7 Best Python Geospatial Analysis Libraries

Here are the best open-source Python geospatial analysis libraries for your applications. You can use these for a wide range of functionality, from reading and writing data to performing complex geometric operations to visualizing and exploring data.

Specific open-source Python libraries provide advanced tools for performing complex geospatial analysis, such as coordinate reference systems, spatial projections, and raster data analysis. Whether you're working on a GIS project or want to visualize certain data on a map, these libraries are a great place to start. These data analysis libraries in Python make working with geospatial data easy and intuitive. These libraries offer a simple and powerful interface for working with various geospatial file formats, including shapefiles, GeoJSON, and more. Also, developers get extensive options for creating static and interactive maps and working with different projections.

We have handpicked the top and tending open-source Python libraries that make geospatial analysis more accessible and efficient. Moreover, they are actively maintained and are an excellent choice for your next geospatial analysis project or application development.

Fiona:

• Used in Geo, Map applications, etc.
• Useful for reading and writing spatial data in various formats.
• Supports shapefiles and GeoJSON.

Geopandas:

• Used for working with geospatial data.
• Adds support for geographic data to pandas objects.
• Provides a high-level interface for multiple geometries.

Shapely:

• Used for performing geometric operations on points, lines, and polygonal shapes.
• Offers manipulation and analysis of planar geometric objects.
• Build using the extensively deployed GEOS, a C++ open-source geometry library.

Pyproj:

• Used for performing coordinate transformations.
• Allows projections from one coordinate system to another.
• Provides interface to PROJ (cartographic projections and coordinate transformations library).

Rasterio:

• Used for reading and writing raster data, such as satellite imagery.
• Provides a Python API based on N-D arrays.
• Offers binary packages for Linux, macOS, and Windows.

Folium:

• A library for creating interactive maps using the popular leaflet.js library.
• Allows data manipulation in Python and visualization in a Leaflet map.
• Supports image, video, GeoJSON, and TopoJSON overlays.

Geopy:

• Used in Web Services, REST applications, etc.
• Useful for working with geographic data, including geocoding and distance calculations.
• Helps locate coordinates, addresses, cities, countries, and landmarks across the globe.