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

Resumo

Desertifi cation 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
desertifi cation, but few studies explore qualitative and quantitative aspects of indices on desertifi cation on spatial and hierarchical scale.
This study aims to identify and measure indices related to increased risk of desertifi cation 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 desertifi cation (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 desertifi cation on global, local and hierarchical scales. Therefore, the increase in the risk of desertifi cation in the
studied areas is due to human activities of deforestation, overgrazing and fi re. These factors contributed to reduction of vegetation
cover and increase in temperature, changing the microclimatic, which led to decline in precipitation and worsening of desertifi cation.