Professional geospatial services
Key accomplishments in GDAL/OGR
Design and implementation of many features in the GDAL/OGR core:
- Unification of raster and vector driver models, per RFC 46, for GDAL 2.0.
- Use of the OGR SQL SQLite dialect.
- Support for multiple geometry fields per vector layer, per RFC 41.
- Support for curve geometries, per RFC 49.
- Support for sub-types of attributes of vector features, per RFC 50.
- Support for 64 bit integers for attributes and identifiers of vector features, per RFC 31.
- Support dataset transactions, per RFC 54.
- Addition of millisecond accuracy for dates, per RFC 56.
- Multithreading in the computational part of the image warping.
- GDAL_API_PROXY mechanism to off-load the execution of a driver in another process.
- Mechanism to expose GDAL datasets and raster bands as virtual memory mappings, per RFC 45.
- Support for several resampling algorithms in RasterIO() API, per RFC 51.
- Support for rasters of very large dimensions, per RFC 26
- Improvements in overview resampling and use of overviews in warping.
- Upgrade of the JP2OpenJPEG (JPEG 2000) driver to comply with Inspire recommandations for orthoimagery, and GMLJP2 v2 standard support.
Reverse engineering of ESRI FileGDB format
Writing of new GDAL (Raster) Drivers :
Significant enhancements to the following GDAL drivers :
Writing of new OGR (Vector) Drivers :
Significant enhancements to the following OGR drivers :
Maintainer of the Python and
Java bindings, and the documentation of the latter one.
Code review and integration of the following drivers:
Key accomplishments in MapServer
- Implementation of tile indexes of raster with different projections (RFC 100)
- Implementation of OGC WFS 2.0 protocol (RFC 105)
- Implementation of 2.5D geometry support for PostGIS and OGR input and WFS/GML output.
Key accomplishments in QGIS
Key accomplishments in OpenJPEG library (JPEG2000 library)
an executable that can help handling securely data from untrusted sources.