Integración de imágenes del sensor MODIS y cartografía temática para la simulación de modelos geoespaciales para obtener zonas propensas a desertificación en el Estado de Sinaloa, México

Abstract

Desertification is a complex process, involving environmental and anthropogenic factors in a dry climate context. This process has a global importance, because it reduces the productivity and value of causing an impact on the territory and its population. The information technology helps identify areas prone to desertification through geospatial and quantitative indicators. This research therefore seeNs to develop a methodology that allows to model the input variables obtained from MODIS sensor data, thematic mapping and statistical information, which is then integrated from multicriteria evaluation technique weighted linear sum. The varia- bles were considered are: increased albedo, reduce biomass, deforestation, spearly vegetated areas; vegetated areas (green cover); moisture content in the soil; precipitation; surface temperature; distance of human assessment, agriculture, hidrology networNs; areas with physical and chemical degradation and areas with water and wind erosion. The weighting is performed with the method of Saaty pairwise comparison. To provide robustness to generated model, it proceeded to perform a validation of the result (desertification index) using land use and vegetation maps, climate and humidity, arid index and intensity of soil degradation. Desertification index show that most vulnerable areas are in the northern of Sinaloa and reduced southward.