A GeoTIFF is a special type of image file (usually a .tif) that stores geographic information inside the image itself. In addition to pixel values (like colors or elevations), it includes data that tells software where the image sits on the Earth, such as its coordinate system, map projection, location, and pixel size. This makes GeoTIFFs widely used in GIS, remote sensing, and environmental science for things like satellite imagery, elevation models, and mapped water‑quality data.
To use a GeoTIFF, you typically open it in GIS or data‑analysis software such as QGIS, ArcGIS, or Python libraries like rasterio or xarray. Because the spatial information is embedded, the file will automatically line up correctly with other spatial layers (like rivers, boundaries, or sampling sites). You can visualize it as a map, extract values at specific locations, analyze spatial patterns, or combine it with other datasets. In short, a GeoTIFF lets you treat an image as real‑world, map‑aware data, not just a picture.
Many types of software support GeoTIFF files, ranging from full GIS platforms to programming tools and even some image viewers.
GIS and mapping software
- QGIS (free, open‑source) – widely used and very strong GeoTIFF support
- ArcGIS Pro / ArcMap (Esri) – industry standard GIS tools
Remote sensing and scientific tools
- Google Earth Pro – can display GeoTIFFs (often after conversion)
- SNAP (ESA) – used for Sentinel satellite data
Programming and data‑science tools
- Python: rasterio, GDAL, xarray, rioxarray
- R: terra, raster, stars
Image viewers (limited support)
- Preview (macOS) and some TIFF viewers can open GeoTIFFs as images, but they usually ignore the geographic information, so they are not suitable for analysis.
A rainfall map produced from a gridded climatology raster, showing the mean annual rainfall total (mm) for New Zealand, based on the 1991-2020 climatology period. Every 500x500 m ‘square’ (or cell) in the gridded dataset contains a single value indicating the long term annual average rainfall total. The values have been grouped into classes (e.g., 250-500 mm, 500-750 mm), with each class symbolised by a different colour on the map.