Spatiotemporal
agricultural drought analysis in Sivaganga district using Remote sensing indices
and Google Earth Engine
Suvish S.
Disaster Advances; Vol. 18(12); 31-40;
doi: https://doi.org/10.25303/1812da031040; (2025)
Abstract
Agricultural drought poses a significant threat to crop productivity and rural livelihoods,
particularly in semi-arid regions such as Sivaganga district in Tamil Nadu, India.
This study leverages the capabilities of Google Earth Engine (GEE) to assess agricultural
drought vulnerability using Landsat 8 satellite data spanning from 2018 to 2024.
Key remote sensing indices including the Normalized Difference Vegetation Index
(NDVI), Vegetation Condition Index (VCI), Land Surface Temperature (LST), Temperature
Condition Index (TCI) and Vegetation Health Index (VHI), were analyzed within the
GEE platform to evaluate spatial and temporal drought patterns. The results indicate
that the northeastern and central regions of Sivaganga district experienced severe
to very severe drought during 2018, 2020 and 2021, primarily due to low precipitation,
elevated thermal stress and prolonged dry spells. Conversely, the southern regions
demonstrated greater resilience, with moderate to no drought conditions observed
in 2019 and 2023. Emerging moderate drought conditions in 2024 in the eastern part
of the district signal a potential trend toward increased aridity. The integration
of NDVI, VCI, LST, TCI and VHI within GEE provided a robust framework for comprehensive
drought assessment, revealing strong correlations between thermal stress and vegetation
health.
This study underscores the importance of adaptive water management strategies, reforestation
efforts and climate-resilient agricultural practices to mitigate drought risks.
The findings offer actionable insights for targeted agricultural planning and sustainable
resource management, highlighting the critical role of remote sensing and cloud-based
platforms like GEE in supporting informed decision-making in drought-prone regions.
