Period: 1992 – 2015
Sensor: AVHRR, PROBA-V, SPOT-VGT, MERIS FR & RR
Data can be accessed here.
Algorithm description: The algorithm uses time series of surface reflectance data and derives land cover map using ‘machine learning’ and unsupervised classification algorithms. FAO LCCS system is followed for classification.
Accuracy: Detailed validation is still ongoing, however, some limited work shows that the accuracy is highly dependent on the region and classes.
- Abrupt changes between classes have been captured better than gradual changes.
- Global assessment has not yet been done.
Bontemps, S. et al. Multi-year global land cover mapping at 300 m and characterization for climate modelling: achievements of the Land Cover component of the ESA Climate Change Initiative. ISPRS – Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XL-7/W3, 323–328 (2015).