Displaying 1 to 20 from 42 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 - GDAL is an open source X/MIT licensed translator library for raster and vector geospatial data formats

  •    C++

GDAL is an open source X/MIT licensed translator library for raster and vector geospatial data formats.

dom-to-image - Generates an image from a DOM node using HTML5 canvas

  •    Javascript

dom-to-image is a library which can turn arbitrary DOM node into a vector (SVG) or raster (PNG or JPEG) image, written in JavaScript. It's based on domvas by Paul Bakaus and has been completely rewritten, with some bugs fixed and some new features (like web font and image support) added. Include either src/dom-to-image.js or dist/dom-to-image.min.js in your page and it will make the domtoimage variable available in the global scope.

grass - GRASS GIS - free and open source Geographic Information System (GIS)

  •    C

GRASS GIS (https://grass.osgeo.org/) is a Geographic Information System used for geospatial data management and analysis, image processing, graphics/map production, spatial modeling, and visualization. In general: you don't really need write access as you can simply open a pull request to contribute to GRASS GIS. See CONTRIBUTING file for more details.


  •    DotNet

A Photoshop-like raster-based image editor, which is built on .NET/Mono to try to achieve cross-platform capability.

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.

earthpy - A package built to support working with spatial data using open source python

  •    Python

EarthPy makes it easier to plot and manipulate spatial data in Python. EarthPy's design was inspired by the raster and sp package functionality available to R users.

svg-to-image - convert SVG text to a Image that can be drawn in canvas

  •    Javascript

Converts a string of SVG into an HTMLImageElement using Blob and URL.createObjectURL. Falls back to encodeURIComponent for unsupported browsers, such as Safari 8.0.A common use case for this is rendering SVG to a 2D or WebGL canvas.

lerc - Limited Error Raster Compression

  •    C++

LERC is an open-source image or raster format which supports rapid encoding and decoding for any pixel type (not just RGB or Byte). Users set the maximum compression error per pixel while encoding, so the precision of the original input image is preserved (within user defined error bounds). This repository contains both a C++ library for encoding/decoding images and JavaScript, C#, and Python decoders.

mdcs-py - MDCS is an acronym for Mosaic Dataset Configuration Script and is the entry point to a collection of Python classes/libraries that could be consumed by a Python client application to complete a given workflow for creating a mosaic dataset, populating it with data, and setting all required/desired parameters

  •    Python

The Mosaic Dataset Configuration Script (MDCS) is a Python script that reads parameters stored in an xml file in order to create, configure, and populate a mosaic dataset. If you want to try out MDCS, review the documentation included in the repo for instructions, and download the suggested sample data from ArcGIS Online.

OptimizeRasters - OptimizeRasters is a set of tools for converting raster data to optimized Tiled TIF or MRF files, moving data to cloud storage, and creating Raster Proxies

  •    HTML

OptimizeRasters is a set of tools for accomplishing three tasks: converting raster data to optimized Tiled TIF or MRF files, moving data to cloud storage, and creating Raster Proxies. The result is more efficient, scalable, and elastic data access with a lower storage cost. OptimizeRasters converts a variety of non-optimized raster formats into optimized Tiled TIF or MRF formats. File conversion speeds up read performance in three ways. First, it improves the data structure, which makes data access and transfer (especially from cloud storage) more efficient. Second, it generates pyramids, which provides faster access to data at smaller scales. Third, it offers optional compression, which further reduces the amount of data stored and transmitted.

raster-functions - A curated set of lightweight but powerful tools for on-the-fly image processing and raster analysis in ArcGIS

  •    Python

This repository houses modern image processing and analytic tools called raster functions. Raster functions are lightweight and process only the pixels visible on your screen, in memory, without creating intermediate files. They are powerful because you can chain them together and apply them on huge rasters and mosaics on the fly. In this repository, you will find useful function chains (*.rft.xml) created by the Esri community. You can also create custom raster functions in Python that work seamlessly with the several dozen functions that ship with ArcGIS.

raster-tiles-compactcache - Compact Cache V2 is used by ArcGIS to store raster tiles

  •    Python

The Compact Cache V2 is the current file format used by ArcGIS to store raster tiles. The Compact Cache V2 stores multiple tiles in a single file called a bundle. The bundle file structure is very simple and optimized for quick access, the result being improved performance over other alternative formats. This repository contains documentation, a sample cache and a Python 2.x code example of how to build Compact Cache V2 bundles from individual image tiles.

WAB-Image-Services-Widgets - Web AppBuilder widgets for Image Services (WABIS)

  •    Javascript

Web AppBuilder for Image Services (WABIS) is a set of custom widgets to be used in Web AppBuilder that are designed to work with image services. Find a bug or want to request a new feature? Please let us know by submitting an issue.

weighted-raster-overlay-service-toolbox - Tools to help you setup a mosaic dataset to support fast, web-based suitability analysis

  •    Python

Tools to create and configure raster data for web-based weighted overlay to support suitability modeling. This python toolbox helps you create and configure a mosaic dataset for use in a web-based weighted overlay analysis service. You can use these services from web-based clients like GeoPlanner for ArcGIS and Web AppBuilder for ArcGIS to help find the best place or identify risks in an area.

Leaflet.CanvasLayer.Field - Load and style Raster files in Leaflet (geotiff & asciigrid)

  •    Javascript

A plugin for LeafletJS that adds layers to visualize fields (aka Rasters) from ASCIIGrid or GeoTIFF files (EPSG:4326). This plugin extends L.CanvasLayer Leaflet Plugin by Stanislav Sumbera and uses geotiff.js by Fabian Schindler. For the 'arrow' renderer, it includes a modified portion of leaflet-geotiff by Stuart Matthews.

unmixing - Interactive tools for spectral mixture analysis of multispectral raster data

  •    Python

Because this is a scientific library, there are complex dependencies that may be difficult to install. For GNU/Linux systems, particularly Ubuntu, look at install.sh for a guide on installing the system dependencies required for the Python dependencies. Many of the core packages, particularly NumPy and SciPy, have wide adoption and use. They also take a lot of time and clock cycles to compile into a virtual environment. Consequently, it is recommended that these libraries be installed globally (system-wide).

gdal2tiles-leaflet - Generate raster image tiles for use with leaflet.

  •    Python

Generate raster image tiles for use with leaflet. Example in action.

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