Enhancing aridity index assessment in Pakistan's dryland ecosystems: A machine learning approach integrating remote sensing and seasonal lag effects
Mazhar, N.; Ghalub, A.K.; Malki, I.; Noreena; Arshad, S. · University of Westminster Research
Dryland ecosystems are highly vulnerable to increased aridity, thus exacerbating the drought stress. From this perspective, our study aimed to evaluate the aridity index (AI) and Standardized Precipitation Index at a three-month scale (SPI-3) across three arid stations of Pakistan from 1990 to 2023. Seven remote sensing indices were used as covariates with S…
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