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

Abstract

ABSTRACT Desertification is the degradation process caused by climatic conditions and human activities that results in loss of soil productivity and decline in vegetation growth in the long term. Several indices related to vegetation, soil and climate are used to monitor desertification, but few studies explore qualitative and quantitative aspects of indices on desertification on spatial and hierarchical scale. This study aims to identify and measure indices related to increased risk of desertification on global, local and hierarchical scales using multinomial logistic regression models. Images from TM, ETM+ and OLI sensor from 1997 to 2018 in the end of dry and rainy seasons were used to quantify NDVI, TGSI, albedo, temperature, aridity index, evapotranspiration and precipitation on global spatial scale (Irauçuba Centro Norte) and local spatial scale (Miraíma, Canindé, Irauçuba and Santa Quitéria). GISD was calculated by geometric mean of weighted indices and segmented into 8 classes of susceptibility to desertification (hierarchical scale). The results showed that the best models were obtained on local scale and for the end of the rainy season. Temperature proved to be the most important variable for increased risk of desertification on global, local and hierarchical scales. Therefore, the increase in the risk of desertification in the studied areas is due to human activities of deforestation, overgrazing and fire. These factors contributed to reduction of vegetation cover and increase in temperature, changing the microclimatic, which led to decline in precipitation and worsening of desertification.

Keywords

• Precipitation
• Temperature
• Deforestation
• Microclimate