Open Source Python Mapping Software

GPlates is a plate-tectonics program. Manipulate reconstructions of geological and paleo-geographic features through geological time. Interactively visualize vector, raster and volume data. PyGPlates is the GPlates Python library. Get fine-grained access to GPlates functionality in your Python scripts.

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

Platform providing the support for Wireless Sensor Networks in the domain of Natural Hazards as a Service. The objective of the WSN platform is monitoring the behaviour of rockfall barriers, rockfall netting, rock sheds and other protection systems

The purpose of this workshop is to share the tools created as an aid to our everyday work with students, enthusiasts and specialists interested in the development and use of new technologies including (but not limited to) geomatics, mapping, web mapping services (WMS), drafting, remote sensing, GIS and related occult sciences of Gaia. Check out the NBR (dn2nbr) and NDVI (dn2ndvi) calculating tools for GRASS GIS at the top menu!!!

PySOS, a python-based implementation of the OGC SOS standard. PySOS is a lightweight set of scripts that work in conjunction with a web server to serve data from a relational database.

Project created to develop customizations in OpenGeo, to contribute to the standardization of formats Brazilians. Tool-Kit aplication for system Geo Integrations, using java frameworks.

Geomorphometry Toolbox for AG is concerned with automated analysis of Digital Elevation Models with ESRI's software packages, mainly ArcInfo and ArcGIS

GeoSciPy is a set of C and Python functions that provide an API for all aspects of Geoscience and Remote Sensing Applications. Functions include reading/writing of many data formats, images, vectors, ..., and processing of images, vectors, ... including map projections, ... The library is written C, using HDF5 as the file format for storage of all remotely-sensed data and ancillary data, as well as processed data. The C functions assume a particular format for the HDF5 file contents, and provide functions for reading and writing data to such files. There is also a Python API that provides a procedural as well as an object-oriented interface to these functions. A Python GUI for interacting with such datasets is also part of the project. While there are other open-source GIS, and image-processing packages available, this one is designed to be comprehensive, work on 3 major platforms, user-extensible, fast, and able to handle huge datasets. Click the Blog tab for more info.

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.