Monthly Remote Sensing Indicators for West Africa predicted to support climate models

Monthly Remote Sensing Indicators for West Africa predicted to support climate models

October 1, 2024

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.

 

 

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