Integrating Spatiotemporal Analysis of Land Transformation and Urban Growth in Peshawar Valley and Its Implications on Temperature in Response to Climate Change
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Published:2024-07-03
Issue:7
Volume:13
Page:239
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ISSN:2220-9964
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Container-title:ISPRS International Journal of Geo-Information
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language:en
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Short-container-title:IJGI
Author:
Hussain Muhammad Farooq1, Meng Xiaoliang1, Shah Syed Fahim1, Hussain Muhammad Asif2
Affiliation:
1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China 2. College of Veterinary Sciences and Animal Husbandry, Faculty of Chemical and Life Sciences, Abdul Wali Khan University, Mardan 23200, Pakistan
Abstract
Examining the interconnected dynamics of urbanization and climate change is crucial due to their implications for environmental, social, and public health systems. This study provides a comprehensive analysis of these dynamics in the Peshawar Valley, a rapidly urbanizing region in Khyber Pakhtunkhwa, Pakistan, over a 30-year period (1990–2020). A novel methodological framework integrating remote sensing, GIS techniques, and Google Earth Engine (GEE) was developed to analyze land use/land cover (LULC) changes, particularly the expansion of the built-up environment, along with the land surface temperature (LST) and heat index (HI). This framework intricately links these elements, providing a unique perspective on the environmental transformations occurring in the Peshawar Valley. Unlike previous studies that focused on individual aspects, this research offers a holistic understanding of the complex interplay between urbanization, land use changes, temperature dynamics, and heat index variations. Over three decades, urbanization expanded significantly, with built-up areas increasing from 6.35% to 14.13%. The population surged from 5.3 million to 12.6 million, coupled with significant increases in registered vehicles (from 0.171 million to 1.364 million) and operational industries (from 327 to 1155). These transitions influenced air quality and temperature dynamics, as evidenced by a highest mean LST of 30.30 °C and a maximum HI of 55.48 °C, marking a notable increase from 50.54 °C. These changes show strong positive correlations with built-up areas, population size, registered vehicles, and industrial activity. The findings highlight the urgent need for adaptive strategies, public health interventions, and sustainable practices to mitigate the environmental impacts of urbanization and climate change in the Peshawar Valley. Sustainable urban development strategies and climate change mitigation measures are crucial for ensuring a livable and resilient future for the region. This long-term analysis provides a robust foundation for future projections and policy recommendations.
Funder
National Natural Science Foundation of China
Reference111 articles.
1. Ramzan, M., Saqib, Z.A., Hussain, E., Khan, J.A., Nazir, A., Dasti, M.Y.S., Ali, S., and Niazi, N.K. (2022). Remote sensing-based prediction of temporal changes in land surface temperature and land use-land cover (LULC) in urban environments. Land, 11. 2. Georgati, M., Hansen, H.S., and Keßler, C. (2023). Random Forest Variable Importance Measures for Spatial Dynamics: Case Studies from Urban Demography. ISPRS Int. J. Geo-Inf., 12. 3. Major trends in population growth around the world;Gu;China CDC Wkly.,2021 4. Rural-urban migration in developing countries: Lessons from the literature;Selod;Reg. Sci. Urban Econ.,2021 5. Zhai, H., Lv, C., Liu, W., Yang, C., Fan, D., Wang, Z., and Guan, Q. (2021). Understanding spatio-temporal patterns of land use/land cover change under urbanization in Wuhan, China, 2000–2019. Remote Sens., 13.
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