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Eugene Krevenets edited this page Jun 2, 2017 · 34 revisions

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Datasets in details

NonNASA Data

Machine Learning

NASA Space Apps Challenge 2017

Libs

package designed to make drawing maps for data analysis and visualisation as easy as possible.

extends the datatypes used by pandas to allow spatial operations on geometric types. Geometric operations are performed by shapely. Geopandas further depends on fiona for file access and descartes and matplotlib for plotting.

This Python package and extensions are a number of tools for programming and manipulating the GDAL_ Geospatial Data Abstraction Library. Actually, it is two libraries -- GDAL for manipulating geospatial raster data and OGR for manipulating geospatial vector data -- but we'll refer to the entire package as the GDAL library for the purposes of this document.

The GDAL project (primarily Even Rouault) maintains SWIG generated Python bindings for GDAL and OGR. Generally speaking the classes and methods mostly match those of the GDAL and OGR C++ classes. There is no Python specific reference documentation, but the GDAL API Tutorial_ includes Python examples.

a web based data mining tool for OpenStreetMap

It is based on the widely deployed GEOS (the engine of PostGIS) and JTS (from which GEOS is ported) libraries.

User stories

Useful information

  • A-Train - satellites fly in a some sequence, called A-Train. Six satellites currently fly in the A-Train: OCO-2, GCOM-W1, Aqua, CALIPSO, CloudSat, and Aura. On November 16, 2011, PARASOL was lowered to 9.5 km under the A-Train and on December 18, 2013 PARASOL ceased operation, fully exiting the A-Train. https://atrain.gsfc.nasa.gov/ A-Train

Other data challenges

Other