Evaluating Vegetation Dynamics through Multiple Vegetation Indices: An Integrated Study of CTVI, DVI, and NDVI in Pen Tehsil

This study presents a comprehensive analysis of vegetation dynamics in a selected region, utilizing three different vegetation indices: the Corrected Transformed Vegetation Index (CTVI), Difference Vegetation Index (DVI), and Normalized Difference Vegetation Index (NDVI). The analysis focuses on the spatial distribution and classification of vegetation cover over multiple years using remote sensing data. The study evaluates the variations in the indices across different classes of vegetation, highlighting their efficiency in capturing changes in vegetation health and density. Results show that each index presents unique strengths in capturing vegetation dynamics, with CTVI proving effective in identifying subtle shifts in vegetation cover, while DVI and NDVI exhibit more distinct thresholds for vegetation classification. This paper aims to enhance the understanding of vegetation patterns and their response to environmental factors, contributing to more accurate land-use and land-cover classification models.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-10
DOI
https://doi.org/10.5281/zenodo.15279134
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Evaluating Vegetation Dynamics through Multiple Vegetation Indices: An Integrated Study of CTVI, DVI, and NDVI in Pen Tehsil

Zenodo (CERN European Organization for Nuclear Research)
Remote Sensing in Agriculture
article

Evaluating Vegetation Dynamics through Multiple Vegetation Indices: An Integrated Study of CTVI, DVI, and NDVI in Pen Tehsil

article en

Abstract

This study presents a comprehensive analysis of vegetation dynamics in a selected region, utilizing three different vegetation indices: the Corrected Transformed Vegetation Index (CTVI), Difference Vegetation Index (DVI), and Normalized Difference Vegetation Index (NDVI). The analysis focuses on the spatial distribution and classification of vegetation cover over multiple years using remote sensing data. The study evaluates the variations in the indices across different classes of vegetation, highlighting their efficiency in capturing changes in vegetation health and density. Results show that each index presents unique strengths in capturing vegetation dynamics, with CTVI proving effective in identifying subtle shifts in vegetation cover, while DVI and NDVI exhibit more distinct thresholds for vegetation classification. This paper aims to enhance the understanding of vegetation patterns and their response to environmental factors, contributing to more accurate land-use and land-cover classification models.

Zenodo (CERN European Organization for Nuclear Research)
G.S. Science, Arts And Commerce College (IN)
Life in Land
Openalex Percentile: Top 51%
Remote Sensing in Agriculture
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Evaluating Vegetation Dynamics through Multiple Vegetation Indices: An Integrated Study of CTVI, DVI, and NDVI in Pen Tehsil · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS