Eff ect of indices on desertifi cation risk: spatial and hierarchical approach using multinomial logistic regression

Effect of index on desertification risk: spatial and hierarchical approach using multinomial logistic regression

Abstract

Desertification is the degradation process caused by climatic conditions and human activities that long term results loss of soil productivity and declive vegetation growth. Several index from vegetation, soil and climate are used to monitorig desertification, but few studies explore qualitative and quantitative index on desertification process on spatial and hierarchical scale. This work aims to identify and measure index related to increased risk of desertification on global, local and hierarchical scale using multinomial logistic regression models. Images from TM, ETM plus and OLI sensor between 1997 to 2018 in the dry and rainy to quantitative NDVI, TGSI, albedo, temperature, aridity index, evapotranspiration and precipitation on global spatial scale (Irauçuba Centro Norte) and local scale (Miraíma, Canindé, Irauçuba e Santa Quitéria). This IGSD calculated by geometric mean refers to score index, after to submit segmentation into 8 class of susceptibility to desertification (hierarchical scale). The results showed that the best models from local scale and rainy season. Temperature proved to be the most important variable increase risk of desertification on global, local and hierarchical scale. Therefore, the increase in the risk of desertification in the studied areas is due to human activities of deforestation, over grazing and fire. These factors results the reduction of vegetation cover and increase temperature, change microclimatic and results decline precipitation and more effect desertification problem.