Forest Cover Change Detection Over North Eastern Ghat Zone of Odisha, India Using Multi-Year Landsat Data

Aims: The current study's objective is to compute the forest cover dynamics using Land Use and Land Cover (LULC) change detection. Place and Duration of Study: North Eastern Ghat Zone (NEGZ) of Odisha, India over 1990 to 2020. Methodology: Through the use of Landsat images and the Supervised & Unsupervised technique of classification, five main categories were established under LULC, viz., Agriculture, Barren Lands, Forest, Settlements, and Water Bodies. Results: The results infer that the forest cover reduced by 20%. On the contrary, the settlements area increased by about 130%. From this we could infer that the expansion of settlements due to population hike is the primary driver of deforestation and forest fragmentation because the population growth and increased settlements accounted for 97% and 93% of the variability in forest cover dynamics, as illustrated by the coefficient of determination (R2 = 0.971** for population and R2 = 0.9271** for settlement areas). Moreover, the LULC classification achieved high accuracy, with an overall accuracy and kappa coefficient of 87.5% and 0.84 respectively. Conclusion: Therefore, by placing special focus on the aforementioned findings, we may conclude that the current study may contribute to research on forest management, climate change mitigation, and sustainable development for emphasizing the critical need to address deforestation and forest fragmentation driven by population growth.

Authors

Institutions

Publication Details

Journal
International Journal of Environment and Climate Change
Published
2024-09-14
DOI
https://doi.org/10.9734/ijecc/2024/v14i94456
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Forest Cover Change Detection Over North Eastern Ghat Zone of Odisha, India Using Multi-Year Landsat Data

Argha Ghosh, Ankit Kumar Meena, Fawaz Parapurath, Rashmirekha Senapati et al.
International Journal of Environment and Climate Change
Remote Sensing in Agriculture
article

Forest Cover Change Detection Over North Eastern Ghat Zone of Odisha, India Using Multi-Year Landsat Data

Argha Ghosh, Ankit Kumar Meena, Fawaz Parapurath, Rashmirekha Senapati, Ritoban Pandit, Bama Shankar Rath, Meera Mahanty
article en

Abstract

Aims: The current study's objective is to compute the forest cover dynamics using Land Use and Land Cover (LULC) change detection. Place and Duration of Study: North Eastern Ghat Zone (NEGZ) of Odisha, India over 1990 to 2020. Methodology: Through the use of Landsat images and the Supervised & Unsupervised technique of classification, five main categories were established under LULC, viz., Agriculture, Barren Lands, Forest, Settlements, and Water Bodies. Results: The results infer that the forest cover reduced by 20%. On the contrary, the settlements area increased by about 130%. From this we could infer that the expansion of settlements due to population hike is the primary driver of deforestation and forest fragmentation because the population growth and increased settlements accounted for 97% and 93% of the variability in forest cover dynamics, as illustrated by the coefficient of determination (R2 = 0.971** for population and R2 = 0.9271** for settlement areas). Moreover, the LULC classification achieved high accuracy, with an overall accuracy and kappa coefficient of 87.5% and 0.84 respectively. Conclusion: Therefore, by placing special focus on the aforementioned findings, we may conclude that the current study may contribute to research on forest management, climate change mitigation, and sustainable development for emphasizing the critical need to address deforestation and forest fragmentation driven by population growth.

International Journal of Environment and Climate ChangeVol. 14(9)
Bidhan Chandra Krishi Viswavidyalaya (IN), Tamil Nadu Agricultural University (IN), Odisha University of Agriculture and Technology (IN)
Openalex Percentile: Top 85%
Remote Sensing in Agriculture
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.

Forest Cover Change Detection Over North Eastern Ghat Zone of Odisha, India Using Multi-Year Landsat Data — Argha Ghosh, Ankit Kumar Meena, et al. · International Journal of Environment and Climate Change (2024) | TGRS Research Map | TGRS