Various monthly remote sensing dataset have been published in the context of the LANDSURF project in a spatial resolution of 1 x 1 km which are all based on MODIS and AVHRR datasets covering a period of 40 years which include the following:
Besides the vegetation indices NDVI and LAI we also published a monthly 1x 1 km land cover classification identifying 16 different land cover classes.
In addition, two binary parameters, i.e. forest cover and vegetation cover were contributed to the LANDSURF project. On top we provided a land surface albedo dataset.
For predicting the restrospective indices the STARFM algorithm was utilized in a Python environment.
In addition, the dataset (https://dx.doi.org/10.58160/gGzexcbDikobkyvK) contains climatological and agrometeorological indices of West Africa for 1981-2100 which are based on global and regional climate models (CMIP5 and CORDEX-CORE) calculated by our colleagues from Climatology, Dr. Katrin Ziegler, Dr. Daniel Abel and Prof. Dr. Heiko Paeth . Future greenhouse gas emissions scenarios (low (RCP2.6) and a high (RCP8.5)) were used.
