ArticleScientific reports2025
Examining the landscape transformation and temperature dynamics in Pakistan.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Improvements in sustainable energy utilization in global urban areas: Insights from remote sensing surveys.iScience · 2026Article
- Modeling evapotranspiration in diverse climatic zones of Pakistan using Surface Energy Balance Algorithm for Land (SEBAL) through geospatial technologies.Scientific reports · 2026Article
- Advanced satellite-based remote sensing and data analytics for precision water resource management and agricultural optimization.Scientific reports · 2025Article
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6 authors.
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Abstract
This study aims to examine the landscape transformation and temperature dynamics using multiple spectral indices. The processes of temporal fluctuations in the land surface temperature is strongly related to the morphological features of the area in which the temperature is determined, and the given factors significantly affect the thermal properties of the surface. This research is being conducted in Pakistan to identify the vegetation cover, water bodies, impervious surfaces, and land surface temperature using decadal remote sensing data with four intervals during 1993-2023 in the Mardan division, Khyber Pakhtunkhwa. To analyze the landscape transformation and temperature dynamics, the study used spectral indices including Land Surface Temperature, Normalized Difference Vegetation Index, Normalized Difference Water Index, Normalized Difference Built-up Index, and Normalized Difference Bareness Index by employing Google Earth Engine cloud computing platform. The results suggest that there are differences in the type of land surface temperature, ranging from 15.58 °C to 43.71 °C during the study period. Nevertheless, larger fluctuations in land surface temperature were found in the cover and protective forests of the study area, especially in the northwestern and southeastern parts of the system. These results highlighted the complexity of the relationship between land surface temperature and spectral indices regarding the need for spectral indices.
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