Glossary
Key terms in geospatial intelligence, satellite imagery, and earth observation.
NDVI
Normalized Difference Vegetation Index. A spectral index calculated from red and near-infrared bands that measures vegetation health and density. Values range from -1 to 1, with higher values indicating healthier, denser vegetation. Widely used in agriculture, forestry, and environmental monitoring.
SAR
Synthetic Aperture Radar. An active microwave imaging system that transmits radar pulses and measures the reflected signal. Unlike optical sensors, SAR works through clouds and at night, making it essential for all-weather monitoring. Sentinel-1 is a commonly used SAR satellite.
Multispectral Imagery
Satellite imagery captured across multiple wavelength bands beyond visible light, typically including near-infrared and shortwave infrared. Enables analysis of features invisible to the human eye, such as plant health, water content, and mineral composition.
Change Detection
The process of identifying differences between satellite images captured at different times. Used to monitor construction, deforestation, flood extent, crop growth, and urban expansion. Typically involves comparing spectral signatures or derived indices across image pairs.
Land Cover Classification
The categorisation of Earth surface into classes such as forest, water, urban, agricultural, and bare soil. Machine learning models trained on satellite imagery can classify land cover at scale, enabling monitoring of land use change over time.
GeoTIFF
A standard file format for georeferenced raster imagery. Embeds geographic coordinate system information directly in the TIFF file, allowing the image to be precisely positioned on Earth. The dominant format for satellite imagery distribution.
COG
Cloud Optimised GeoTIFF. A GeoTIFF file structured to enable efficient streaming and partial reads over HTTP. Allows applications to request only the pixels they need rather than downloading entire files. Essential for web-based satellite imagery applications.
STAC
SpatioTemporal Asset Catalog. A specification for organising and querying geospatial data. Provides a common language for describing satellite imagery collections, enabling interoperability between data providers and simplifying search across archives.
GeoJSON
A JSON-based format for encoding geographic data structures including points, lines, and polygons. Widely supported by web mapping libraries and APIs. The standard format for exchanging vector geometry between geospatial services.
WKT
Well-Known Text. A text markup language for representing vector geometry. Used in databases like PostGIS and many GIS applications. Example: POINT(144.9631 -37.8136) represents a coordinate in Melbourne, Australia.
PostGIS
A spatial database extension for PostgreSQL that adds support for geographic objects. Enables SQL queries on spatial data, including proximity searches, intersection tests, and area calculations. The foundation of many geospatial applications.
Foundation Model
A large machine learning model trained on broad data that can be adapted to many downstream tasks. In earth observation, foundation models trained on satellite imagery can answer diverse questions about locations without task-specific training.
Earth Observation
The gathering of information about Earth using remote sensing technologies, primarily satellites. Encompasses optical, radar, and thermal sensors capturing data about land, ocean, and atmosphere. Also called remote sensing or satellite imagery analysis.
Remote Sensing
The science of obtaining information about objects or areas from a distance, typically from aircraft or satellites. Includes both passive sensors (measuring reflected sunlight) and active sensors (emitting their own energy, like radar).
Sentinel-1
A pair of European Space Agency satellites carrying C-band SAR instruments. Provides all-weather, day-and-night radar imagery with a 6-day revisit time over Europe and 12 days globally. Critical for flood mapping, sea ice monitoring, and ground deformation measurement.
Sentinel-2
A pair of European Space Agency satellites carrying multispectral optical instruments. Captures 13 spectral bands at 10-60 metre resolution with a 5-day revisit time. The primary data source for vegetation monitoring, land cover mapping, and change detection.
Landsat
A joint NASA/USGS satellite program providing the longest continuous record of Earth observation data, dating to 1972. Landsat 8 and 9 currently operate with 30-metre resolution optical imagery. Essential for long-term environmental change studies.
Spatial Resolution
The size of the smallest feature that can be detected in an image, typically expressed as pixel size on the ground. Sentinel-2 has 10-metre resolution for visible bands. Higher resolution means more detail but larger data volumes and narrower coverage.
Temporal Resolution
How frequently a satellite revisits and images the same location. Sentinel-2 has a 5-day revisit time. Higher temporal resolution enables monitoring of rapidly changing phenomena like floods, fires, and crop growth.
Spectral Band
A specific range of wavelengths captured by a satellite sensor. Different bands reveal different surface properties: blue for water depth, red for vegetation absorption, near-infrared for plant health, shortwave infrared for moisture content.