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Section 4.1 : Requirements


4.1.1 Requirements for Offering a GeoTiff dataset

4.1.2 Requirements for TRMM Precipitation Data with GMU CSISS’s WCS

4.1.3 Requirements for Multidimensonal data with Rasdaman

4.1.3 Requirements for WCS 2.0 and EO-WCS with MapServer and EOxServer (EOX)

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4.1.1 Requirements for Offering a GeoTiff dataset

Geoserver latest versions allow to upload GeoTIFF raster data directly by indicating to create a Raster Data Source for GeoTIFF data. In the case of offering a GeoTIFF mosaic, Geoserver has an option of creating a Raster Data Source “ImageMosaic”. When Geoserver is given all GeoTIFFs image to be used, it automatically create the needed files to read the mosaic: Index.shp, configuration.properties and a .proj file.
Be aware that as soon as your Geotiffs gets beyond some tens of megabytes you’ll want to add the following capabilities:

•inner tiling
•overviews


Inner tiling sets up the image layout so that it’s organized in tiles instead of simple stripes (rows). This allows much quicker access to a certain area of the geotiff, and the Geoserver readers will leverage this by accessing only the tiles needed to render the current display area. The following sample command instructs gdal_translate to create a tiled geotiff.


gdal_translate -of GTiff -projwin -180 90 -50 -10 -co "TILED=YES" bigDataSet.ecw myTiff.tiff


Overviews are downsampled version of the same image, that is, a zoomed out version, which is usually much smaller. When Geoserver needs to render the Geotiff, it’ll look for the most appropriate overview as a starting point, thus reading and converting way less data. Overviews can be added using gdaladdo, or the the OverviewsEmbedded command included in Geotools. Here is a sample of using gdaladdo to add overviews that are downsampled 2, 4, 8 and 16 times compared to the original:


gdaladdo -r average mytiff.tif 2 4 8 16


As a final note, Geotiff supports various kinds of compression, but it is not recommended to use it. Whilst it allows for much smaller files, the decompression process is expensive and will be performed on each data access, significantly slowing down rendering. In our experience, the decompression time is higher than the pure disk data reading.

4.1.2 Requirements for TRMM Precipitation Data with GMU CSISS’s WCS

GMU WCS is based on multiple open source software including GDAL, PROJ.4 library. Since TRRM data is encoded to HDF format, the HDF library is also required to implement WCS. Please make sure the HDF library is installed successfully before compiling GDAL.
In order to deploy WCS instance to a server, since GMU WCS is a cgi-bin program, Apache server is required to run the service instance. TRMM data will be pre-downloaded from NASA and archived to the same server that WCS is deployed.

4.1.3 Requirements for Multidimensonal data with Rasdaman

A preconfectioned CentOS Linux VM – with rasdaman, MapServer, and further tools preinstalled – is about to be provided on EarthServer (www.earth¬server.eu) for free download.
Alternatively, rasdaman can be downloaded and installed via www.rasdaman.org, where also detailed instructions, FAQs, etc. can be found. Additionally, there is mailing list support. The process consists of downloading and installing rasdaman and its prerequisites, launching PostgresQL and rasdaman, and deploying the petascope servlet in Tomcat or similar.

4.1.4 Requirements for WCS 2.0 and EO-WCS with MapServer and EOxServer (EOX)

As the name implies this use case focuses on the new version of WCS 2.0 and its application profile for Earth Observation data – EO-WCS (see section 2.2.3.4 above). We describe the usage of a Free and Open Source Software (FOSS) stack including MapServer and EOxServer to provide EO data via the mentioned OGC services.
As EOxServer is based on Python, MapServer, GDAL/OGR, and Django these software components need to be installed first. The base configuration of EOxServer consists of the generation of an EOxServer instance and registering it in a web server.

 

 

 

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