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Summary of Proposal LAN1363

TitleRemote sensing based assessment of agricultural land use in West Africa
Investigator Thiel, Michael - University of Wuerzburg, Geographical Institute, Department of Remote Sensing
Team Member
Prof. Dr. Dech, Stefan - German Aerospace Center (DLR), Earth Observation Center (EOC), German Remote Sensing Data Center (DFD)
Dr. Denich, Manfred - University of Bonn, Center for Development Research, ZEF
SummaryAgriculture employs over 60% of the economically active population in the West Africa. Farming is mostly small-holder (plots typically < 1ha), and heavily reliant on erratic rainfall. But this region has been identified as one of the most vulnerable to climate change (Boko et al. 2007). Climate change effects, such as floods and droughts, will thus increase poverty and food insecurity in the region. However, climate models, which predict future climate change effects, have seldom considered historical and future land use change in their predictions. Consequently, the linkages between climate change and land use change are poorly understood at local and regional levels (Vlek and Denich 2010). To this end, accurate information on land use change and their drivers is crucial to understanding the effects of climate change on land use patterns, which is vital for the sustenance of agricultural practice. Multi-temporal optical imagery has, over the 40 years, proven to be invaluable for mapping land use change at varying scales. For agricultural land use mapping, acquisition of images at different crop growth stages improves the detection of croplands. However, the susceptibility of optical systems to clouds often results in cloudy images during the rainy season. Consequently, images of critical crop growth stages are often missing in regions like West Africa, a situation that negatively affects agriculture land use mapping efforts. The solution to this problem lies in Radar systems, which are less affected by clouds due to their longer operative wavelength. Systems such as TerraSAR-X are able to acquire cloud free images, especially in the rainy season, which can be used in a complementary way with optical images for a detailed mapping of agricultural landuse change pathways. The project team proposes to use a combination of Radar (TerraSAR-X) and Optical (RapidEye) images for a detailed mapping of crops and cropping systems at watershed level in the Sudanian Savanna of West Africa. The proposal requires multi-temporal, dual polarization TerraSAR-X data to be acquired on three watersheds with a total size of 6100km2. Multi-temporal data from the two systems will be aligned to the agro-ecological calendar for a better understanding of local-scale changes in land use. Spectral and textural information of different land use classes will be extracted from the optical and radar data respectively and integrated in a classification scheme. Results obtained will feed into the setting up of an operational and repeatable land use mapping in West Africa, as well as in the formulation of CC adaptation and mitigation measures.

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DLR 2004-2016