Modeling climate change impacts on coastal land use and vegetation dynamics
- 1Department of Chemistry, School of Advanced Sciences, Vellore Institute of Technology
- 2Tamil Nadu Forest Department and Biodiversity Conservation Foundation (BCF)
Abstract
Coastal deltaic landscapes are increasingly vulnerable to the dual pressures of rapid urbanization and climate variability. Despite this, the long-term trajectories of land degradation in southern Indian coastal systems remain poorly documented. This study employs an integrated geospatial–climatic framework to evaluate multi-decadal Land Use and Land Cover (LULC) dynamics and future projections in the Nagapattinam District, Tamil Nadu. By integrating a Cellular Automata- Weights of Evidence (CA–WoE) model with Normalized Difference Vegetation Index (NDVI) analysis, demographic and climatic datasets, we provide a spatially explicit assessment of landscape transformations. The CA–WoE model yielded an overall accuracy of 83.4% and a kappa coefficient of 0.74, indicating strong agreement between simulated and observed datasets. Our findings reveal a critical shift: agricultural land is projected to decline from 731.79 km2 in 2017 to 481.95 km2 by 2070, while tree cover is expected to diminish from 77.15 to 11.45 km2. These trends are combined by rising thermal stress, with historical maximum temperatures increasing by 0.8 °C (2000–2024) and projected to rise by 2.3 °C by 2100. As the first comprehensive spatial analysis of this southern Indian delta, this research offers a pioneering framework for forecasting land-use transitions. The results provide empirical evidence for Sustainable Development Goals (SDGs 2, 13, 15) and underscore the urgent need for climate-resilient, nature-based solutions to mitigate land deprivation in vulnerable coastal systems globally.
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BibTeX
@article{tharik2026modeling,
title = {{Modeling climate change impacts on coastal land use and vegetation dynamics}},
author = {Mohamed Tharik and Kumaraguru Arumugam and Sai Saraswathi Vijayaraghavalu},
journal = {Scientific Reports},
year = {2026},
month = jul,
doi = {10.1038/s41598-026-54321-6},
url = {https://doi.org/10.1038/s41598-026-54321-6},
note = {CC BY},
}
RIS
TY - JOUR
TI - Modeling climate change impacts on coastal land use and vegetation dynamics
AU - Mohamed Tharik
AU - Kumaraguru Arumugam
AU - Sai Saraswathi Vijayaraghavalu
PY - 2026
DA - 2026/07/01
JO - Scientific Reports
DO - 10.1038/s41598-026-54321-6
UR - https://doi.org/10.1038/s41598-026-54321-6
AB - Coastal deltaic landscapes are increasingly vulnerable to the dual pressures of rapid urbanization and climate variability. Despite this, the long-term trajectories of land degradation in southern Indian coastal systems remain poorly documented. This study employs an integrated geospatial–climatic framework to evaluate multi-decadal Land Use and Land Cover (LULC) dynamics and future projections in the Nagapattinam District, Tamil Nadu. By integrating a Cellular Automata- Weights of Evidence (CA–WoE) model with Normalized Difference Vegetation Index (NDVI) analysis, demographic and climatic datasets, we provide a spatially explicit assessment of landscape transformations. The CA–WoE model yielded an overall accuracy of 83.4% and a kappa coefficient of 0.74, indicating strong agreement between simulated and observed datasets. Our findings reveal a critical shift: agricultural land is projected to decline from 731.79 km2 in 2017 to 481.95 km2 by 2070, while tree cover is expected to diminish from 77.15 to 11.45 km2. These trends are combined by rising thermal stress, with historical maximum temperatures increasing by 0.8 °C (2000–2024) and projected to rise by 2.3 °C by 2100. As the first comprehensive spatial analysis of this southern Indian delta, this research offers a pioneering framework for forecasting land-use transitions. The results provide empirical evidence for Sustainable Development Goals (SDGs 2, 13, 15) and underscore the urgent need for climate-resilient, nature-based solutions to mitigate land deprivation in vulnerable coastal systems globally.
SN - 2045-2322
ER -