How well do you know your GIS formats?
Because an unknown GIS file format can be every GIS analysts worst nightmare.
In your GIS career, you’re going to encounter a wide range of GIS formats.
GIS technicians manage, share and create data in various geospatial data formats. Some are common. Some are not so common.
We’ve got you covered with our comprehensive list of GIS formats. Take a look and bookmark it for future reference:
Vector GIS File Formats:
Vector data is not made up of a grid of pixels. Instead, vector graphics are comprised of vertices and paths. The three basic symbol types for vector data are points, lines and polygons (areas).
Here are the vector GIS file formats that house geospatial data.
READ MORE: GIS Spatial Data Types: Vector vs Raster
The shapefile is BY FAR the most common geospatial file type you’ll encounter. All commercial and open source accept shapefile as GIS formats. It’s become the industry standard.
But you’ll need a complete set of three files that are mandatory to make up a shapefile. The three required files are – SHP is the feature geometry, SHX is the shape index position and DBF is the attribute data.
You can optionally include these files but are not completely necessary. PRJ is the projection system metadata, XML is the associated metadata, SBN is the spatial index for optimizing queries and SBX helps loading times.
KMZ/KML (Keyhole Markup Language)
KML stands for Keyhole Markup Language. This GIS format is XML-based and is primarily used for Google Earth. KML was developed by Keyhole Inc which was later acquired by Google.
KMZ (KML-Zipped) replaced KML as being the default Google Earth geospatial format because it is a compressed version of the file. KML/KMZ became an international standard of the Open Geospatial Consortium in 2008.
The longitude, latitude components (decimal degrees) are as defined by the World Geodetic System of 1984 (WGS84). The vertical component (altitude) is measured in meters from the WGS84 EGM96 Geoid vertical datum.
GDB (File Geodatabase)
Esri created the file geodatabase to be a container for storing multiple attribute tables, vector and raster data sets. It’s the successor of the personal geodatabase (MDB) – and Esri recommend file geodatabases over personal geodatabases.
File geodatabases offer structural and performance advantages. They have fast performance, versatile relationships, compatible storage for rasters, improved spatial indexes, data compression, customizable configuration and 1 terabyte file size restrictions…
Within a geodatabase, shapefiles are referred to as feature classes. It can store more complex data such as networks, raster mosaics and feature data sets.
MDB (Personal Geodatabase)
Once upon a time, personal geodatabases used to be all the talk of GIS. Manage multiple attribute tables, vector and raster data sets. Create relationship classes in a flash.
Yes, personal geodatabases are a lot like file geodatabases. But you won’t really know it until you start adding a lot of data to it.
The Microsoft access-based personal GDB (MDB) are called at only 2GB of storage. While file geodatabases offer 2TB of capacity. You’ll quickly reach storage capacity with personal geodatabases when you add a couple of raster and vector data sets.
Layer files are used for displaying a set of symbology in a map. It doesn’t contain the geographic data itself, layer files simply specify how the data will be displayed.
When you share a vector or raster data set, a layer file ensures the same symbology will be displayed in another map. The GIS user has to repath the layer file to the shapefile or feature class. Layer files can represent polygons, polylines, points or raster data sets.
OpenStreetMap is the largest crowdsourcing GIS data project of the planet Earth.
The GIS format .OSM is OpenStreetMap’s XML-based file format. The more efficient, smaller PBF Format (“Protocolbuffer Binary Format”) is an alternative to the XML-based format.
The data interoperability in QGIS can load native .OSM files. The OpenStreetMap plugin can convert PBF to OSM, which then can be used in QGIS.
The ArcInfo coverage GIS format is an older type of GIS geospatial format. It has no extension, just a set of folders. Coverages use feature classes, stored as points, arcs, polygons or annotation. Tics are geographic control points and help define the extent of the coverage.
Attributes are stored in the ADF or INFOb tables. Each feature is identified with a unique number. These feature numbers are a way to link attribute data with each spatial feature.
E00 ArcInfo Interchange
This GIS format is used to conveniently exchange GIS coverage files. It has the extension E00 and increases incrementally (E01, E02…) with individual coverage files.
Although convenient for interchange, you need to process the data before you can add it to ArcGIS. Run the ‘Import from E00’ in the Conversion ArcToolbox in order to access the data.
ArcSDE (Spatial Database Engine)
ArcSDE serves data in a centralized way over an entire organization using a relational database management system. GIS users can seamlessly access spatial data using Esri ArcMap, ArcEditor, ArcInfo and other products.
ArcSDE facilitates versioned editing with multiple users over the same network. Users can easily publish to the web. ArcSDE geodatabases with with several DBMS storage models including Oracle, Microsoft SQL Server, IBM DB2, IBM Informix and PostgreSQL.
GBF DIME (Geographic Base File, Dual Independent Map Encoding)
The GPF-DIME file format was developed by the US Census Bureau in the late 1960s. It was one of the first GIS data formats. It was used to store the US road network for major urban areas, which is a key factor in census information.
GPF-DIME supports choropleth mapping. It also helped in error removal for digitizing features. DIME was a key component to the current TIGER (Topologically Integrated Geographic Encoding and Referencing) system, which is produced by the US Census Bureau.
Open Source GIS File Formats:
These open source GIS formats can be freely accessed with the ability to hold all spatial and non-spatial files in one file.
PostGIS + PostgreSQL
Open source PostGIS adds spatial objects to the cross platform PostgreSQL database. The three features that PostGIS delivers to PostgreSQL DBMS are spatial types, indexes and functions.
With support for different geometry types, the PostGIS spatial database allows querying and managing information about locations and mapping. PostGIS can be leveraged in several GIS software packages including QGIS, GRASS, ArcGIS and MapInfo.
SpatialLite uses the SQLite relational database management system. But SpatialLite extends SQLite by giving it spatial capabilities. It is the rough equivalence to PostgreSQL + PostGIS.
SpatialLite is open source and light weight with the ability to hold all spatial and non-spatial files in one file.
TIN (Triangular Irregular Network)
TINs are vector-based models depicting three-dimensional elevation surface terrains. Using three dimensional coordinates (x, y and z), TINs connect vertices and form non-overlapping planar triangles.
TINs are vector alternative to the raster-based Digital Elevation Model (DEM). They are flexible enough to determine which points are necessary for an accurate representation of the terrain. This reduces data storage requirements.
Raster GIS Formats
Raster data is made up of pixels (also referred to as grid cells). They are usually regularly-spaced and square but they don’t have to be. Rasters often look pixelated because each pixel is associated with a value or class.
If you wanted to add attribute data to a raster file, the Esri Grid format is your best option. But the catch is that you can only add attributes to integer grids. The attributes are stored in a value attribute tables (VAT) – one record for each unique value in the grid, and the count representing the number of cells.
The two types of Esri Grid files are integer and floating point grids. Land cover would be an example of a discrete grid. Each class has a unique integer cell value. Elevation data is an example of a floating point grid. Each cell represents an elevation floating value. Grids have no extension.
GeoTIFF (Geographic Tagged Image File Format)
The GeoTIFF has become an industry image standard file for GIS and satellite remote sensing applications. Almost all GIS and image processing software packages have GeoTIFF compatibility.
GeoTIFFs may be accompanied by other files. TFW is the world file that is required to give your raster geolocation. XML optionally accompany GeoTIFFs and are your metadata. AUX out auxiliary files store projections and other information.
Highly Compressed Raster GIS File Formats
Lossy GIS compression reduces file size by permanently eliminating certain information, especially redundant information (even though the user may not notice it). These lossy compression algorithms often result in greater reductions of file size. Here are examples of highly compressed GIS formats”
JPEG 2000 (Joint Photographic Experts Group)
JPEG 2000 typically have a JP2 file extension. They are a wavelet compression with the latest JPG format giving an option for lossy or lossless compression.
The JPEG 2000 GIS formats require a world file which gives your raster geolocation. JPEG 2000 is an optimal choice for background imagery because of the lossy compression. JPEG 2000 can achieve a compression ratio of 20:1 which is similar to MrSID format.
MrSID (Multiresolution Seamless Image Database)
LizardTech’s proprietary MrSID format is commonly used for orthoimages in need of compression. MrSID images have an extension of SID and are accompanied with a world file with the file extension SDW.
MrSIDs have impressive compression ratios. Color images can be compressed at a ratio of over 20:1. LizardTech’s GeoExpress is the software package capable of reading and writing MrSID format.
ECW (Enhanced Commission Wavelet)
ECW is a compressed image format typically for aerial and satellite imagery. This GIS file type is known for its high compression ratios while still maintaining quality contrast in images.
ECW format was developed by ER Mapper, but it’s now owned by Hexagon Geospatial.
ASCII (American Standard Code for Information Interchange)
ASCII uses a set of numbers between 0 and 255 for information storage and processing.
In their native form, ASCII text files store GIS data in a delimited format – this could be comma, space or tab-delimited format. Going from non-spatial to spatial data, you can run a conversion process tool like ASCII to raster.
Multi-Temporal GIS Formats
Temporal data has a time component attached to it. A lot of weather data uses temporal GIS data formats because how important time is related to weather. Other examples of temporal data are demographic trends, land use patterns and lightning strikes.
NetCDF (Network Common Data Form)
NetCDF GIS format is an interface for array-oriented data for storing multi-dimensional variables. An example of a multi-dimension NetCDF could be temperature, precipitation or wind speed over time. It’s commonly used for scientific data involved in the oceanic and atmospheric community as a GIS data storage format.
The ArcGIS multidimensional toolbox and the QGIS NetCDF Browser both offer support for NetCDF files.
GRIB (GRIdded Binary or General Regularly-distributed Information in Binary form)
Similar to NetCDF, GRIB files are commonly used in meteorology to store historical and forecast weather data. It’s a multidimensional file with the advantages of self-description, flexibility and expandability.
GRIB is standardized by the World Meteorological Organization’s Commission and in operation since 1985. Currently, there are three versions of GRIB files (GRIB 0, 1 and 2). There are tools to convert GRIB into rasters such as grb2grid and QGIS software.
HDF (Hierarchical Data Format)
HDF (Hierarchical Data Format) was designed by the National Center for Supercomputing Applications (NCSA) to manage extremely large and complex scientific data. It’s a versatile data model with no limit on the number of size of data objects in the collection.
ArcGIS is capable of reading HDF4 and HDF5 data. The free open source GDAL (command-line) tools supports the conversion of HDF files to GeoTIFF. The HDFView program allows users to view HDF files.