List of Projects



GeoBench provides a framework for benchmarking the performance of geospatial databases handling big data ingest and query tasks. The framework will include a documented methodology for performing experiments as well as a configurable tool for executing experiments which yield performance metrics. Documentation for deploying and tuning a comparable cloud testing environment is also a component of the project. Experiments are designed to be reproducible, and results will be openly shared.

Geoff (Geo Fast Forward)

As we know, 80% of any kind of data is said to have some geospatial relevance. There are many Eclipse RCP applications connected to data sources (RDBMS, EMF models, Files, etc.) of valuable information that need to be explored and visualized geographically. Unfortunately, many users and/or developers in their respective business domains are not familiar with the rather complex geospatial topics. But, they are the experts of those domains. The problem is how to make them get their feet wet and start exploring their data sources from a geospatial point of view.


LocationTech GeoGig is a Distributed Version Control System (DVCS) specially designed to handle geospatial data efficiently. It takes inspiration from the source code versioning system Git, but has an approach suited to the spatial data it manages. GeoGig efficiently handles very large binary data, divided up into features with the opportunity to optimise spatial operations using a spatial index. This is in contrast to Git which handles large text data, divided up into lines.


GeoJinni (formerly known as SpatialHadoop) is a comprehensive extension to Hadoop that allows efficient processing of spatial data. It injects spatial awareness in the different layers and components of Hadoop to make it more suitable and more efficient to store and process bug spatial data. More specifically, it modifies the storage layer, MapReduce layer and adds a new operations layer.


GeoPeril merges complementary external and in-house cloud-based services into one platform for automated background GPU computation, for web-mapping of hazard specific geospatial data, and for serving relevant functionality to handle, share, and communicate threat specific information in a collaborative and distributed environment.


GeoScript adds spatial capabilities to dynamic scripting languages. Backed by the GeoTools library, GeoScript provides a collection of modules for geometry handling, spatial data access, and vector feature rendering. Current implementations exist in Groovy, JavaScript, Python, and Scala.


The core GeoTrellis framework provides an ability to process large and small data sets with low latency by distributing the computation across multiple threads, cores, CPUs and machines.  The software includes the ability to rapidly process and distribute processing of raster data as well as data import and conversion tools for the ARG data structure.

JTS Topology Suite

The JTS Topology Suite (JTS) is an open source Java software library that provides an object model for planar geometry together with a set of fundamental geometric functions. JTS conforms to the Simple Features Specification for SQL published by the Open GIS Consortium.  JTS is designed to be used as a core component of vector-based geomatics software such as geographical information systems. It can also be used as a general-purpose library providing algorithms in computational geometry.


libspatialindex is a "Gang of Four"-inspired C/C++ library for implementation of spatial indexes. It contains a number of features that make it a valuable key component of many spatial software stacks, but its stand out feature is that of providing a generic interface to which specific index implementations can be adapted. Some of its current major features include:

LocationTech GeoMesa

LocationTech GeoMesa is an Apache licensed open source suite of tools that enables large-scale geospatial analytics on cloud and distributed computing systems, letting you manage and analyze the huge spatio-temporal datasets that IoT, social media, tracking, and mobile phone applications seek to take advantage of today.

Mobile Map Technology

Mobile Map Technology (MMT) is a SDK designed for building multi-platform high-performance native mobile applications using the most appropriate technology for the target platform(s).

The framework core is built using C++ and is translated to Java and JavaScript to work in all platforms.

The main capabilities of MMT are:


Proj4J is a Java port of the widely used Proj.4 library for coordinate reprojection.  While Proj.4 is widely used and battle-tested, some projects benefit from a pure-Java implementation of the same functionality.  For example, in Spark applications it is cumbersome to require a native library, but a Java dependency can be included in a fat jar with the task code for workers.

Raster Processing Engine

Create a raster processing engine:
  • Modern Java API using Java 8 constructs, literate programing style, as appropriate
  • Pure Java implementation
  • Ability to stage larger rasters as tiles in memory and process tiles in parallel
  • Clear image processing operations, allowing installations to use native libs to accelerate processing if available
This is a new project providing a solution free of any encumbrance.


The SFCurve library is a Scala library for the creation, transformation, and querying of space-filling curves (


Spatial4j is a general purpose spatial / geospatial ASL licensed open-source Java library. Its core capabilities are 3-fold: to provide common geospatially-aware shapes, to provide distance calculations and other math, and to read and write the shapes to strings.



The LocationTech Technology (LTT) project fosters, promotes, and houses location aware efforts in the LocationTech community. These efforts strive towards the common goal of re-usable technology components that are location aware. These components are implemented in different languages and operate across a wide variety of computing environments.

User-friendly Desktop Internet GIS (uDig)

uDig is an open source desktop application framework, built with Eclipse Rich Client (RCP) technology. uDig provides a complete Java solution for desktop GIS data access, editing, and viewing.