Satellitederived

Satellite-derived refers to information, measurements, or products obtained from observations made by Earth-orbiting satellites. These data are usually the result of remotely sensed measurements across one or more spectral, radar, or altimetric instruments and are transformed into higher-level variables such as maps, indices, or estimates for various applications. The term is widely used across disciplines to describe data products created from satellite imagery and related sensor data rather than from ground-based or airborne sources.

Typical data sources include optical sensors on satellites like Landsat, Sentinel-2, and MODIS; radar instruments such as Sentinel-1 SAR; ocean color sensors for mapping chlorophyll; and altimeters used for sea surface height. Derived products range from land cover classifications and vegetation indices to surface temperature, soil moisture, precipitation estimates, sea surface temperature, and atmospheric corrections. Processing workflows usually involve calibration, georeferencing, atmospheric and radiometric correction, data fusion, and the application of domain-specific algorithms to generate usable variables.

Applications span many sectors, including agriculture and food security (crop health, yield estimation), forestry (biomass, deforestation monitoring), hydrology (soil moisture, flood mapping), climate science (long-term trends, anomaly detection), urban planning, and disaster response. Advantages of satellite-derived data include global, repeatable coverage and the ability to monitor inaccessible regions over long timescales. Limitations can include cloud cover for optical data, resolution constraints, need for validation with in-situ measurements, data volume, and licensing or access restrictions. The term underscores data that originate from satellites and are transformed into practical information products.