Assessing forest fragmentation due to land use changes from 1992 to 2023: A spatio-temporal analysis using remote sensing data
Khadim Hussain,
Kaleem Mehmood,
Shoaib Ahmad Anees,
Zhidan Ding,
Sultan Muhammad,
Tariq Badshah,
Fahad Shahzad,
Ijlal Haidar,
Abdul Wahab,
Jamshid Ali,
Mohammad Javed Ansari,
Saleh H. Salmen,
Sun Yujun,
Waseem Razzaq Khan
Affiliations
Khadim Hussain
State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing, 100083, China
Kaleem Mehmood
Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing, 100083, China; Institute of Forest Science, University of Swat, Main Campus Charbagh 19120, Swat, Pakistan
Shoaib Ahmad Anees
Department of Forestry, The University of Agriculture, Dera Ismail Khan, 29050, Pakistan; Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning, 530001, China
Zhidan Ding
State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing, 100083, China
Sultan Muhammad
Institute of Forest Science, University of Swat, Main Campus Charbagh 19120, Swat, Pakistan; Department of Forestry and Wildlife, Faculty of Physical & Applied Sciences, University of Haripur, Pakistan
Tariq Badshah
State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing, 100083, China
Fahad Shahzad
Mapping and 3S Technology Center, Beijing Forestry University, Beijing, 100083, China
Ijlal Haidar
State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing, 100083, China; Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing, 100083, China
Abdul Wahab
Department of Forestry and Range Management, Arid Agriculture University Rawalpindi, Pakistan
Jamshid Ali
Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing, 100083, China
Mohammad Javed Ansari
Department of Botany, Hindu College Moradabad (Mahatma Jyotiba Phule Rohilkhand University Bareilly), 244001, India
Saleh H. Salmen
Department of Botany and Microbiology, College of Science, King Saud University, PO Box -2455, Riyadh, 11451, Saudi Arabia
Sun Yujun
State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing, 100083, China; Corresponding author.
Waseem Razzaq Khan
Department of Forestry Science and Biodiversity, Faculty of Forestry and Environment, Universiti Putra Malaysia UPM, Serdang, 43400, Selangor, Malaysia; Advanced Master in Sustainable Blue Economy, National Institute of Oceanography and Applied Geophysics - OGS, University of Trieste, Trieste, 34127, Italy; Institut Ekosains Borneo (IEB), Universiti Putra Malaysia Bintulu Campus, Sarawak, 97008, Malaysia; Corresponding author. State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing, 100083, China.
The increasing pressures of urban development and agricultural expansion have significant implications for land use and land cover (LULC) dynamics, particularly in ecologically sensitive regions like the Murree and Kotli Sattian tehsils of the Rawalpindi district in Pakistan. This study's primary objective is to assess spatial variations within each LULC category over three decades (1992–2023) using cross-tabulation in ArcGIS to identify changes in LULC and investigates into forest fragmentation analysis using the Landscape Fragmentation Tool (LFTv2.0) to classify forest into several classes such as patch, edge, perforated, small core, medium core, and large core. Utilizing remote sensing data from Landsat 5 and Landsat 9 satellites, the research focuses on the temporal dynamics in various land classes including Coniferous Forest (CF), Evergreen Forest (EF), Arable Land (AR), Buildup Area (BU), Barren Land (BA), Water (WA), and Grassland (GL). The Support Vector Machine (SVM) classifier and ArcGIS software were employed for image processing and classification, ensuring accuracy in categorizing different land types. Our results indicate a notable reduction in forested areas, with Coniferous Forest (CF) decreasing from 363.9 km2, constituting 45.0 % of the area in 1992, to 291.5 km2 (36.0 %) in 2023, representing a total decrease of 72.4 km2. Similarly, Evergreen Forests have also seen a significant reduction, from 177.9 km2 (22.0 %) in 1992 to 99.8 km2 (12.3 %) in 2023, a decrease of 78.1 km2. The study investigates into forest fragmentation analysis using the Landscape Fragmentation Tool (LFTv2.0), revealing an increase in fragmentation and a decrease in large core forests from 20.3 % of the total area in 1992 to 7.2 % in 2023. Additionally, the patch forest area increased from 2.4 % in 1992 to 5.9 % in 2023, indicating significant fragmentation. Transition matrices and a Sankey diagram illustrate the transitions between different LULC classes, providing a comprehensive view of the dynamics of land-use changes and their implications for ecosystem services. These findings highlight the critical need for robust conservation strategies and effective land management practices. The study contributes to the understanding of LULC dynamics and forest fragmentation in the Himalayan region of Pakistan, offering insights essential for future land management and policymaking in the face of rapid environmental changes.
