The objective of this study is to contribute in assessing and monitoring drought’s vulnerability by developing a GIS-based model to determine vulnerable areas to this natural hazard; the model utilizes a series of agricultural, statistical, meteorological and remotely sensed data, using GIS weighed ponderation and multicriteria analysis decision making, with the integration of three components: climatic sensibility, soil sensibility and socioeconomic sensibility. The result is a vulnerability map classified into five classes according to pixel values. Very Vulnerable class forms 19.46% of the study area, vulnerable class forms 32.81% and 21.37% of the area is not vulnerable, the study presents a modeling procedure of which the final results provide to researchers, users and decision makers important information on the environmental situation of the study area, for better prediction, and risk management.

The objective of this study is to modeling and mapping the Forest fire risk in the region of Aures situated in Northeast of Algeria, through the application of multi-criteria analysis methods to integrate geographic information systems (GIS) and remote sensing. The methodology is based on a weighted linear combination of three parameters that influence the initiation and propagation of a forest fire. These are vegetation, topography and anthropogenic index. The result is a vulnerability map classified into four classes according to pixel values. very high risk class forms 18,28% of the study area, high risk class forms 42,42%, moderate risk class forms 5,24% and 34,05% of the area is low risk.