##Origin
MrGeo was developed at the National Geospatial-Intelligence Agency (NGA) in collaboration with DigitalGlobe. The government has "unlimited rights" and is releasing this software to increase the impact of government investments by providing developers with the opportunity to take things in new directions. The software use, modification, and distribution rights are stipulated within the Apache 2.0 license.
###Pull Requests
All pull request contributions to this project will be released under the Apache 2.0 license.
Software source code previously released under an open source license and then modified by NGA staff is considered a "joint work" (see 17 USC 101); it is partially copyrighted, partially public domain, and as a whole is protected by the copyrights of the non-government authors and must be released according to the terms of the original open source license.
###MrGeo in Action See YouTube explainer
###MrGeo in the News NGA Press Release
MrGeo got a mention in an article on NGA Opensourcing from Reuters
###MrGeo Overview
MrGeo (MapReduce Geo) is a geospatial toolkit designed to provide raster-based geospatial capabilities that can be performed at scale. MrGeo is built upon the Hadoop ecosystem to leverage the storage and processing of hundreds of commodity computers. Functionally, MrGeo stores large raster datasets as a collection of individual tiles stored in Hadoop to enable large-scale data and analytic services. The co-location of data and analytics offers the advantage of minimizing the movement of data in favor of bringing the computation to the data; a more favorable compute method for Geospatial Big Data. This framework has enabled the servicing of terabyte scale raster databases and performed terrain analytics on databases exceeding hundreds of gigabytes in size.
See Wiki for detailed documentation
Unique features/solutions of MrGeo:
- Scalable storage and processing of raster data
- Application ready data: data is stored in MrGeo in a format that is ready for computation, eliminating several data pre-processing steps from production workflows.
- A suite of robust MapReduce analytics that that include algebraic math operations, focal operations(i.e. slope), and graph operations (cost distance)
- A third generation data storage model that
- Maintains data locality via spatial indexing.
- An abstraction layer between the MapReduce analytics and storage methods to enable a diverse set of cloud storage options such as HDFS, Accumulo, HBASE etc.
- A Map algebra interface that enables the development of custom algorithms in a simple scripting API
- A plugin architecture that facilitates a modular software development and deployment strategies
- Data and Analytic capabilities provisioned by OGC and REST service end points
Exemplar MrGeo Use Cases:
- Raster Storage and Provisioning: MrGeo has been used to store, index, tile, and pyramid multi-terabyte scale image databases. Once stored, this data is made available through simple Tiled Map Services (TMS) and or Web Mapping Services (WMS).
- Large Scale Batch Processing and Serving: MrGeo has been used to pre-compute global 1 ArcSecond (nominally 30 meters) elevation data (300+ GB) into derivative raster products : slope, aspect, relative elevation, terrain shaded relief (collectively terabytes in size)
- Global Computation of Cost Distance: Given all pub locations in OpenStreetMap, compute 2 hour drive times from each location. The full resolution is 1 ArcSecond (30 meters nominally)