Soil Moisture And Drought Monitoring In Casablanca-Settat Region, Morocco By The Use Of Gis And Remote Sensing

摘要

Soil moisture (SM) is a key factor in climate, hydrology, and agronomy. Its assessment is therefore important and constitutes an alert parameter for desertification. It impacts the heat and mass transfers between soil and atmosphere. However, information access in the regional or global scale is very complicated which usually leads to a rough estimate, or completely disregard of this parameter. Today, remote sensing offers a solution to this problem by providing access to this information through the satellite images. The use of geospatial data to generate adequate information on droughts, we applied the remote sensing method based on the use of the Soil Moisture Index (SMI), which in its algorithm uses the data obtained from satellite sensors. As reported by Hunt et al., The index is based on actual water content (), water capacity and wilting point. The multispectral satellite images from the visible (red band) and infrared (near-infrared and thermal band) bands are essential for the calculation of the index, which is why we used Landsat 8 OLI/TIRS in this context, then SMOS disaggregated data is chosen to be compared with SMI and MI (Moisture Index) used in this work. On the other side, drought monitoring in Morocco faces complexity in the evidence that it depends on a lot of parameters including the SM. Thus, the aim of this paper is firstly to analyze the spatiotemporal variation of SM from SMOS in Casablanca-Settat region of Morocco site during five successive years 2013 to 2017. For that, the first temporal SM values mapping of the study area is established for each year of 2013 to 2017. Next, for each year we will compare SM from SMOS with SMI by drawing the graph line of SM variability in this period and generating differences maps. Secondly, we will evaluate the effect and the impact of Soil Moisture Index (SMI) in Drought monitoring by calculation of Land Surface Temperature (LST) from Landsat 8 OLI/TIRS, and define which indexes are more indicated for assessing soil conditions.