions on the data files, in which case the only way to import the data is by uploading it to the server; note, however, that this adds a performance penalty, so it should be avoided whenever possible. By default this setting is true.

  • mock - Print WCS-T requests but do not execute anything if set to true. Set to false by default.

  • automated - Set to true to avoid any interaction during the data import process. Useful in production environments for automated deployment for example. By default it is false, i.e. user confirmation is needed to execute the actual import.

  • blocking (since v9.8) - Set to false to analyze and import each file separately (non-blocking mode). By default blocking is set to true, i.e. wcst_import will analyze all input files first to create corresponding coverage descriptions, and only then import them. The advantage of non-blocking mode is that the analyzing and importing happens incrementally (in blocking mode the analyzing step can take a long time, e.g. days, before the import can even begin).


    When importing in non-blocking import mode for coverages with irregular axes, it will only rely on sorted files by filenames and it can fail if these axes’ coefficients are collected from input files’ metadata (e.g: DateTime value in TIFF’s tag or GRIB metadata) as they might not be consecutive. wcst_import will not analyze all files to collect metadata to be sorted by DateTime as in default blocking import mode.

  • default_null_values - This parameter adds default null values for bands that do not have a null value provided by the file itself. The value for this parameter should be an array containing the desired null value either as a closed interval low:high or single values. Example:

    ▶ show


    • If set this parameter will override the null/nodata values present in the input files and the nilValue setting specified in the ingredients file.

    • If this parameter is not set, wcst_import will try to detect these values for bands implicity from the first input file.

    • If set this parameter to: [], then, wcst_import will create a coverage without any null values.


    If a null value interval is specified, e.g "9.96921e+35:*", during encode it will not be preserved as-is because null value intervals are not supported by most formats. In this case it is recommended to first specify a non-interval null value, followed by the interval, e.g. [9.96921e+35, "9.96921e+35:*"].

  • tmp_directory - Temporary directory in which gml and data files are created; should be readable and writable by rasdaman, petascope and current user. By default this is /tmp.

  • crs_resolver - The crs resolver to use for generating WCS-T request. By default it is determined from the petascope.properties setting.

  • url_root - In case the files are exposed via a web-server and not locally, you can specify the root file url here; the default value is "file://".

  • skip - Set to true to ignore files that failed to analyze (i.e. file can be accessed but it is not possible to open and read its content) or failed to import to rasdaman. If set to files_that_fail_to_open, then files that failed to analyze will be skipped, however if a file failed to import to rasdaman, then import process is terminated. By default it is false, i.e. the import process is terminated when a file fails to import.

  • retry - Set to true to retry a failed request. The number of retries is either 5, or the value of setting retries if specified. This is set to false by default.

  • retries - Control how many times to retry a failed WCS-T request; set to 5 by default.

  • retry_sleep - Set number of seconds to wait before retrying after an error; a floating-point number can also be specified for sub-second precision. Default values is 1.

  • track_files - Set to true to allow input files to be tracked in a JSON file <coverage_id>.resume.json containing a list of imported file paths, in order to avoid reimporting them when wcst_import.sh is subsequently executed again. The JSON file is generated in the directory set by the resumer_dir_path setting. This setting is enabled by default. Example content of a resume file S2_L2A_32633_B01.resume.json of a coverage S2_L2A_32633_B01:

    ▶ show

  • resumer_dir_path - The directory in which to store the resume file generated when track_files is set to true. The user invoking wcst_import.sh must have permissions to write in this directory. By default the resume file will be stored in the same directory as the ingredients file.

  • slice_restriction - Limit the slices that are imported to the ones that fit in a specified bounding box. Each subset in the bounding box should be of form { "low": 0, "high": <max> }, where low/high are given in the axis format. Example:

    ▶ show

  • description_max_no_slices - Maximum number of slices (files) to show for preview before starting the actual data import.

  • subset_correction (deprecated since v9.6) - In some cases the resolution is small enough to affect the precision of the transformation from domain coordinates to grid coordinates. To allow for corrections that will make the import possible, set this parameter to true. input section

  • coverage_id - The name of the coverage to be created; if the coverage already exists, it will be updated with the new files collected by paths.

  • paths - List of absolute or relative (to the ingredients file) paths or regex patterns in format acceptable by the Python glob function. Multiple paths separated by commas can be specified. The collected file paths are by default sorted in ascending order before import, either by calculated datetime in time-series recipes, or by lexicographic comparison of the file path strings otherwise. The ordering can be changed to descending or disabled completely with the import_order option.


    wcst_import analyzes each input file from paths and maximum time to open one file for this purpose is 60 seconds. If during this time the file cannot be opened, then wcst_import will try to open it two more times. If the file is still not possible to open, then it will:

    • throw exception and stop the importing process if skip setting is False, or

    • ignore this file and continue with the other input files if skip setting is True

  • inspire section contains the settings for importing INSPIRE coverage:

    • metadata_url - If set to non-empty string, then the importing coverage will be marked as INSPIRE coverage, see more details here. If set to empty string or omitted, then the coverage will be updated as non-INSPIRE coverage. recipe section

  • tiling - (required) Specifies the tile structure to be created for the coverage in rasdaman. You can set arbitrary tile sizes for the tiling option only if the tile name is ALIGNED. Example:

    ▶ show

    For more information on tiling check Storage Layout Language

  • import_order - Indicate in which order the input files collected with the paths setting should be imported. In time-series recipes, the ordering is based on the datetime calculated for each file. In other recipes, e.g. map_mosaic, the ordering is based on lexicographic comparison of the file paths. Possible values are:

    • ascending (default) - import files in ascending order;

    • descending - import files in descending order;

    • none - do not order files in any particular way before import.


    ▶ show

  • wms_import - If set to true, after importing data to coverage, it will also create a WMS layer from the imported coverage and populate metadata for this layer. After that, this layer will be available from WMS GetCapabilties request. Example:

    ▶ show

  • scale_levels - Enable the WMS pyramids feature. Level must be positive number and greater than 1 (note: only spatial geo axes, e.g. Lat and Long are scaled down in the pyramid member coverage). A new coverage as pyramid member of the importing coverage will be created with this pattern. Syntax:

    ▶ show

  • scale_factors - Enable the WMS pyramids feature. It is a more flexible variant of the scale_levels setting. The two settings are exclusive, either scale_levels or scale_factors can exist in the ingredient file. The coverage_id of each factor must be unique in rasdaman and manually set by the user. The factors is a list of decimal values corresponding to the coverage axes according to its CRS order; a scale value for an irregular axis must be 1, while for a regular axis it should be greater than 1; see more details here. For example, you can create two pyramid member 2D coverages which are 2x smaller (cov_level_2) and 4x smaller (cov_level_4) on the regular Lat and Long axes:

    ▶ show

  • import_overviews - If specified with indices (0-based), wcst_import will import the corresponding overview levels defined in the input files as separated coverages with this naming pattern. The selected overview coverages are then added as pyramid memberds to the base importing coverage. For example, to import overview levels 0 and 3 from a tiff file which has 4 overview levels in total

    ▶ show

    you can specify "import_overviews": [0, 3] in the ingredients.

    By default this setting is set to an empty array, i.e. no overview levels will be imported. Only GDAL recipes and gdal version 2+ are supported.

  • import_all_overviews - If specified with true, all overview levels which exist in the input files will be imported. For example, to import all 4 overview levels from a tiff file you can specify "import_all_overviews": true in the ingredient file.

    This setting and import_overviews are exclusive, only one can be specified. By default it is set to false. Only GDAL recipes and gdal version 2+ are supported.

  • import_overviews_only - If specified with true, input files are not imported to the base coverage specified with coverage_id, but only to the overview coverages as specified in the ingredients file by either import_all_overviews or import_overviews. This setting is set to false by default if not specified explicitly.


    If the input files were already imported to the base coverage and they were tracked in <base_coverage_id>.resume.json, it is necessary to remove this resume file in order to import only the overview coverages. Alternatively the ingredients file can be copied to another directory and adapted to set import_overviews_only to true.

  • pyramid_members - List of existing coverages which can be added as pyramid members of the importing coverage, see request. Syntax:

    ▶ show

  • pyramid_bases - List of existing coverages to which the importing coverage will be added as a pyramid member. This parameter has the opposite effect of pyramid_members, see corresponding request. Syntax:

    ▶ show

  • pyramid_harvesting - If set to true, recursively add all nested pyramid members of the pyramid member coverage to the target base coverage. The pyramid member coverage depends on which of these two settings is used:

    • If pyramid_bases is specified, then the currently importing coverage is the pyramid member of the the base coverages listed in pyramid_bases;

    • Otherwise, if pyramid_members is specified, then the currently importing coverage is the base coverage of the pyramid member coverages listed in pyramid_members;

    • Otherwise, if neither of the above options is specified, an error is throws.

    See request for more details on the underlying request sent to petascope when this option is set to true. By default this option is set to false. Image pyramids

Since v9.7 it is possible to create downscaled versions of a given coverage, eventually achieving something like an image pyramid, in order to enable faster WMS requests when zooming in/out.

By using the scale_levels option of wcst_import when importing a coverage with WMS enabled, petascope will create downscaled collections in rasdaman following this pattern: coverageId_<level>. If level is a float, then the dot is replaced with an underscore, as dots are not permitted in a collection name. Some examples:

  • MyCoverage, level 2 -> MyCoverage_2

  • MyCoverage, level 2.45 -> MyCoverage_2_45

Example ingredients specification to create two downscaled levels which are 8x and 32x smaller than the original coverage:

▶ show

Two new WCS-T non-standard requests are utilized by wcst_import for this feature, see here for more information. hooks section

Since v9.8, it is possible to run shell commands before/after data import by adding optional hooks top-level configuration in an ingredient file (on the same level as the config, input, and recipe sections).

There are 2 types of hooks:

  • before_import - Run shell commands before analyzing the input files, e.g. reproject input files from EPSG:3857 to EPSG:4326 with gdalwarp and import the reprojected files only.

  • after_import - Run shell commands after importing the input files, e.g. clean all projected files from running gdalwarp above.

When import mode is set to non-blocking ("blocking": false), wcst_import will run before/after hook(s) for the file which is being used to update coverage, while the default blocking importing mode will run before/after hooks for all input files before/after they are updated to a coverage.

Multiple before/after hooks can be specified, and they will be evaluated in the order in which they are specified. Each hook is a JSON object in the "hooks" JSON array, with parameters as follows:

  • description - Describe what this hook does and wcst_import prints this message when processing this hook.

  • when - mandatory parameter. Run a command before (set to before_import) or after (set to after_import) importing files to a coverage.

  • execute_if - Optional parameter applied only for after_import hooks. If omitted the default value is import_succeeded which indicates that the hook should be executed only for successfully imported files. If it is set to import_failed (note: only works when skip:true is set, see doc) then the hook will be executed only when a file fails to import for some reason.

  • With one of the following options either Bash or Python code must be specified, which will be run for each input file.

    • cmd - specify Bash commands; standard error is redirected to standard output, which wcst_import prints while executing the command. Note that the code is executed in a new Bash process newly forked for every file; if there are many files, this can be costly in terms of performance and memory usage, and it may be better to use python_cmd.

    • python_cmd - specify Python code, which is evaluated in the same Python instance already running wcst_import with the exec() method. It may be preferable to Bash cmd when there are many files to import, or more complex tasks need to be performed with advance math calculations, for example.


      As an ingredients file can contain arbitrary Python or Shell code which wcst_import will execute before/after importing files or during the evaluation of sentence expressions, it can pose a security issue if untrusted users are allowed to write ingredients files to be executed with wcst_import. In this case, it is recommended to make sure the user executing wcst_import is properly restricted on their ingredients files.

  • abort_on_error - Only valid for before_import hook. If set to true, when a cmd bash command returns an error or when a python_cmd raises an Exception, wcst_import terminates immediately.

  • replace_path - Only valid for before_import hook. wcst_import considers the specified absolute paths (globbing is allowed) as the actual absolute file paths to be imported after running a hook, rather than the original input file paths configured in paths setting, under input section.

Example: Import GDAL subdatasets

The example ingredients below contains a pre-hook which replaces the collected file path into a GDAL subdataset form; in this particular case, with the GDAL driver for NetCDF a single variable from the collected NetCDF files is imported.

▶ show

Example: Preprocessing GDAL files before importing

This example ingredients below contains one before_import hook and one after_import hook. The before_import hook runs a bash command to project each input tiff file to a temp tiff file in EPSG:4326 CRS, then, it collects these temp file paths to import. The after_import hook runs a bash command after importing to remove the temp file paths above.

▶ show

5.9.3. Recipe map_mosaic

Well suited for importing a tiled map, not necessarily continuous; it will place all input files given under a single coverage and deal with their position in space. Parameters are explained below.

▶ show

5.9.4. Recipe time_series_regular

Well suited for importing multiple 2-D slices created at regular intervals of time (e.g sensor data, satelite imagery etc) as 3-D cube with the third axis being a temporal one.


This recipe should be used to update an existing coverage with new data only in the case when "track_files": "false" and previously imported files have not been removed. The timestamp for the first input file is set by the time_start setting, so if old imported files are removed the timestamp will be set again to time_start when wcst_import is run again with new files to be imported. The effect is that new input files will override the existing time slices instead of adding new time slices on top of time axis.

Parameters are explained below:

▶ show

5.9.5. Recipe time_series_irregular

Well suited for importing multiple 2-D slices created at irregular intervals of time into a 3-D cube with the third axis being a temporal one. There are two types of time parameters in “options”, one needs to be choosed according to the particular use case:

  • tag_name - e.g. TIFFTAG_DATETIME in the image’s metadata; the metadata should be checked with gdalinfo <file>, as not every image may have the tag. Below is an example:

    ▶ show

  • filename allows an arbitrary pattern to extract the time information from the data file paths. Below is an example:

    ▶ show

5.9.6. Recipe general_coverage

This is a highly flexible recipe that can handle any kind of data files (be it 2D, 3D or n-D) and model them in coverages of any dimensionality. It does that by allowing users to define their own coverage models with any number of bands and axes and fill the necesary coverage information through the so called ingredient sentences inside the ingredients. Coverage parameters

Using ingredient sentences we can define any coverage model directly in the options of the ingredients file. Each coverage model contains the following parts:

  • crs - Indicates the crs of the coverage to be constructed. Either a CRS url can be used e.g. http://localhost:8080/rasdaman/def/crs/EPSG/0/4326 or a shorthand notation CRS1<op>CRS2<op>.., where CRS1/CRS2/.. are of the form EPSG/0/4326 or EPSG:4326, and <op> is either @ or +. For example, a time/date + spatial compound CRS could be OGC/0/AnsiDate@EPSG/0/4326, or OGC:AnsiDate+EPSG:4326.

  • metadata - A group of options controlling metadata extraction and consolidation; more detailed information follows below

  • slicer - A group of options controlling the data decoding and placement into the overall datacube; more detailed information follows below. metadata section

The metadata section specifies in which format you want the metadata (json or xml). It can only contain characters and is limited in size by the backend database limit for CLOB columns; for postgresql (the default backend for petascope) the maximum size is 2GB (source).

  • type - Specifies the format for storing the coverage metadata; xml and json are supported, and it is set to xml by default.

  • global - Specifies fields which should be saved once for the whole coverage (e.g. title, data licence, creator etc). For example a “Title” metadata value can be set with "global": { "Title": "'Drought code'", ... }.

    Global metadata will be collected automatically for netCDF and gdal recipe from the first input file, if the "global" setting is omitted, or it is set to "auto". From netCDF data, the attributes of each variable as well as the global attributes are collected. In case of importing with a gdal slicer, the GDAL metadata will be collected.

    This automatic collection is not done when additional global metadata needs to be added on top of the metadata present in the input file; in this case both the metadata from the file and the additional metadata have to be specified explicitly.

    The specified/collected metadata will be listed in the DescribeCoverage rasdaman metadata.

  • local - Specifies fields which are fetched from each input file to be stored in coverage’s metadata. When subsetting in the output coverage only local metadata associated to the subsetted areas will be added to the result. E.g., "local": { "LocalMetadataKey": "${netcdf:metadata:LOCAL_METADATA}" } sets LocalMetadataKey to a metadata value extracted from the input data; the ${..} is explained in Data expressions. For a more detailed explanation of local metadata see the dedicated Local metadata from input files section.

  • colorPaletteTable - Controls collection of color palette table for the created coverage, which can then be used internally when encoding coverage to, e.g. PNG, to colorize the result. Currently only GDAL-style colorTable with 256 color entries is supported (GDAL docs <https://gdal.org/user/raster_data_model.html#color-table>).

    A path to an explicit Color Palette Table file can be specified, see example file; such a file can be referenced in the ingredients file with, e.g., "colorPaletteTable": "PATH/TO/table.cpt".

    If colorPaletteTable is set to "auto" or not specified at all, and the slicer is set to gdal (see next section for info on slicers), then the color table will be read automatically from the first input file if its metadata contains one.

    If colorPaletteTable is set to an empty string "", any color table metadata will be ignored when creating coverage’s global metadata.

    The specified/collected color palette table will be listed in the DescribeCoverage rasdaman metadata.

  • bands and axes - Allow specifying metadata for the coverage bands and/or axes; more details can be found in Band and axis metadata in global metadata. slicer section

The slicer subsection specifies the driver to use to read from the data files, the required bands from data files and for each axis from the CRS how to obtain the bounds and resolution corresponding to each file.

  • type - Specifies the decoding driver to be used; currently the following are supported:

    • gdal - for TIFF, PNG, and other encoding format that can be read with GDAL (check with gdalinfo <file>);

    • netcdf - for importing NetCDF data. If a netCDF file is flipped on Lat axis (South -> North coordinates increase in the output of ncdump -c) instead of GDAL style (North -> South coordinates decrease), then it is necessary to flip it before importing as rasdaman, e.g. with cdo invertlat input.nc output.nc.

    • grib - for GRIB data. Currently, rasdaman only supports GRIB files with gridType format of regular lat long regular_ll. If the format is different, it is necessary to preprocess the input files into regular grid type. The grid type can be retreived with grib_dump file.grib | grep 'gridType'.

      If a GRIB file is flipped on Lat axis (South -> North with jScansPositively = 0 in the output of grib_dump) instead of GDAL style (North -> South with jScansPositively = 1), then it is necessary to flip it before importing to rasdaman, e.g. with cdo invertlat input.grib output.grib.

  • subtype - Specify a slicer subtype. Currently only "sentinel2" is supported as a value, valid in combination with "type": "gdal". When present in the ingredients, instead of opening files to be imported with GDAL in order to read needed metadata such as CRS and geo bbox, this will be done by reading the MTD_TL.xml file present in the SAFE container that contains the file to be imported. This can be much faster compared to reading the metadata from JPEG 2000 files with GDAL. Note that this only works with file paths on the filesystem in extracted SAFE directories, or with SAFE directories on S3 object storage. In the latter case, wcst_import will try to use s3cmd to retrieve the MTD_TL.xml locally first in /tmp/rasdaman_wcst_import/; these temporary files need to be manually removed.

  • pixelIsPoint - Only valid if type is netcdf or grib. In some cases, by convention in the input files, the coordinates are set in the middle of grid pixels, hence, set to true to extend the lower and upper bounds of each regular axis by half grid pixel to be able to import. By default it is set to false.

  • bands - A list of bands/chanels/variables from the input files which should be imported to the importing coverage. Each entry is a JSON object with the following options, of which identifier and name are mandatory to specify while the rest are optional:

    • identifier - The name of the band in the input file. With GRIB data, only one band can be specified in the ingredients file, and the band identifier must match the shortName field in the GRIB messsages so only those messages will be imported. If no messages matched the band identifier, then all GRIB messages will be imported; this only works for input GRIB files with only one band.

    • name - The name of the band which will be used in the created coverage; this can be set to different from the indentifier;

    • label - The label of the band according to swe:label element; if not set, then, it is set to the name of the band (field’s name)

    • observationType - set the output type in GML format of a band in SWE standard. If omitted, then it set to numerical by default. Valid values are: numeric (in GML showed as swe:Quantity) and categorial (in GML showed as swe:Category).

    • description - Metadata description of the band;

    • definition - Metadata definition of the band, typically it is a URL pointing to online registries, ontologies or dictionaries. If omitted, petascope sets the value to the URL corresponding to band’s data type.

    • nilValue` - Metadata null value of the band; used in case band has only one null value.

      If default_null_values setting is specified, then nilValue setting is ignored.

    • nilReason - Metadata reason for the null value of the band;

    • uomCode - Set the Unit of measurement (uom) code of the band. Besides setting it directly, it can also be derived from the input file metadata, with e.g. ${netcdf:variable:NAME:units} for NetCDF or ${grib:unitsOfFirstFixedSurface} for GRIB. Note: only valid for swe:Quantity.

    • codeSpace - List and define the meaning of all possible values for this component. Note: only valid for swe:Category. ${grib:unitsOfFirstFixedSurface} for GRIB. Note: only used for swe:Category.

    • filterMessagesMatching - Default is empty. If not-empty (a dictionary of user input GRIB keys:values; keys (e.g. shortName) must exist in the input GRIB files), then it filters any GRIB message which has a GRIB value not contain a user input value of a GRIB key.

    • Further "key": "value" entries can be specified to add customized band metadata to the global coverage metadata.

  • axes - A JSON object which configures the properties of each axis of the created coverage with "axisLabel": { properties... }. The possible properties are listed below; generally, gridOrder, min, max, and resolution have to be specified, except for irregular axes where resolution is not applicable.

    • gridOrder - specify the grid order of axes defined by the coverage CRS. If not specified, wcst_import will try to automatically derive the gridOrder according to the documentation below. That may fail with unusual data, in which case it will be necessary to set this setting manually for each axis.

      Axes of a CRS which is not part of the file CRS have gridOrder that is same as the order in the CRS definition. For example, if the coverage CRS is a compound CRS OGC/0/AnsiDate@EPSG/0/4326 and data files themselves have CRS EPSG/0/4326, then gridOrder for the ansi axis in OGC/0/AnsiDate will be 0, and the gridOrder of the EPSG/0/4326 axes will follow with 1 and 2. If the CRS order was reversed to EPSG/0/4326@OGC/0/AnsiDate, then the gridOrder of 4326 axes (Long/Lat) would be 0 and 1, and of AnsiDate (ansi) would be 2. Usually axes of non-file CRS (AnsiDate in this example) will also have setting dataBound: false.

      Below we give hints on how to determine the gridOrder of axes in the file CRS.

      • When data is imported with the gdal or grib slicer, generally the gridOrder is n for X axes (Longitude, E, …), and n+1 for Y axes (Latitude, N, …).

      • When importing data with the netcdf slicer, the gridOrder should usually match the dimension order of the imported variable, which can be checked with ncdump -h; e.g. a variable float dc(time, lat, lon) will have gridOrder n for time, n+1 for lat, and n+2 for lon. This will work well as long as the data conforms to the CF-conventions <https://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/cf-conventions.html#dimensions>, and may otherwise need adjustments if the spatial dimensions are not in Y/X order.

    • crsOrder - The index of the geo axis in the coverage’s CRS (0-based). Note: By default it is not required. Only set when one specifies a different name for this axis, than the one configured in the CRS’s definition; more details can be found here; In this case, each axis must have an unique index crsOrder specified.

    • min - The lower bound of the axis (coordinates in the axis CRS);

    • max- The upper bound of the axis (coordinates in the axis CRS);

    • resolution - The resolution of the axis from the input file; if this axis is irregular, the resolution is set to 1;

    • statements - Import python utility libraries (e.g. datetime / timedelta) to support calculating min, max, resolution, etc; covered in more detail in a subsequent section;

    A few additional options are specific to irregular axes:

    • irregular - Set to true to specify that this axis is irregular, e.g. a time axis with irregular datetime indexes; if not specified, it is set to false by default;

    • directPositions - A list of coefficients which are extracted and calculated based on the axis lower bound from the irregular axis values specified in the input netCDF/GRIB file.

      For example, let’s consider a netCDF file that has a time dimension with attribute units: "days since 1970-01-01 00:00:00". All stored values of the time axis must be converted to datetime based on the lower bound value ("1970-01-01") as an origin. See this ingredients file for a full example.

      ▶ show

    • dataBound - Set to false to specify that this axis should be imported as a slicing point instead of a subset with lower and upper bounds; typical use case for this is when extracting irregular datetime values from the input file names. When not specified it is set to true by default.

      For example, the indexes of an irregular axis ansi could be extracted from dates in the file names of input netCDF files (e.g. GlobLAI-20030101-20030110-H01V06-1.0_MERIS-FR-LAI-HA.nc) through a regular expression.

      ▶ show

    • sliceGroupSize - Group multiple input slices into a single slice in the created coverage, e.g., multiple daily data files onto a single week index on the coverage time axis; explained in more detail here;

    • areasOfValidity - Specify a list of start and end bounds for each coefficient in an irregular axis to extend their areas to [start, end] intervals (see Areas of validity on irregular axes). The start/end intervals must not overlap, and the number of pairs must equal the number of coefficients imported.

      The start and end may be specified with less than millisecond precision, e.g. "2010" and "2012-05". In this case they are expanded to millisecond precision internally such that start is the earliest possible datetime starting with "2010" (i.e. "2010-01-01T00:00:00.000Z") and end is the latest possible datetime starting with "2012-05" (i.e. "2012-05-31T23:59:59.999Z"). The same semantics applies in subsetting in queries, see Temporal subsets.

      By default if not specified, a coefficient is a single point.

      The example below imports 3 input files with the datetime coefficients for the irregular axis ansi collected from the filename ("dataBound": false) and custom areas of validity for the 3 coefficients:

      ▶ show Examples

The examples below illustrate importing data in different formats with the general_coverage recipe; many more can be found in the rasdaman test suite.

  • Commented example for importing GRIB data (only the recipe section is shown for brevity):

    ▶ show

  • Example for importing NetCDF data (full ingredients file here):

    ▶ show

  • Example for importing TIFF data with the gdal driver (full ingredients file here):

    ▶ show Ingredient sentences

An ingredient sentence can be of multiple types:

  • Numeric - e.g. 2, 4.5

  • Strings - e.g. 'Some information'

  • Functions - e.g. datetime('2012-01-01', 'YYYY-mm-dd')

  • Data expressions - Allow to collect information from the data file being imported with a specific format driver. An expression is of form ${driverName:driverOperation} - e.g. ${gdal:minX} or ${netcdf:variable:time:min. All possible expressions are documented in Data expressions.

  • Python expressions - The types above can be combined into any valid Python expression; this allows to do mathematical operations, string parsing, date/time manipulation, etc. E.g. ${gdal:minX} + 1/2 * ${gdal:resolutionX} or datetime(${netcdf:variable:time:min} * 24 * 3600). Expressions can use functions from any Python library which just needs to be explicitly imported as explained in Using libraries in sentences. Data expressions

Each driver allows expressions to extract information from input files. We will mark with capital letters things that vary in the expression. E.g. ${gdal:metadata:FIELD} means that you can replace FIELD with any valid gdal metadata tag such as TIFFTAG_DATETIME. Example ingredients where data expressions are used can be found in Examples. NetCDF




Metadata information



Variable information

${netcdf:variable:VAR_NAME:MODIFIER} where VAR_NAME can be any variable in the file and MODIFIER can be one of: first|last|max|min; Any extra modifiers will return the corresponding metadata field on the given variable

${netcdf:variable:t:min} ${netcdf:variable:t:units}

Dimension information

${netcdf:dimension:DIM_NAME} where DIM_NAME can be any dimension in the file. This will return the value on the selected dimension.

${netcdf:dimension:time} GDAL

Relevant for TIFF, PNG, JPEG, and other 2D data formats.




Metadata information



Geo Bounds

${gdal:BOUND_NAME} where BOUND_NAME can be one of the minX|maxX|minY|maxY


Geo Resolution

${gdal:RESOLUTION_NAME} where RESOLUTION_NAME can be one of the resolutionX|resolutionY



${gdal:ORIGIN_NAME} where ORIGIN_NAME can be one of the originX|originY

${gdal:originY} GRIB





${grib:KEY} where KEY can be any of the keys contained in the GRIB file ${grib:messagenumber} is the special value to get the current processed GRIB message index (starting from 1)

${grib:experimentVersionNumber} File




File Information

${file:PROPERTY} where property can be one of path|name|dir_path|original_path|original_dir_path original_* allows to get the original input file’s path/directory. Used only in before_import hooks with replace_path to replace original input file paths with customized file paths.


Imported File Information

${imported_file:PROPERTY} where property can be one of path|name|dir_path|original_path|original_dir_path Files which were imported to rasdaman (excluding skipped files). This variable is used only in after_import hooks.

${imported_file:path} BBox




Coverage axis information

${bbox:AXIS_LABEL:PROPERTY} where axis_label is one of coverage’s axis name and property can be one of min|max (return the lower/upper geo bound of the selected axis). Used only in after_import hooks where each bbox containing the multi-dimensional bounding box of the data region affected by the update of an input file

${bbox:Lat:min} Special functions

A couple of special functions are available to help with more complicated expressions:

Function and Arguments




  • date

  • time

This function helps to deal with the usual grib date and time format. It returns back a datetime string in ISO format.



  • date

  • format

This function helps to deal with strange date time formats. It returns back a datetime string in ISO format.



  • string

  • regex

  • group

This function extracts information from a string using regex; input is the string you parse, regex is the regular expression, group is the regex group you want to select

    '(.*)_(\\d*-\\d\\d)(.*)', 2),


  • str

  • old

  • new

Replaces all occurrences of a substring with another substring in the input string

        '.tiff', '.xml') Using libraries in sentences

In case the ingredient sentences require functionality from extra Python libraries, they can be imported with a statements option. For example, to calculate the lower bound and upper bound for the time axis ansi (starting days from 1978-12-31T12:00:00) one could use datetime and timedelta from the datatime library.

▶ show

Python functions imported in this way override the special functions provided by wcst_import. For example, the special utility function datetime(date_time_string, format) to convert a string of datetime to an ISO date time format will be overridden when the datetime module is imported with a statements setting.


See details about potential issue for running python code in the ingredients file. Local metadata from input files

Beside the global metadata of a coverage, you can add local metadata for each file which is a part of the whole coverage (e.g. a 3D time-series coverage mosaiced from 2D GeoTiff files).

Under the metadata section add a “local” object with keys and values extracted by using format type expression. Example of extracting an attribute from a netCDF input file:

▶ show

Each file’s envelope (geo domain) and its local metadata will be added to the coverage metadata under <slice>...</slice> element if coverage metadata is imported in XML format. Example of a coverage containing local metadata in XML from 2 netCDF files:

▶ show

Since v10.0, local metadata for input files can be also fetched from corresponding external text files with the optional metadata_file option. For example:

▶ show

When subsetting a coverage which contains a local metadata section from input files (via WC(P)S requests), if the geo domains of subsetted coverage intersect with some input files’ envelopes, only local metadata of these files will be added to the output coverage metadata.

For example: a GetCoverage request with a trim such that crs axis subsets are within netCDF file 1:

▶ show

The coverage’s metadata result will contain local metadata only from netCDF file 1:

▶ show Customized axis labels

By default, the axes to be configured must be matched by their name as defined by the coverage CRS. For example, a CRS OGC/0/AnsiDate@EPSG:4326 defines three axes with labels ansi, Long, and Lat. To configure them, we would have a section as bellow:

▶ show

Since v9.8, one can change the default axis label defined by the CRS through indicating the axis index in the CRS (0-based) with the "crsOrder" setting. For example, to change the axis labels to MyDateTimeAxis, MyLatAxis, and MyLongAxis:

▶ show Group coverage slices

Since v9.8, wcst_import allows to group input files on irregular axes (with "dataBound": false) through the sliceGroupSize option, which would specify the group size as a positive number. E.g:

▶ show

If each input slice corresponds to index X, and one wants to have slice groups of size N, then the index would be translated with this option to X - (X % N).

Typical use case is importing 3D coverage from 2D satellite imagery where the time axis is irregular and its values are fetched from input files by regex expression. Then, all input files which belong to the same time window (e.g 7 days in AnsiDate CRS with "sliceGroupSize": 7) will have the same value, which is the first date of the week. Band and axis metadata in global metadata

Metadata can be manually specified for each band and axis in the ingredient file or automatically derived from input netCDF files. All collected metadata becomes available in the DescribeCoverage rasdaman metadata. band metadata

If "bands" is set to "auto" or does not exist under "metadata" in the ingredient file, all user-specified bands will have metadata which is collected directly from the corresponding variable attributes in the netCDF file; this only works with netcdf slicer.

Otherwise, the user could specify metadata explicitly with keys/value pairs. The band name (e.g. “red”) refers to the rasdaman band name, and not the identifier in the input file. Example:

▶ show


If no metadata should be automatically collected, nor explicitly specified, it is necessary to explicitly set empty metadata:

"metadata": {
  "type": "xml",
  "bands": {
    "red": {},
    "green": {}
} axis metadata

If "axes" is set to "auto" or does not exist under "metadata" in the ingredient file, all user-specified axes will have metadata which is fetched directly from the netCDF file. Metadata for one axis is collected automatically if 1) the axis is not specified, 2) the axis is set to "auto", or 3) the axis is set to ${netcdf:variable:Name:metadata}. The axis label for variable is detected from the min or max value of CRS axis configuration under "slicer/axes" section. For example:

▶ show

Otherwise, the user could specify metadata explicitly as a dictionary of keys/values. The axis name are the rasdaman CRS axis names, and not the dimension variable names in input files.

▶ show


If no metadata should be automatically collected, nor explicitly specified, it is necessary to explicitly set empty metadata:

"metadata": {
  "type": "xml",
  "axes": {
    "i": {},
    "j": {}
} Rotated CRS support

If rasdaman is compiled with GDAL v3.4.1+, importing and querying data with rotated CRS COSMO:101 is supported. The netCDF data usually has to be preprocessed before import:

  1. Invert the latitude axis when it is south to north order (lower to upper coordinates):

    cdo invertlat input.nc inverted_input.nc
  2. Swap the order of the rotated latitude (rlat) and rotated longitude (rlon) axes when the data variable has rlat,rlon order. For example, the float CAPE_ML(time, rlat, rlon) variable can be transformed to float CAPE_ML(time, rlon, rlat) with the following command:

    ncpdq --rdr=time,rlon,rlat inverted_input.nc correct_lon_lat.nc

Example ingredient file for importing the CAPE_ML variable from preprocessed COSMO netCDF data:

▶ show

wcst_import automatically checks if the specified band variables (CAPE_ML in the above example) have a grid_mapping metadata entry (e.g. CAPE_ML:grid_mapping = "rotated_pole"), and adds all metadata from the grid mapping variable (rotated_pole) to the global metadata of the imported coverage. With the added grid_mapping section, the global metadata of the coverage might look as below, for example:

▶ show

When encoding to netCDF in WCS or WCPS requests with the same COSMO:101 CRS, rasdaman will add this grid mapping metadata as a non-dimension variable in the output, so that it has the correct CRS information. The name of the non-dimension variable in the output is set from the identifier value (rotated_pole above).

5.9.7. Recipe wcs_extract

Allows to import a coverage from a remote petascope endpoint into the local petascope. Parameters are explained below.

▶ show

5.9.8. Recipe sentinel1

This is a convenience recipe for importing Sentinel 1 data in particular; currently only GRD/SLC product types are supported, and only geo-referenced tiff files. Below is an example:

▶ show

The recipe extends general_coverage so the "recipe" section has the same structure. However, a lot of information is automatically filled in by the recipe now, so the ingredients file is much simpler as the example above shows.

The other obvious difference is that the "coverage_id" is templated with several variables enclosed in ${ and } which are automatically replaced to generate the actual coverage name during import:

  • modebeam - the mode beam of input files, e.g. IW/EW.

  • polarisation - single polarisation of input files, e.g: HH/HV/VV/VH

If the files collected by "paths" are varying in any of these parameters, the corresponding variables must appear somewhere in the "coverage_id" (as for each combination a separate coverage will be constructed). Otherwise, the data import will either fail or result in invalid coverages. E.g. if all data’s mode beam is IW, but still different polarisations, the "coverage_id" could be "MyCoverage_${polarisation}";

In addition, the data to be imported can be optionally filtered with the following options in the "input" section:

  • modebeams - specify a subset of mode beams to import from the data, e.g. only the IW mode beam; if not specified, data of all supported mode beams will be ingested.

  • polarisations - specify a subset of polarisations to import, e.g. only the HH polarisation; if not specified, data of all supported polarisations will be imported.


  • Only GRD/SLC products are supported.

  • Data must be geo-referenced.

  • Filenames are assumed to be of the format: s1[ab]-(.*?)-grd(.?)-(.*?)-(.*?)-(.*?)-(.*?)-(.*?)-(.*?).tiff or s1[ab]-(.*?)-slc(.?)-(.*?)-(.*?)-(.*?)-(.*?)-(.*?)-(.*?).tiff.

5.9.9. Recipe sentinel2

This is a convenience recipe for importing Sentinel 2 data in particular. It relies on support for Sentinel 2 in more recent GDAL versions. Importing zipped Sentinel 2 is also possible and automatically handled.

Below is an example:

▶ show

The recipe extends general_coverage so the "recipe" section has the same structure. However, a lot of information is automatically filled in by the recipe now, so the ingredients file is much simpler as the example above shows.

The other obvious difference is that the "coverage_id" is templated with several variables enclosed in ${ and } which are automatically replaced to generate the actual coverage name during import:

  • crsCode - the CRS EPSG code of the imported files, e.g. 32757 for WGS 84 / UTM zone 57S.

  • resolution - Sentinel 2 products bundle several subdatasets of different resolutions:

    • 10m - bands B4, B3, B2, and B8 (base type unsigned short)

    • 20m - bands B5, B6, B7, B8A, B11, and B12 (base type unsigned short)

    • 60m - bands B1, B8, and B10 (base type unsigned short)

    • TCI - True Color Image (red, green, blue char bands); also 10m as it is derived from the B2, B3, and B4 10m bands.

  • level - L1C or L2A

If the files collected by "paths" are varying in any of these parameters, the corresponding variables must appear somewhere in the "coverage_id" (as for each combination a separate coverage will be constructed). Otherwise, the import will either fail or result in invalid coverages. E.g. if all data is level L1C with CRS 32757, but still different resolutions, the "coverage_id" could be "MyCoverage_${resolution}"; the other variables can still be specified though, so "MyCoverage_${resolution}_${crsCode}" is valid as well.

In addition, the data to be imported can be optionally filtered with the following options in the "input" section:

  • resolutions - specify a subset of resolutions to import from the data, e.g. only the “10m” subdataset; if not specified, data of all supported resolutions will be ingested.

  • levels - specify a subset of levels to import, so that files of other levels will be fully skipped; if not specified, data of all supported levels will be ingested.

  • crss - specify a list of CRSs (EPSG codes as strings) to import; if not specified or empty, data of any CRS will be imported.

5.9.10. Creating your own recipe

The recipes above cover a frequent but limited subset of what is possible to model using a coverage. WCSTImport allows to define your own recipes in order to fill these gaps. In this tutorial we will create a recipe that can construct a 3D coverage from 2D georeferenced files. The 2D files that we want to target have all the same CRS and cover the same geographic area. The time information that we want to retrieve is stored in each file in a GDAL readable tag. The tag name and time format differ from dataset to dataset so we want to take this information as an option to the recipe. We would also want to be flexible with the time crs that we require so we will add this option as well.

Based on this usecase, the following ingredient file seems to fulfill our need:

▶ show

To create a new recipe start by creating a new folder in the recipes folder. Let’s call our recipe my_custom_recipe:

▶ show

The last command is needed to tell python that this folder is containing python sources, if you forget to add it, your recipe will not be automatically detected. Let’s first create an example of our ingredients file so we get a feeling for what we will be dealing with in the recipe. Our recipe will just request from the user two parameters Let’s now create our recipe, by creating a file called recipe.py

▶ show

Use your favorite editor or IDE to work on the recipe (there are type annotations for most WCSTImport classes so an IDE like PyCharm would give out of the box completion support). First, let’s add the skeleton of the recipe (note that in this tutorial, we will omit the import section of the files (your IDE will help you auto import them)):

▶ show

The first thing you need to do is to make sure the get_name() method returns the name of your recipe. This name will be used to determine if an ingredient file should be processed by your recipe. Next, you will need to focus on the constructor. Let’s examine it. We get a single parameter called session which contains all the information collected from the user plus a couple more useful things. You can check all the available methods of the class in the session.py file, for now we will just save the options provided by the user that are available in session.get_recipe() in a class attribute.

In the validate() method, you will validate the options for the recipe provided by the user. It’s generally a good idea to call the super method to validate some of the general things like the WCST Service availability and so on although it is not mandatory. We also want to validate our custom recipe options here. This is how the recipe looks like now:

▶ show

Now that our recipe can validate the recipe options, let’s move to the describe() method. This method allows you to let your users know any relevant information about the data import before it actually starts. The irregular_timeseries recipe prints the timestamp for the first couple of slices for the user to check if they are correct. Similar behaviour should be done based on what your recipe has to do.

Next, we should define the import behaviour. The framework does not make any assumptions about how the correct method of data import is, however it offers a lot of utility functionality that help you do it in a more standardized way. We will continue this tutorial by describing how to take advantage of this functionality, however, note that this is not required for the recipe to work. The first thing that you need to do is to define an importer object. This importer object, takes a coverage object and imports it using WCST requests. The object has two public methods, ingest(), which imports the coverage into the WCS-T service (note: this can be an insert operation when the coverage was not defined, or update if the coverage exists. The importer will handle both cases for you, so you don’t have to worry if the coverage already exists.) and get_progress() which returns a tuple containing the number of imported slices and the total number of slices. After adding the importer, the code should look like this:

▶ show

In order to build the importer, we need to create a coverage object. Let’s see how we can do that. The coverage constructor requires a

  • coverage_id: the id of the coverage

  • slices: a list of slices that compose the coverage. Each slice defines the position in the coverage and the data that should be defined at the specified position

  • range_fields: the range fields for the coverage

  • crs: the crs of the coverage

  • pixel_data_type: the type of the pixel in gdal format, e.g. Byte, Float32 etc

The coverage object can be built in many ways, we will present one such method. Let’s start from the crs of the coverage. For our recipe, we want a 3D crs, composed of the CRS of the 2D images and a time CRS as indicated. The following lines of code give us exactly this:

▶ show

Let’s also get the range fields for this coverage. We can extract them again from the 2D image using a helper class that can use GDAL to get the relevant information:

▶ show

Let’s also get the pixel base type, again using the gdal helper:

pixel_type = gdal_dataset.get_band_gdal_type()

Let’s see what we have so far:

▶ show

As you can notice, the only thing left to do is to implement the _get_slices() method. To do so we need to iterate over all the input files and create a slice for each. Here’s an example on how we could do that

▶ show

And we are done we now have a valid coverage object. The last thing needed is to define the status method. This method need to provide a status update to the framework in order to display it to the user. We need to return the number of finished work items and the number of total work items. In our case we can measure this in terms of slices and the importer can already provide this for us. So all we need to do is the following:

▶ show

We now have a functional recipe. You can try the ingredients file against it and see how it works.

▶ show

5.9.11. Importing many files

When an ingredient contains many paths to be imported, usually more than 1000, this may lead to hitting some system limits during the import.

In particular when data is imported with the GDAL driver, wcst_import has a cache of open GDAL datasets to avoid reopening files, which is costly. With too many open GDAL datasets limit on max open files can be reached, which is often 1024 (see ulimit -n). wcst_import handles this case by clearing its cache; however, this may degrade import performance, so increasing the limit on open files should be considered.

Furthermore, limits on maximum number of threads may be reached as well, as each open GDAL dataset creates several threads. This will lead to errors such as fork: retry: Resource temporarily unavailable. The maximum allowed number can be observed with cat /sys/fs/cgroup/pids/user.slice/user-<id>.slice/pids.max, where <id> can be found with id -u <user> for the user with which wcst_import is executed. Increasing to a larger value, e.g. 4194304, should solve this issue.

Finally, wcst_import.sh allows to control the gdal cache size with the -c, --gdal-cache-size <size> option. The specified value can be one of: -1 (no limit, cache all files), 0 (fully disable caching), N (clear the cache whenever it has more than N datasets, N should be greater than 0). The default value is -1 if this option is not specified.

5.10. Data export

WCS formats are requested via the format KVP key (<gml:format> elements for XML POST requests), and take a valid MIME type as value. Output encoding is passed on to the the GDAL library, so the limitations on output formats are devised accordingly by the supported raster formats of GDAL. The valid MIME types which Petascope may support can be checked from the WCS 2.0.1 GetCapabilities response:

▶ show

In case of encode processing expressions, besides MIME types WCPS (and rasql) can also accept GDAL format identifiers or other commonly-used format abbreviations like “CSV” for Comma-Separated-Values for instance.

5.10.1. Support for time in netCDF output

If the global metadata of a coverage contains "units" and "calendar" settings for the time axis, when encoding to netCDF rasdaman will adjust the coordinates of the time variable based on the origin specified in the "units" and "calendar" setting instead of the time CRS. Only standard and proleptic_gregorian calendars are currently supported. More details on these standard attributes of time variables can be found in the CF conventions docs.

For example, a coverage might have this metadata for the ansi time axis:

▶ show

The values of ansi variable in the output netCDF file will be based on the origin 2016-12-01 00:00:00 as specified by the <units> above, instead of 1600-12-31, the origin of the AnsiDate CRS associated with this axis.

5.11. rasdaman / petascope Geo Service Administration

The petascope conpoment, which geo services contact through its OGC APIs, uses rasdaman for storing the raster arrays; geo-related data parts (such as geo-referencing), as per coverage standard, are maintained by petascope itself.

Petascope is implemented as a war file of Java servlets. Internally, incoming requests requiring coverage evaluation are translated by petascope, with the help of the coverage metadata, into rasql queries executed by rasdaman as the central workhorse. Results returned from rasdaman are forwarded by petascope to the client.


rasdaman can maintain arrays not visible via petascope (such as non-geo objects like human brain images). Data need to be imported via Data Import, not rasql, for being visible as coverages.

For further internal documentation on petascope see Petascope Developer’s Documentation.

5.11.1. Service Startup and Shutdown

Depending of how java_server is configured in petascope.properties, starting the petascope Web application is different as follows:

  • If set to external, then managing the petascope Web application is done via the system Tomcat in which it is deployed, e.g.

    $ systemctl start tomcat
    $ systemctl stop tomcat
    $ systemctl restart tomcat
  • If set to embedded then petascope is managed along with rasdaman; see this section for more details.

5.11.2. Configuration

The rasdaman-geo frontend (petascope) can be configured via changing settings in /opt/rasdaman/etc/petascope.properties. For changes to take effect, system Tomcat (if deployment is external) or rasdaman (if deployment is embedded) needs to be restarted after editing this file. Database

  • spring.datasource.url set the connectivity string to the database administered by rasdaman-geo. Supported databases are PostgreSQL, H2, HSQLDB; for more details, see this section.

    • Default: jdbc:postgresql://localhost:5432/petascopedb

    • Need to change: YES when DMBS other than PostgreSQL is used

  • spring.datasource.username set the username for connecting to the above database.

    • Default: petauser

    • Need to change: YES when changed in the above database

  • spring.datasource.password set the password for the user specified by spring.datasource.username.

    • Default: randomly generated password

    • Need to change: YES when changed in the above database

  • spring.datasource.jdbc_jar_path absolute path to the JDBC jar file for connecting to the database configured in setting spring.datasource.url. If left empty, the default PostgreSQL JDBC driver will be used. To use a different DBMS (e.g. H2) download the corresponding JDBC driver, and set the path to it.

    • Default: empty

    • Need to change: YES when a DMBS other than PostgreSQL is used

  • spring.datasource.tomcat.initial-size set the initial size for JDBC connections in pool.

    • Default: 30 connections

    • Need to change: NO

  • spring.datasource.tomcat.max-active set the maximum number of active JDBC connections in pool.

    • Default: 70 connections

    • Need to change: NO

  • spring.datasource.tomcat.max-idle set the maximum number of idle JDBC connections in pool.

    • Default: 30 connections

    • Need to change: NO

  • metadata_url set the connectivity string to the database administered by rasdaman-geo. This setting is only used for database migration from one DBMS to another (e.g. PostgreSQL to H2) with migrate_petascopedb.sh; in this case metadata_url is used to connect to the source database, while spring.datasource.url is used to connect to the target database.

    • Default: jdbc:postgresql://localhost:5432/petascopedb

    • Need to change: YES when migrating from a DMBS different from PostgreSQL

  • metadata_user set the username for the above database

    • Default: petauser

    • Need to change: YES when different in the above database

  • metadata_pass set the password for the user specified by metadata_user

    • Default: petapasswd

    • Need to change: YES when different in the above database

  • metadata_jdbc_jar_path absolute path to the JDBC jar file for connecting to the database configured in setting metadata_url. If left empty, the default PostgreSQL JDBC driver will be used. To use a different DBMS (e.g. H2) download the corresponding JDBC driver, and set the path to it.

    • Default: empty

    • Need to change: YES when a DMBS other than PostgreSQL is used General

  • server.contextPath when rasdaman-geo is running in embedded mode (setting java_server), this setting allows to control the prefix in the deployed web application URL, e.g. the /rasdaman in http://localhost:8080/rasdaman/ows.

    • Default: /rasdaman

    • Need to change: NO

  • secore_urls set SECORE endpoints to be used by rasdaman-geo. Multiple endpoints for fail-safety can be specified as a comma-separated list, attempted in order as listed. By default, internal indicates that rasdaman-geo should use its own SECORE, which is more efficient as it avoids external HTTP requests.

    • Default: internal

    • Need to change: NO

  • crs_domain set the domain to be used for CRS URLs in results of WCS GetCapabilities / DescribeCoverage / GetCoverage requests.

    • Default: https://opengis.net/def

    • Need to change: NO

  • xml_validation if set to true, WCS POST/SOAP XML requests will be validated against OGC WCS 2.0.1 schema definitions; when starting Petascope it will take around 1-2 minutes to load the schemas from the OGC server.


    Passing the OGC CITE tests requires this parameter to be set to false.

    • Default: false

    • Need to change: NO

  • ogc_cite_output_optimization if true, rasdaman-geo will optimize responses in order to pass a couple of invalid OGC CITE test cases. Indentation of WCS GetCoverage and WCS DescribeCoverage results, for example, will be trimmed.

    • Default: false

    • Need to change: NO, except when executing OGC CITE tests

  • petascope_servlet_url set the service endpoint in <ows:HTTP> elements of the result of GetCapabilities. Change to your public service URL if rasdaman-geo runs behind a proxy; if not set then it will be automatically derived, usually to http://localhost:8080/rasdaman/ows.

    • Default: empty

    • Need to change: YES when rasdaman-geo runs behind a proxy.

  • max_wms_cache_size set the maximum amount of memory (in bytes) to use for caching WMS GetMap requests. This setting speeds up repeating WMS operaions over similar area/zoom level. It is recommended to consider increasing the parameter if the system has more RAM, but make sure to correspondingly update the -Xmx option for Tomcat as well. The cache evicts least recently inserted data when it reaches the maximum limit specified here.

    • Default: 100000000 (100 MB)

    • Need to change: NO

  • uploaded_files_dir_tmp set an absolute path to a server directory where files uploaded to rasdaman-geo by a request will be temporarily stored; the user running rasdaman-geo (either tomcat or rasdaman) should have write permissions on the specified directory.

    • Default: /tmp/rasdaman_petascope/upload

    • Need to change: NO

  • full_stacktraces log only stacktraces generated by rasdaman (false), or full stacktraces including all external libraries (true). It is recommended to keep this setting to false for shorter exception stacktraces in petascope.log.

    • Default: false

    • Need to change: NO

  • inspire_common_url set the URL to an external catalog service for the INSPIRE standard, to be provided by the user. If not set then it will be automatically derived from the petascope_servlet_url setting.

    • Default: empty

    • Need to change: NO Deployment

  • java_server specify how is rasdaman-geo deployed: embedded starts the Web application standalone with embedded Tomcat, listening on the server.port setting as configured below, while external indicates that rasdaman.war is deployed in the webapps dir of external Tomcat.

    It is recommended to set embedded, as there is no dependency on external Tomcat server, petascope.log can be found in the rasdaman log directory /opt/rasdaman/log, and start/stop of rasdaman-geo is in sync with starting/stopping the rasdaman service. Setting to external on the other hand can be preferred when there is already an existing Tomcat server running other Web applications.

    • Default: embedded

    • Need to change: NO, unless rasdaman-geo is deployed in external Tomcat

  • server.port set the port on which embedded rasdaman-geo (java_server=embedded above) will listen when rasdaman starts. This setting has no effect when java_server=external.

    • Default: 8080

    • Need to change: YES when port 8080 is occupied by another process, e.g. external Tomcat

  • static_html_dir_path absolute path to a directory containing static demo Web pages (html/css/javascript). If set, rasdaman-geo will serve the index.html in this directory at the /rasdaman endpoint, e.g. http://localhost:8080/rasdaman/. Changes of files in this directory do not require a rasdaman-geo restart. The system user running Tomcat (if java_server=external) or rasdaman (if java_server=embedded) must have read permission on this directory.

    • Default: empty

    • Need to change: YES when demo web pages required under radaman-geo’s endpoint Rasdaman

  • rasdaman_url set the connection URL to the rasdaman database. Normally rasdaman is installed on the same machine, so the bellow needs no changing (unless the default rasmgr port 7001 has changed).

    • Default: http://localhost:7001

    • Need to change: NO, unless changed in rasdaman (not recommended)

  • rasdaman_database set the name of the rasdaman database (configured in /opt/rasdaman/etc/rasmgr.conf).

    • Default: RASBASE

    • Need to change: NO, unless changed in rasdaman (not recommended)

  • rasdaman_user set the user for unauthenticated access to rasdaman.

    When authentication is disabled by setting authentication_type= in petascope.properties, this user is used to run SELECT rasql queries, so it is best to limit it to read-only access in rasdaman (e.g. by granting the R role to it).

    When authentication is enabled by setting authentication_type=basic_header, then this setting allows to control whether any unauthenticated access is enabled.

    If it is not set to anything with rasdaman_user=, then unauthenticated access is disabled and any request without credentials will be immediately denied.

    If it is set to some valid rasdaman user (e.g. rasdaman_user=rasguest), then unauthenticated requests which do not specify any credentials will be executed with this user and its corresponding password set with rasdaman_pass.

    • Default: rasguest

    • Need to change: YES when changed in rasdaman

  • rasdaman_pass set the password for the user set for rasdaman_user. It is recommended to change the default password for rasguest user in rasdaman and update the value here.

    • Default: rasguest

    • Need to change: YES when changed in rasdaman

  • rasdaman_admin_user when authentication is disabled with authentication_type=, this user will be used for executing update queries in rasdaman, if they come from an allowed IP address as configured in allow_write_requests_from. When authentication is enabled, these credentials are not used for executing user requests. However, in both cases they are also needed internally for various tasks.

    Generally, this user should be granted the RW rasdaman role.

    • Default: rasadmin

    • Need to change: YES when changed in rasdaman

  • rasdaman_admin_pass set the password for the user set for rasdaman_admin_user. It is recommended to change the default password for rasadmin user in rasdaman and update the value here.

    • Default: rasadmin

    • Need to change: YES when changed in rasdaman

  • rasdaman_retry_attempts set the number of re-connect attempts to a rasdaman server in case a connection fails.

    • Default: 5

    • Need to change: NO

  • rasdaman_retry_timeout set the wait time in seconds between re-connect attempts to a rasdaman server.

    • Default: 10 (seconds)

    • Need to change: NO

  • rasdaman_bin_path absolute path to the rasdaman executables directory.

    • Default: /opt/rasdaman/bin

    • Need to change: NO Security

  • authentication_type specifies how to authenticate requests. Valid values are:

    • basic_header requires requests to attach username:password encoded as a Base64 string to the HTTP header. If the rasdaman_user setting is not empty, however, requests without credentials will be automatically mapped to the user and password configured in rasdaman_user and rasdaman_pass; thereby unauthenticated access can be allowed, but limited to some restricted rasdaman user.

    • An empty string, i.e. authentication_type=, disables authentication. All requests will be forwarded to rasdaman with the credentials configured with rasdaman_user / rasdaman_pass for read queries, and rasdaman_admin_user / rasdaman_admin_pass for update queries.

    • Default if the setting does not exist, it is set to basic_header.

  • allow_write_requests_from configure from which IP addresses (as a comma-separated list) should the server accept write requests such as WCS-T InsertCoverage, UpdateCoverage and DeleteCoverage. will allow locally generated requests, usually needed to import data with wcst_import.sh; setting to empty will block all requests, while * will allow any IP address.


    This setting (i.e. the origin IP) is ignored when a request contains basic auth credentials for a valid rasdaman user with RW rights in the HTTP Authorization header.

    • Default:

    • Need to change: NO, unless more IP addresses should be allowed to execute write requests

  • security.require-ssl allow embedded petascope to work with HTTPS requests from its endpoint.

    • Default: false

    • Need to change: NO Logging

rasdaman-geo uses the log4j library version 1.2.17 provided by Spring Boot version 1.5.2 to log information/errors in a petascope.log file. See the log4j 1.2 document for more details.

  • Configuration for petascope logging; by default only level INFO or higher is logged to a file. The valid logging levels are TRACE, DEBUG, INFO, WARN, ERROR and FATAL.

    log4j.rootLogger=INFO, rollingFile
  • Configuration for reducing logs from external libraries: Spring, Hibernate, Liquibase, GRPC and Netty.

  • Configure file logging. The paths for file logging specified below should be write-accessible by the system user running Tomcat. If running embedded Tomcat, then the files should be write accessible by the system user running rasdaman, which is normally rasdaman.

    log4j.appender.rollingFile.layout.ConversionPattern=%6p [%d{yyyy-MM-dd HH:mm:ss}] %c{1}@%L: %m%n
  • Select one strategy for rolling files and comment out the other. Default is rolling files by time interval.

    # 1. Rolling files by maximum size and index
    # 2. Rolling files by time interval (e.g. once a day, or once a month)

Logging level for rasj is configured via the optional setting rasj_logging_level. The valid values for logging are ERROR, WARN, DEBUG, and TRACE. By default the logging level is WARN if this setting is not set in the configuration file.

5.11.3. Security

By default only local IP addresses are allowed to make write requests to petascope (e.g. InsertCoverage and UpdateCoverage when importing data, or DeleteCoverage, etc). This is configured through the allow_write_requests_from setting in petascope.properties.

Any write requests from a non-listed IP address will be blocked. However, if one has a rasdaman user credentials with RW rights (see user rights), then one can send write requests with these credentials via basic authentication header. This authentication mechanism is used by the WSClient for example when logged in with the petascope admin credentials, to enable deleting coverages, updating metadata, styles, etc.


Since v10+, the petascope admin user configured in petascope.properties by settings petascope_admin_user and petascope_admin_pass has no effect. One must use credentials of a rasdaman user with RW rights to perform a request with the basic header authentication method.

5.11.4. Meta Database Connectivity

Non-array data of coverages (here loosely called metadata) are stored in another database, separate from the rasdaman database. This backend is configured in petascope.properties.

As a first action it is highly recommended to substitute {db-username} and {db-password} by some safe settings; keeping obvious values constitutes a major security risk.

Note that the choice is exclusive: only one such database can be used at any time. Changing to another database system requires a database migration which is entirely the responsibility of the service operator and involves substantially more effort than just changing these entries; generally, it is strongly discouraged to change the meta database backend.

If necessary, add the path to the JDBC jar driver to petascope.properties using metadata_jdbc_jar_path and spring.datasource.jdbc_jar_path.

Several different systems are supported as metadata backends. Below is a list of petascope.properties settings for different systems that have been tested successfully with rasdaman. Postgresql (default)

The following configuration in petascope.properties enables PostgreSQL as metadata backend:

▶ show HSQLDB

The following configuration in petascope.properties enables HSQLDB as metadata backend:

▶ show H2

The following configuration in petascope.properties enables H2 as metadata backend:

▶ show

5.11.5. petascope Standalone Deployment

The petascope Web application can be deployed through any suitable servlet container, or (recommended) can be operated standalone using its built-in embedded container. The embedded variant is activated through setting java_server=embedded in $RMANHOME/etc/petascope.properties.

To configure embedded mode, the following options will need to be checked and adjusted:

  • petascope.properties

    # a path writable by the rasdaman user
    # or
  • secore.properties

    # paths writable by the rasdaman user

In the standalone mode petascope can be started individually using the central startup/shutdown scripts of rasdaman:

$ sudo -u rasdaman start_rasdaman.sh --service petascope
$ sudo -u rasdaman stop_rasdaman.sh --service petascope

The Web application can be even be started from the command line:

$ java -jar rasdaman.war [ --petascope.confDir={path-to-etc-dir} ]

The port required by the embedded tomcat will be fetched from the server.port setting in petascope.properties. Assuming the port is set to 8080, petascope can be accessed via URL http://localhost:8080/rasdaman/ows.

5.11.6. Serving Static Content

Serving external static content (such as HTML, CSS, and Javascript) residing outside rasdaman.war through petascope can be enabled with the following setting in petascope.properties:


with an absolute path to a directory readable by the user running petascope. The directory must contain an index.html, which will be served as the root, ie: at URL http://localhost:8080/rasdaman/.

5.11.7. Logging

Configuration file petascope.properties also defines logging. The log level can be adjusted in verbosity, log file path can be set, etc. Tomcat restart is required for new settings to become effective.

The user running Tomcat (tomcat or so) must have write permissions to the petascope.log file specified if java_server=external; usually the file should be placed in the Tomcat log directory in this case, e.g. /var/log/tomcat/petascope.log.

Otherwise, if java_server=embedded, then the user running rasdaman must have write permissions to the specified log file; usually the file would be placed in the rasdaman log directory in this case, e.g. /opt/rasdaman/log/petascope.log.

5.12. Geo Service Standards Compliance

rasdaman community is OGC WCS reference implementation and supports the following conformance classes:

  • OGC CIS:

  • CIS 1.0:

  • Class GridCoverage

  • Class RectifiedGridCoverage

  • Class ReferenceableGridCoverage

  • Class gml-coverage

  • Class multipart-coverage

  • CIS 1.1:

  • Class grid-regular

  • Class grid-irregular

  • Class gml-coverage

  • Class json-coverage

  • Class other-format-coverage


  • WCS 2.0:

  • WCS Core

  • WCS Range Subsetting

  • WCS Processing (supporting WCPS 1.0)

  • WCS Transaction


  • WCS Scaling

  • WCS Interpolation

  • WMS 1.3.0:

    • all raster functionality, including SLD ColorMap styling


With WCS 2.1, petascope provides an additional proprietary parameter to request CIS 1.0 coverages to be returned as CIS 1.1 coverages. This is specified by adding parameter outputType=GeneralGridCoverage.