What does this research mean for the field?

Agricultural drought vulnerability in Sivagangai District, India, has drastically worsened over the past 30 years, with areas classified as 'Very High' vulnerability increasing from 1.08% in 1994 to 40.04% in 2024. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To assess agricultural drought vulnerability across a semi-arid landscape over a 30-year timeframe using integrated remote sensing and GIS methods.

September 6, 2026Biosphere0 citationsOpen Access

Remote Sensing and GIS Modeling for Agricultural Drought Vulnerability Monitoring

Integrated Remote Sensing and GIS-Based Agricultural Drought Vulnerability Assessment in Sivagangai District, Tamil Nadu, India

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Authors

KTKongeswaran Thangaraj MRM. Rajendran PVPerumal Velmayil

Discussion

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Overview

Spatiotemporal analysis reveals a steep rise in severe agricultural drought vulnerability across semi-arid farmland, highlighting an urgent need for targeted water and land management.

Key Points

To assess agricultural drought vulnerability across a semi-arid landscape over a 30-year timeframe using integrated remote sensing and GIS methods.
Analyzed multi-temporal Landsat satellite imagery and climate data spanning from 1994 to 2024.
Derived biophysical and climatic indicators including NDVI, NDWI, VCI, SMI, LST, LULC, and SPI.
Applied the Analytic Hierarchy Process to calculate indicator weights and generate drought vulnerability maps.
The area classified under 'Very High' agricultural drought vulnerability increased from 1.08% in 1994 to 40.04% in 2024.
Spatiotemporal assessments showed a marked reduction in vegetated and moist zones, accompanied by an increase in high-temperature areas and built-up land.
Vegetation index (NDVI) and water index (NDWI) were identified as the primary indicators influencing agricultural drought vulnerability.

Cite This Study

Thangaraj et al. (2026) studied this question.

synapsesocial.com/papers/6a9d1ea728139818eab21a38 https://doi.org/10.3390/biosphere2030009

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September 6, 2026Biosphere0 citationsOpen Access

Remote Sensing and GIS Modeling for Agricultural Drought Vulnerability Monitoring

Integrated Remote Sensing and GIS-Based Agricultural Drought Vulnerability Assessment in Sivagangai District, Tamil Nadu, India

View Full Paper

Ask AI

Bookmark

Authors

KTKongeswaran Thangaraj MRM. Rajendran PVPerumal Velmayil

Discussion

Member takes

Overview

Spatiotemporal analysis reveals a steep rise in severe agricultural drought vulnerability across semi-arid farmland, highlighting an urgent need for targeted water and land management.

Key Points

To assess agricultural drought vulnerability across a semi-arid landscape over a 30-year timeframe using integrated remote sensing and GIS methods.
Analyzed multi-temporal Landsat satellite imagery and climate data spanning from 1994 to 2024.
Derived biophysical and climatic indicators including NDVI, NDWI, VCI, SMI, LST, LULC, and SPI.
Applied the Analytic Hierarchy Process to calculate indicator weights and generate drought vulnerability maps.
The area classified under 'Very High' agricultural drought vulnerability increased from 1.08% in 1994 to 40.04% in 2024.
Spatiotemporal assessments showed a marked reduction in vegetated and moist zones, accompanied by an increase in high-temperature areas and built-up land.
Vegetation index (NDVI) and water index (NDWI) were identified as the primary indicators influencing agricultural drought vulnerability.

Cite This Study

Thangaraj et al. (2026) studied this question.

synapsesocial.com/papers/6a9d1ea728139818eab21a38 https://doi.org/10.3390/biosphere2030009

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