GIS Software

Free and Open Source (FOSS)

FOSS GIS software offers powerful tools for geospatial data analysis and management without cost. Examples include QGIS, a widely-used desktop GIS application with extensive capabilities; GRASS GIS, which excels in spatial modeling and visualization; and GeoDa, a tool focused on spatial data analysis. Other options like gvSIG and uDig cater to specific user needs with user-friendly interfaces and flexibility.

Commercial

Commercial GIS software typically provides more advanced features and support. ArcGIS Desktop is a leading option, offering comprehensive tools for 2D and 3D data management, analysis, and visualization. Global Mapper is known for its affordability and broad data format support, while other commercial solutions cater to niche applications or specific industries.

Web Map Servers

Free and Open Source (FOSS)

Open-source web map servers enable the hosting and sharing of geospatial data online. GeoServer is a prominent example, allowing users to share data through various formats and protocols. MapServer and QGIS Server are also popular for publishing spatial data, while tools like OpenMapTiles offer customizable map hosting solutions.

Commercial

Commercial web map servers like ArcGIS Server provide robust, enterprise-level solutions for geospatial data hosting and analysis. These servers are often integrated with other enterprise GIS tools, offering comprehensive support and advanced functionalities for large-scale geospatial applications.

Cloud Services

Cloud services in GIS offer platforms for storing, managing, and analyzing spatial data online. Popular services include Mapbox, which allows users to design custom maps and visualize data, and ArcGIS Online, which provides access to a vast array of datasets and tools for spatial analysis. Other services like GIS Cloud and CartoDB focus on ease of use and accessibility for a wide range of users.

Spatial Databases

Spatial databases support the storage and querying of geospatial data. PostGIS, an extension of PostgreSQL, is one of the most advanced open-source spatial databases available, supporting complex spatial queries. SpatiaLite, based on SQLite, offers lightweight spatial capabilities, while GeoMesa is designed for distributed, large-scale spatial and temporal data storage.

Language-Based Geospatial Libraries

C++

C++ libraries offer powerful tools for geospatial data processing and analysis. GEOS is a geometry engine that mirrors the Java Topology Suite, providing essential tools for geometric operations. GDAL is a comprehensive library that translates raster and vector geospatial data formats, widely used across the industry. PDAL extends similar functionalities to point cloud data, while other libraries like tippecanoe and gdalcubes focus on building vector tilesets and managing Earth Observation data as multidimensional arrays.

Python

Python libraries provide flexible and user-friendly options for geospatial analysis and data manipulation. Shapely and GeoPandas are foundational tools for working with geometric objects and geographic data in Python. Rasterio and Rasterstats handle geospatial raster data, while libraries like Landlab and MovingPandas are designed for more specialized tasks, such as modeling Earth surface dynamics and analyzing movement data. Additional tools like Cartopy, Pyproj, and Matplotlib support cartographic transformations and visualization, while WhiteboxTools offers an advanced platform for geospatial data analysis with a simple installation process.

JavaScript

Map Display Libraries

These libraries enable interactive map visualizations on the web. Leaflet is a lightweight and mobile-friendly option, while Mapbox GL JS and OpenLayers offer more advanced capabilities for rendering and manipulating map data. Frameworks like ArcGIS API for JavaScript are tailored to specific platforms for building high-performing web applications.

3D Specialized

3D visualization libraries like three.js and CesiumJS make it easier to render complex 3D maps and globes in web browsers. These tools are essential for applications requiring detailed terrain models or interactive 3D environments.

Visual Data Analysis

Libraries like D3.js and Echarts enable the creation of dynamic data visualizations, including maps. Turf.js is specifically designed for geospatial analysis in the browser, while other tools like Polymaps and kepler.gl provide specialized functionality for geospatial data visualization and editing.