Spatiotemporal Assessment of Land Use Land Cover Change Detection and Normalized Difference Vegetation Index in Desert Area

This study examines the spatiotemporal changes in land use land cover (LULC) from 1990 to 2023 in the Islamkot subdistrict of Tharparkar, Pakistan, an area known for its vast coal reserves and environmental challenges. A change detection analysis was performed using the maximum likelihood supervised classification method, and a Normalized Difference Vegetation Index (NDVI) analysis was conducted to evaluate vegetation variations. The findings indicate significant changes in land cover patterns: settlement, vegetation, water bodies, and mining areas increased by approximately 3.02%, 20.2%, 3.8%, and 0.9%, respectively, while bare land decreased by 27.9%. The primary drivers of these changes were identified as mining activities and precipitation variations. These results provide a foundation for informed land use planning , conservation efforts, and regional sustainable development strategies.

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Publication Details

Journal
Rangeland Ecology & Management
Published
2025-06-07
DOI
https://doi.org/10.1016/j.rama.2025.03.008
Citations
3
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
3.90
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article

Spatiotemporal Assessment of Land Use Land Cover Change Detection and Normalized Difference Vegetation Index in Desert Area

Imran Aziz Tunio, Love Kumar, Abdul Ahad Abro, Sheeraz Memon et al.
3 citations
Rangeland Ecology & Management
Remote Sensing and Land Use
3.90
article

Spatiotemporal Assessment of Land Use Land Cover Change Detection and Normalized Difference Vegetation Index in Desert Area

Imran Aziz Tunio, Love Kumar, Abdul Ahad Abro, Sheeraz Memon, Jaten Kumar, Habibullah Abbasi, Muhammad Abdullah Tunio, Abdul Rehman Tunio
article en
3 citations

Abstract

This study examines the spatiotemporal changes in land use land cover (LULC) from 1990 to 2023 in the Islamkot subdistrict of Tharparkar, Pakistan, an area known for its vast coal reserves and environmental challenges. A change detection analysis was performed using the maximum likelihood supervised classification method, and a Normalized Difference Vegetation Index (NDVI) analysis was conducted to evaluate vegetation variations. The findings indicate significant changes in land cover patterns: settlement, vegetation, water bodies, and mining areas increased by approximately 3.02%, 20.2%, 3.8%, and 0.9%, respectively, while bare land decreased by 27.9%. The primary drivers of these changes were identified as mining activities and precipitation variations. These results provide a foundation for informed land use planning , conservation efforts, and regional sustainable development strategies.

Rangeland Ecology & ManagementVol. 101
University of Sindh (PK), NED University of Engineering and Technology (PK), University of Illinois Urbana-Champaign (US), Mehran University of Engineering and Technology (PK), Iqra University (PK), Government of Pakistan (PK), Institute of Business Management (PK), Illinois Archaeological Survey (US)
Climate action
Openalex Percentile: Top 7%
Remote Sensing and Land Use
3.90
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Spatiotemporal Assessment of Land Use Land Cover Change Detection and Normalized Difference Vegetation Index in Desert Area — Imran Aziz Tunio, Love Kumar, et al. · Rangeland Ecology & Management (2025) | TGRS Research Map | TGRS