Quantifying Vegetation Cover Change In Ajodhya Hill Forest: A Landsat-Based NDVI Study

Forests are pivotal in providing ecological interconnectedness and essential ecosystem services. In this regard, remote sensing techniques are crucial to depict existing forest resources' original state and nature. NDVI is a preliminary and pilot method for simplifying complex multi-spectral image interpretation. Nowadays, it is the most beneficial and approving lead for vegetation assessment. This study aims to quantify vegetation change coverage in the Ajodhya Hill Forest region, Purulia District, using the Landsat-based Normalized Difference Vegetation Index (NDVI). The present research article focuses on identifying vegetation coverage trends and determining the nature, rate, location, and magnitude of vegetation swaps over 20 years. Our analysis reveals a concerning decline in forest cover, particularly in dense vegetation areas, with simultaneous increases in Sparse and No vegetation categories in this region. Change detection analysis highlights the dynamic nature of forest cover attributed to deforestation, forest logging, tourism development, and policy execution. Our findings underscore the importance of effective forest conservation and management strategies to mitigate further vegetation loss and preserve ecosystem integrity.

Authors

Institutions

Publication Details

Journal
International Journal of Innovative Research in Engineering & Management
Published
2024-12-01
DOI
https://doi.org/10.55524/ijirem.2024.11.6.17
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantifying Vegetation Cover Change In Ajodhya Hill Forest: A Landsat-Based NDVI Study

Saumitra Mukherjee, Rajesh Mandal
International Journal of Innovative Research in Engineering & Management
Land Use and Ecosystem Services
article

Quantifying Vegetation Cover Change In Ajodhya Hill Forest: A Landsat-Based NDVI Study

Saumitra Mukherjee, Rajesh Mandal
article en

Abstract

Forests are pivotal in providing ecological interconnectedness and essential ecosystem services. In this regard, remote sensing techniques are crucial to depict existing forest resources' original state and nature. NDVI is a preliminary and pilot method for simplifying complex multi-spectral image interpretation. Nowadays, it is the most beneficial and approving lead for vegetation assessment. This study aims to quantify vegetation change coverage in the Ajodhya Hill Forest region, Purulia District, using the Landsat-based Normalized Difference Vegetation Index (NDVI). The present research article focuses on identifying vegetation coverage trends and determining the nature, rate, location, and magnitude of vegetation swaps over 20 years. Our analysis reveals a concerning decline in forest cover, particularly in dense vegetation areas, with simultaneous increases in Sparse and No vegetation categories in this region. Change detection analysis highlights the dynamic nature of forest cover attributed to deforestation, forest logging, tourism development, and policy execution. Our findings underscore the importance of effective forest conservation and management strategies to mitigate further vegetation loss and preserve ecosystem integrity.

International Journal of Innovative Research in Engineering & ManagementVol. 11(6)
Sidho-Kanho-Birsha University (IN)
Openalex Percentile: Top 77%
Land Use and Ecosystem Services
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Quantifying Vegetation Cover Change In Ajodhya Hill Forest: A Landsat-Based NDVI Study — Saumitra Mukherjee, Rajesh Mandal · International Journal of Innovative Research in Engineering & Management (2024) | TGRS Research Map | TGRS