Displaying 1 to 20 from 21 results

earthenterprise - Google Earth Enterprise - Open Source

  •    Javascript

Earth Enterprise is the open source release of Google Earth Enterprise, a geospatial application which provides the ability to build and host custom 3D globes and 2D maps. Earth Enterprise does not provide a private version of Google imagery that's currently available in Google Maps or Earth.Refer to the wiki for instructions on building from source on one of these platforms.

rasterio - Rasterio reads and writes geospatial raster datasets

  •    Python

Rasterio reads and writes geospatial raster data.Geographic information systems use GeoTIFF and other formats to organize and store gridded, or raster, datasets. Rasterio reads and writes these formats and provides a Python API based on N-D arrays.



GDAL SSIS is a collection of geospatial components for SQL Server Integration Services (SSIS) that leverages GDAL to support a large number of GIS data formats.

node-gdal - Node.js bindings for GDAL (Geospatial Data Abstraction Library)

  •    C++

Read and write raster and vector geospatial datasets straight from Node.js with this native GDAL binding. GDAL 2.0.1 (GEOS 3.4.2, Proj.4 4.8.0) comes bundled, so node-gdal will work straight out of the box. To get started, browse the API Documentation or examples. This binding is a collaboration between Natural Atlas and Mapbox. Its contributors are Brandon Reavis, Brian Reavis, Dane Springmeyer, Zac McCormick, and others.

heroku-geo-buildpack - Geo libraries for Heroku

  •    Shell

This is a Heroku buildpack that vendors main geo/gis libraries like geos, proj and gdal. You will use this buildpack with other major buildpack such as Ruby buildpack.

node-ogr - OGR bindings for node

  •    C++

OGR bindings for node. As of right now you can only install it locally since it's not on npm yet.

gdal-docker - A Dockerfile compiling the latest GDAL github checkout with a broad range of drivers

  •    Shell

NB: As of GDAL version 1.11.2 the image has been renamed from homme/gdal to geodata/gdal. This is an Ubuntu derived image containing the Geospatial Data Abstraction Library (GDAL) compiled with a broad range of drivers. The build process is based on that defined in the GDAL TravisCI tests.

DicoGIS - Automatic creation of a dictionary of geographic data

  •    Python

Automatize the creation of a dictionnary of geographic data in a folders structure. The output dictionary is an Excel file (.xls). Available in 3 languages (English, French and Spanish) but you can add your own translations (in locale folder).

MODIStsp - An "R" package for automatic download and preprocessing of MODIS Land Products Time Series

  •    R

MODIStsp is a “R” package devoted to automatizing the creation of time series of rasters derived from MODIS Land Products data. MODIStsp allows to perform several preprocessing steps (e.g., download, mosaicing, reprojection and resize) on MODIS data available within a given time period. Users have the ability to select which specific layers of the original MODIS HDF files they want to process. They also can select which additional Quality Indicators should be extracted from the aggregated MODIS Quality Assurance layers and, in the case of Surface Reflectance products, which Spectral Indexes should be computed from the original reflectance bands. For each output layer, outputs are saved as single-band raster filescorresponding to each available acquisition date. Virtual files allowing access to the entire time series as a single file can be also created. All processing parameters can be easily selected with a user-friendly GUI, although non-interactive execution exploiting a previously created Options File is possible. Stand-alone execution outside an “R” environment is also possible, allowing to use scheduled execution of MODIStsp to automatically update time series related to a MODIS product and extent whenever a new image is available. L. Busetto, L. Ranghetti (2016) MODIStsp: An R package for automatic preprocessing of MODIS Land Products time series, Computers & Geosciences, Volume 97, Pages 40-48, ISSN 0098-3004, http://dx.doi.org/10.1016/j.cageo.2016.08.020, URL: https://github.com/ropensci/MODIStsp.

gdal_hillshade_tutorial - Tutorial for rendering hillshades with GDAL

  •    Javascript

Participants will learn how to work with Digital Elevation Model data and use GDAL to generate a Shaded Relief / Hillshade for the Kings Canyon National Park area, in the southern Sierra Nevada mountain range, California. The commands in this tutorial are meant to be run in the Bash shell on Mac OS X or a Linux OS but these processes can also be accomplished using QGIS. Ths tutorial assumes you have GDAL installed and that it is accessible from a Command Line Interface such as the Terminal App. Some familiarity with the Unix CLI is beneficial but not required.

shell_scripts - Bash shell scripts for batch GeoProcessing using GDAL & OGR2OGR

  •    Shell

Bash shell scripts primarily for batch geoprocessing spatial data using the OGR2OGR utility, a part of the Geospatial Data Abstract Library: GDAL. These scripts are useful when open-source GIS applications such as QGIS do not allow for batch processing directories of vector spatial data. Additionally, invoking the scripts from a shell (such as the Terminal.App in Mac OSX) allows for heavy data processing to be run in the background while freeing up a GIS software to be used simultaneously for visualization and analysis.

dem-playground - Downloading, Processing and Visualization of Digital Elevation Model (DEM) Data

  •    Javascript

I favour Postgres as a middleman, for faster and easier queries (but that is just my opinion). For those who don't want to rely on Postgres i will start with a process that only relies on GDAL. Use one of the processes described below to download either the OpenDEM shapefiles or the CGIAR geotiffs.

ogr2ogr - A ogr2ogr wrapper full of win

  •    Javascript

ogr2ogr requires the command line tool ogr2ogr - gdal install page. It is recommended to use the latest version. See /examples for usage examples and /test/api.js.

gdal - Rust bindings for GDAL

  •    Rust

GDAL bindings for Rust.

buzzard - Geofiles management can be great. No joke! 🗺

  •    Python

In a nutshell, buzzard reads and writes geospatial raster and vector data. This example illustrates visualization of a raster based on polygons.

geokit - Geospatial toolkit for Python

  •    Python

GeoKit communicates directly with functions and objects within the Geospatial Data Abstraction Library (GDAL) and exposes them in such a way that is particularly useful for programmatic general purpose geospatial analyses. It gives low overhead control of fundamental operations; such as reading, writing, and mutating geospatial data sets, manipulating and translating geometries, warping and resampling raster data, and much more. Via the RegionMask object, GeoKit even allows for seamless integration of information expressed across multiple geospatial datasets in many formats and reference systems into the context of a single region. GeoKit is not intended to replace the GDAL library, as only very small subset of GDAL's capabilities are exposed. Nor is it intended to compete with other libraries with similar functionalities. Instead GeoKit evolved in an ad hoc manner in order to realize the Geospatial Land Eligibility for Energy Systems (GLAES) model which is intended for rapid land eligibility analyses of renewable energy systems and is also available on GitHub. Nevertheless, GeoKit quickly emerged as a general purpose GIS toolkit with capabilities far beyond computing land eligibility. Therefore, it is our pleasure to offer it to anyone who is interested in its use.

openfluid - OpenFLUID framework and applications

  •    C++

Further informations are available on the OpenFLUID site at www.openfluid-project.org. See also the LICENSE and AUTHORS files included in the sources.

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