Flood monitoring in a semi-arid environment using spatially high resolution radar and optical data

The geographic term “Niger Inland Delta” stands for a vast plain of approximately 40,000 km2, which is situated in the western Sahel (Republic of Mali). The Inland Delta is affected by yearly inundation through the variable water levels of the Niger–Bani river system. Due to a good availability of (surface) water, the ecosystem at the Niger Inland Delta serves as resting place stop-over for many migrating birds and other wildlife species as well as economic base for farmers and pastoral people. To foster the sustainable usage of its natural resources and to protect this natural heritage, the entire Niger Inland Delta became RAMSAR site in 2004. This paper aims to test to which extent texture analysis can improve the quality of flood monitoring in a semi-arid environment using spatially high resolution ASAR imaging mode data. We found the Gray Level Dependence Method (GLDM) was most suitable proceeding for our data. Several statistical parameters were calculated via co-occurrence matrices and were used to classify the images in different gradation of soil moisture classes. In a second step we used additional information from spatially high resolution optical data (ASTER) to improve the separability of open water areas from moisture/vegetated areas.