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World of GIS: 24 Essential File Formats You Should Know

6 min readOct 8, 2024

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Geographic Information Systems (GIS) have revolutionized the way we capture, store, analyze, and visualize spatial data.

Whether you’re mapping environmental changes, planning urban developments, or navigating new territories, GIS is at the heart of these processes. However, the multitude of file formats can be overwhelming.

To help you navigate this complex landscape, we’ve compiled a list of 20 essential GIS file formats that every GIS professional should know.

1. Shapefile (.shp, .shx, .dbf)

Developed by Esri, the Shapefile is one of the most common GIS file formats. It stores geometric location and attribute information of geographic features. While widely used, it has limitations like the inability to store topology and file size restrictions.

2. GeoJSON (.geojson)

GeoJSON is a format for encoding various geographic data structures using JavaScript Object Notation (JSON). It’s lightweight and easy to read, making it popular for web mapping applications.

3. KML/KMZ (.kml, .kmz)

Keyhole Markup Language (KML) is an XML-based format used for displaying geographic data in Earth browsers like Google Earth. KMZ is the compressed version of KML files, allowing for easier distribution.

4. GeoTIFF (.tif, .tiff)

GeoTIFF is a public domain metadata standard that allows georeferencing information to be embedded within a TIFF file. It’s commonly used for satellite imagery and digital elevation models.

5. CSV (.csv)

Comma-Separated Values (CSV) files are simple text files that can store tabular data. When combined with coordinate data, CSV files can represent spatial data points and are easily imported into GIS software.

6. GML (.gml)

Geography Markup Language (GML) is an XML grammar for expressing geographic features. It’s used for data interchange among GIS systems and supports complex geometries and topologies.

7. GPX (.gpx)

GPS Exchange Format (GPX) is an XML schema designed for transferring GPS data between applications. It’s commonly used in GPS devices and applications for sharing waypoints, tracks, and routes.

8. Esri File Geodatabase (.gdb)

The File Geodatabase is a collection of files in a folder that can store datasets including feature classes, raster datasets, and tables. It supports large datasets and allows for efficient data storage and management.

9. SpatiaLite (.sqlite)

SpatiaLite is an extension of the SQLite relational database. It adds spatial capabilities, allowing for efficient storage and querying of spatial data within a lightweight, standalone database file.

10. NetCDF (.nc)

Network Common Data Form (NetCDF) is a set of software libraries and machine-independent data formats for array-oriented scientific data. It’s widely used in climatology, meteorology, and oceanography for storing multidimensional data.

11. HDF (.hdf)

Hierarchical Data Format (HDF) is designed to store and organize large amounts of numerical data. Common in scientific computing, it’s used for handling complex datasets, including satellite imagery.

12. LAS/LAZ (.las, .laz)

LAS is a binary file format for storing LIDAR data. LAZ is the compressed version of LAS files. They store point cloud data collected from laser scanners, crucial for high-resolution topographic mapping.

13. DXF (.dxf)

Drawing Exchange Format (DXF) is a CAD data file format developed by Autodesk for data interoperability between AutoCAD and other programs. It’s used to represent both 2D and 3D drawings.

14. DWG (.dwg)

DWG is a proprietary binary file format used for storing design data and metadata. Native to Autodesk’s AutoCAD software, it’s widely used in engineering and architectural design.

15. Raster ASCII Grid (.asc)

ASCII Grid files are simple text files that represent raster data. Commonly used for representing elevation data, they are easy to read and import into various GIS applications.

16. WKT/WKB (.wkt, .wkb)

Well-Known Text (WKT) and Well-Known Binary (WKB) are formats for representing geometric objects. They’re used in databases and GIS software for spatial data interchange and support standard geometric types.

17. MapInfo TAB (.tab, .map, .dat, .id)

MapInfo TAB is a file format used by the MapInfo GIS software. It consists of multiple files that store spatial and attribute data, supporting complex mapping and analysis.

18. CADRG (.toc)

Compressed ARC Digitized Raster Graphics (CADRG) is a military standard for compressed raster maps. It’s used for efficient storage and rapid retrieval of map data in defense applications.

19. VTK (.vtk)

Visualization Toolkit (VTK) files are used for 3D computer graphics, image processing, and visualization. They’re common in scientific computing for visualizing complex data structures.

20. STL (.stl)

Stereolithography (STL) files are used for 3D printing and computer-aided manufacturing. They store 3D models and are useful in terrain modeling and visualization in GIS applications.

21. Geopackage (.gpkg)

GeoPackage is an open, standards-based, platform-independent, portable, self-describing, compact format for transferring geospatial information.

22. NTF

The files with extension .ntf extension are called the National Transfer Format (NTF) Files; mostly used by the U.K. Ordnance Survey (OS); specifically for the transfer of geospatial data.

23. FlatGeobuf

Is a new geospatial data format that allows users to work more efficiently with vector data. It can be used as a replacement for GeoJSON, providing smaller file sizes and faster loads. It is a binary (FlatBuffers-encoded) format that defines geospatial geometries. It is row-oriented rather than columnar like GeoParquet and GeoArrow and offers a different set of trade-offs.

24. GeoParquet

Apache Parquet is a powerful column-oriented data format, built from the ground up to as a modern alternative to CSV files. GeoParquet is an incubating Open Geospatial Consortium (OGC) standard that adds interoperable geospatial types (Point, Line, Polygon) to Parquet.

Understanding these file formats is essential for efficient GIS work. Each format serves specific purposes and comes with its own features and limitations.

By familiarizing yourself with them, you can choose the right tools for your projects and ensure smooth data interoperability.

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Felipe Limeira 🌍
Felipe Limeira 🌍

Written by Felipe Limeira 🌍

I'm Full Stack GIS Developer, this is a place where I write about the subjects I study and my experiences.

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