Аннотация:An extensive remotely sensed dataset recently available to the scientific community, The Global Land 1-km AVHRR Project, has been used to examine the possibilities of multi-temporal imagery for mapping and monitoring changes in the biophysical characteristics of land cover. Our goal was to investigate the regional response of the soil-vegetation system to climate in arid zones. We addressed this problemby applying theoretical models to obtain parameters such as Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) from satellite data and by analysing the spatial-temporal dynamics of these parameters. Morocco was selected as the area of study due to its high environmental diversity. This area is also clearly affected by the risk of the advance of the desert. Using The Global Land 1-km AVHRR Project dataset, two methodologies are proposed for the monitoring of land cover dynamics in different areas of interest defined using as mapping criteria the Annual Average of NDVI (AANDVI): (1) The Method of the Area of the Triangle (MAT), based on a form described by the annual evolution of LST and NDVI in each area; (2) the Method of the Slope, which analyses the slope of the line defined by the months of the maximum NDVI and the minimum LST.
