Spatio-Temporal Assessment of Vegetation Response to Climatic Variability Using NDVI and VCI in the Forested Landscape

This study analyzes the spatiotemporal dynamics of vegetation in the forested landscapes of Dindigul and Madurai, Tamil Nadu, India, from 2001 to 2020 using satellite-derived Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), and key meteorological parameters. Results reveal that NDVI has a strong positive correlation with relative humidity ( r = 0.68, P < 0.01), surface pressure ( r = 0.52, P < 0.05), and precipitation ( r = 0.60, P < 0.05), indicating that moisture availability is a major driver of vegetation health. In contrast, elevated temperature and high radiation were linked to reduced NDVI, suggesting vegetation stress under warming conditions. VCI analysis for 2005, 2010, 2015, and 2020 revealed minimal drought-affected areas, indicating strong ecological resilience across the study period. However, a gradual decline in NDVI between 2005 and 2015 reflects growing climate-induced stress on vegetation. The findings underscore the influence of climatic variability on vegetation dynamics and highlight the potential of NDVI and VCI as effective tools for long-term ecosystem monitoring and sustainable forest management.

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Publication Details

Journal
Rangeland Ecology & Management
Published
2026-01-20
DOI
https://doi.org/10.1016/j.rama.2025.12.007
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
31.91
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article

Spatio-Temporal Assessment of Vegetation Response to Climatic Variability Using NDVI and VCI in the Forested Landscape

Eman Rafi Alamery, Somayah Moshrif Alamri, Khadeijah Yahya Faqeih, Elayapillai Periyasami et al.
1 citations
Rangeland Ecology & Management
Remote Sensing in Agriculture
31.91
article

Spatio-Temporal Assessment of Vegetation Response to Climatic Variability Using NDVI and VCI in the Forested Landscape

Eman Rafi Alamery, Somayah Moshrif Alamri, Khadeijah Yahya Faqeih, Elayapillai Periyasami, Mohammad Suhail Meer, Sivaraman Mayan Ayyanar, Chandramohan Karuppiah
article en
1 citations

Abstract

This study analyzes the spatiotemporal dynamics of vegetation in the forested landscapes of Dindigul and Madurai, Tamil Nadu, India, from 2001 to 2020 using satellite-derived Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), and key meteorological parameters. Results reveal that NDVI has a strong positive correlation with relative humidity ( r = 0.68, P < 0.01), surface pressure ( r = 0.52, P < 0.05), and precipitation ( r = 0.60, P < 0.05), indicating that moisture availability is a major driver of vegetation health. In contrast, elevated temperature and high radiation were linked to reduced NDVI, suggesting vegetation stress under warming conditions. VCI analysis for 2005, 2010, 2015, and 2020 revealed minimal drought-affected areas, indicating strong ecological resilience across the study period. However, a gradual decline in NDVI between 2005 and 2015 reflects growing climate-induced stress on vegetation. The findings underscore the influence of climatic variability on vegetation dynamics and highlight the potential of NDVI and VCI as effective tools for long-term ecosystem monitoring and sustainable forest management.

Rangeland Ecology & ManagementVol. 105
Princess Nourah bint Abdulrahman University (SA), Tamil University (IN), Saveetha University (IN), Gandhigram Rural Institute (IN)
Openalex Percentile: Top 2%
Remote Sensing in Agriculture
31.91
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