Casablanca, Morocco's economic capital continues today to fight against the proliferation of informal settle- ments affecting its urban fabric illustrated especially by the slums. Actually Casablanca represents 25% of the total slums of Morocco [1]. These are the habitats of all deprived of healthy sanitary conditions and judged precarious from the perspective humanitarian and below the acceptable. The majority of the inhabi- tants of these slums are from the rural exodus with insufficient income to meet the basic needs of daily life. Faced with this situation and to eradicate these habitats, the Moroccan government has launched since 2004 an entire program to create cities without slums (C.W.S.) to resettle or relocate families. Indeed the process control and monitoring of this program requires first identifying and detecting spatial habitats. To achieve these tasks, conventional methods such as information gathering, mapping, use of databases and statistics often have shown their limits and are sometimes outdated. It is within this framework and that of the great German Morocco project “Urban agriculture as an integrative factor of development that fits our project de- tection of slums in Casablanca. The use of satellite imagery, particulary the HSR, has the advantage of providing the physical coverage of urban land but it raises the difficulty of choosing the appropriate method to apply.This paper is actually to develop new approaches based mainly on object-oriented classification of high spatial resolution satellite images for the detection of slums.This approach has been developed for mapping the urban land through by integration of several types of information (spectral, spatial, contextual ...) (Hofmann, P ., 2001, Herold et al. 2002b; Van Der Sande et al., 2003, Benz et al., 2004, Nobrega et al., 2006). In order to refine the result of classification, we applied mathematical morphology and in particular the closing filter. The data from this classification (binary image), which then will be used in a spatial data- base (ArcGIS)

Casablanca, main metropolis of Morocco concentrates more than 46% of the working population. She is considered as the most affected city by the increase of the temperature. We have therefore chosen to base our study on the city of Ca- sablanca. The main objective of this study is to estimate the ground temperature in order to evaluate the impact of the vegetation on cooling the ground temperature. In order to move to the achievement and to identify the formation of is- lands of warmth or coolness which occur in the urban municipalities of Casablanca, we have used the satellites images Landsat 5 TM. Graphical analysis based on studying the correlation was performed to quantify the strength of the link between the coolest urban surfaces and the green spaces. To achieve this, we used “mono-window” algorithm which re- quires knowledge of the atmospheric transmittance, the emissivity of soil and the effective temperature of the air. This study revealed a strong correlation between vegetation cover and cold areas (R² = 0.911) and allowed us to determine graphically that there is a strong link between the urban ground temperature and the density of buildings