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...Quick Start: git clone git://git.code.sf.net/p/mossco/setups mossco-setups git clone git://git.code.sf.net/p/mossco/code mossco-code cd mossco-code cat QuickStart.md or read online https://sf.net/p/mossco/code/ci/master/tree/QuickStart.md Beware: this is alpha software, expect trouble! ------------------------- Better, read the full documentation online http://www.mossco.de/doc or make it yourself make doc acroread doc/mossco_documentation.pdf ---------------------- Why MOSSCO? MOSSCO, the "Modular System for Shelves and Coasts" is a framework for coupling processes or domains that are originally developed in standalone numerical models. The software MOSSCO implements this infrastructure in the form of a library of components and couplers, and of example coupled application.

A python-based system to diagnosis and make weather maps (wxmap) of numerical weather prediction models using the Grid Analysis and Display System (GrADS) from opengrads.org

33 starts out to gather topographic information to compare different locations on key measures like Height Above Sea Level, Geographical Latitude, Aspect (ST_Aspect), Slope (ST_Slope), Terrain Ruggedness Index (TRI, ST_TRI/ST_Roughness), Topographic Position Index (TPI, ST_TPI), or Hill Shade (ST_HillShade). Ultimately intended to make a comparing decision on suitability for agriculture. We will see how far we get or if we surpass it even, e.g with weather data and more. Why 33 as the name? Even though the answers we could get from the project might be very important, they won't be "The Answer to the Ultimate Question of Life, the Universe, and Everything", so not quite 42. ...

*.xml files are uploaded to SAGA GIS toolchains 'Files' from where they can be downloaded: https://sourceforge.net/projects/saga-gis-rhotoolchains/files/ SAGA-GIS-toolchain_Burned_area.xml ___is presented in GitHub: https://github.com/RhoSpatial/Saga-gis-toolchain-for-burned-area-mapping- VIIRS_snow_tool_FINAL7.xml ___is a toolchain for snow cover retrival from VIIRS instrument imagery (NASA), input is study area cloud free VNP09GA product and DEM in GQ(nom 250m) resolution, it was developed to make high accurate snow cover analytics on Atlas mountains(Morocco). It was tested in 2017/18 snow season(output grids are available: mih.zemva@gmail.com). It is fairly complicated but not as much as toolchain for MODIS(not uploaded) with MOD09.. products input . * in line 139 polygon *.shp must be linked from drive; it's an additional retrieval of index values to monitor waterbodies and does not relate to snow cover analytics

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.

This software computes synthesis of spherical harmonics models on sparse coordinates or grids (provided in a geodetic or geocentric reference system). It exploits basic parallelism using openmp directives. A solution with MPI has not be taken into account since it cannot be so easily manageble by final users.

The project aims to make publishing of wildlife survey data easier using PHP Mapscript. By uploading survey or sightings data the user will be presented with a generalization map based on the Quarter Degree Grid Cell system.

SwarmNet is a framework for distributed computing applications. Its goal is to make the creation of applications that compute complex calculations in distributed fashion as simple as possible.