Integrating Cloud-Based Geospatial Analysis for Understanding Spatio-Temporal Drought Dynamics and Microclimate Variability in Rajasthan: Implications for Urban Development Planning

Abstract

This study examines the spatio-temporal dynamics of drought and microclimate variability in Rajasthan, India, from 2010 to 2022 using the Standardized Drought Composite Index (SDCI). The SDCI integrates the Temperature Condition Index (TCI), Precipitation Condition Index (PCI), and Vegetation Condition Index (VCI) to assess drought severity. Remote sensing data from MODIS and CHIRPS were processed using Google Earth Engine (GEE) for large-scale, continuous drought monitoring. The results reveal significant drought conditions in 2014, 2015, 2020, 2021, and 2022, with southeastern districts like Kota, Bundi, and Baran experiencing SDCI values below 0.2, indicating severe drought. Arid regions, including Jaisalmer, Barmer, and Bikaner, consistently exhibited extreme drought (SDCI < 0.1) due to low annual precipitation (less than 250 mm). In contrast, semi-humid regions like Udaipur and Ajmer showed variable drought intensities linked to localized climatic factors. Temperature-related vegetation stress was particularly high during pre-monsoon periods, affecting agricultural productivity. The spatial analysis highlights significant regional disparities in drought severity, emphasizing the need for tailored, location-specific drought management strategies. Incorporating green infrastructure, such as urban forests and permeable pavements, is recommended to mitigate the impacts of drought and desertification. This study underscores the utility of cloud-based geospatial tools for drought monitoring and resource planning, providing critical insights for sustainable urban and agricultural development. Future research could refine the SDCI methodology and integrate socio-economic factors to enhance drought resilience.