In 2017, GIS is now moving in new and exciting directions. The industry has become more outward looking and more open to new opportunities than ever before. The current deluge of big-data (from IoT, social media, tracking, and other apps) requires spatially-aware big-data platforms which are capable of performing geospatial analytics on cloud and distributed computing systems.
While there are numerous commercial products on the market, this short article will give an overview of three powerful open-source standards-based systems which are turning often unassuming geospatialists into big data superheros!
GeoMesa is one such system which is enabling geospatialists to make more sense of information in a confusing world. The software is written in Scala and is based on Apache Hadoop (an open-source software framework used for distributed storage and processing of dataset of big data). GeoMesa uses the Apache Accumulo (a sorted, distributed key/value store based on the Google's Bigtable technology) as its backend and it performs geospatial analysis (on mainly vector datasets) using Apache Spark SQL.
GeoWave is a similar open-source system which is focused on the efficient storage and retrieval of geotemporal data using the Apache Accumulo store. The Java-based system was originally developed by the National Geospatial Agency (NGA) before being released in 2014 to the energetic and innovative open-source community. Since then GeoWave, which works on top of sorted key-value datastores and popular big data and distributed computing frameworks) has engaged with the Eclipse Foundation.
GeoTrellis is a raster-based data processing engine for high performance computing. Like GeoMesa, GeoTrellis is written in Scala and it is commonly used for climatology modelling and imagery processing and analysis at both web and cluster scales for powerful real time, interactive web applications. In terms of its background, the GeoTrellis project launched off the back of a US Department of Agriculture business innovation grant. It was subsequently refined while being applied to the development of a sustainable transit web application and an educational watershed modeling game.
The emergence of GeoMesa, GeoWave and GeoTrellis indicate that the open-source systems are keeping pace with commercial geospatial tools. Thanks to these flexible and extensible libraries, geospatialists have, in the chaotic world of Big Data, superpowers which will help to save the day!