Open Source Python Mapping Software

To use precompiled wheels: 1) go to releases (Files) and download tarball needed; 2) install it with command: python3 -m pip install /path/to/wheel.whl Or simply use URL in pip: python3 -m pip install https://sourceforge.net/projects/gdal-wheels-for-linux/files/GDAL-3.1.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl/download URL may be found under "View details" button (i) To use GDAL in C/C++ project you need to link gdal lib AND all libs located at dir GDAL.libs (usually this folder resides inside python site-packages) To compile your own wheels see information given at forefather project: https://github.com/youngpm/gdalmanylinux Usually this is done via command `make wheels` GDAL wheels for Windows are provided by Christoph Gohlke at https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal Built with PROJ (proj.db is included), GEOS, EXPAT. See Dockerfile.wheels for additional components.

GEOMS2 is a geostatistics and geosciences modeling software. Provides interface for grid (mesh), point, surface and data (non-spatial) objects. It has a 3D viewer and 2D plots using the well known Python engines Mayavi and Matplotlib. It has several functions to manipulate your data as well as provide univariate and multivariate analysis. NOTE: The software is still an early beta. Please tell us if you found a bug. Download datasets for students of Geostatistics 2017 (Petroleum Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Petroleum.zip/download Download datasets for students of Geostatistics 2017 (Geology and Mining Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Mining.zip/download Old: http://sourceforge.net/projects/geoms2/files/SETS_geoestatistica2_2015.7z/download https://sites.google.com/site/cmrpsoftware/downloads/Quarry_sets.7z?attredirects=0&d=1 http://sourceforge.net/projects/geoms2/files/Mining.7z/download

streamline the DSM process in ArcGIS/Numpy/GDAL/Python using Sampling, Statistical elaboration, Prediction to allow the application of extended statistical models generated by the CUBIST (TM) or JMP (TM) software to a set of auxiliary input parameters, thereby bypassing the need to i) manually calculate the equations using Raster calculator; ii) use a grid-to-point conversion process prior to applying the prediction model in the statistical software itself and then a point-to-grid conversion process.