Land-Use/Land Cover Changes Contribute to Land Surface Temperature: A Case Study of the Upper Indus Basin of Pakistan

Abstract

Land-use/land cover (LULC) changes have an impact on land surface temperature (LST) at the local, regional, and global scales. To simulate the LULC and LST changes of the environmentally important area of northern Pakistan, this research focused on spatio-temporal LULC and associated LST changes since 1987 and made predictions to 2047. We classified LULC from Landsat TM and ETM data, using the maximum probability supervised categorization approach. LST was retrieved using the Radiative Transfer Equation (RTE) methodology. Furthermore, we simulated LULC using the integrated approaches of Cellular Automata (CA) and Weighted Evidence (WE) and used a regression model to predict LST. The built-up areas and vegetation have increased by 2.1% and 11% due to a decline in the barren land by −8.5% during the last 30 years. The LULC is expected to increase, particularly the built-up and vegetation classes by 2.74% and 13.66%, respectively, and the barren land would decline by −4.2% by 2047. Consequently, the higher LST classes (i.e., 27 °C to <30 °C and ≥30 °C) soared up by about 25.18% and 34.26%, respectively, during the study period, which would further expand to 30.19% and 14.97% by 2047. The lower LST class (i.e., 12 °C to <21 °C) indicated a downtrend of about −41.29% and would further decrease to −3.13% in the next 30 years. The study findings are useful for planning and management, especially for climatologists, land-use planners, and researchers in sustainable land use with rapid urbanization.

An Investigation of the Impact of Spatiotemporal Changes of Land Use and Land Cover and Land Surface Temperature Using RS Techniques for Selected Cities in Sri Lanka

“…In this study, all bands were employed, especially the thermal bands, which are frequently used to diagnose LST. The surface temperature may be calculated using Landsat data, which are also often used for assessments of changes in LULC (Dissanayake et al, 2019a;Majeed et al, 2021;Rehman et al, 2022;Shamsudeen et al, 2022). The USGS-provided Landsat level 2 data that have been radiometrically calibrated and atmospherically adjusted, have been analyzed in this study using various functions.…”

Effects of Rising Urban Temperatures on the Wellbeing of the Residents:

“…Derdouri, Wang et al (2021) analysed several case studies conducted between 2001 to 2020 to identify a significant rise in SUHI (surface urban heat island) owing to the modifications in the landuse of the cities. Several other studiesreported a close relationship between landscape modification in terms of increased impervious urban surfaces (on the cost of blue-green infrastructure) and rising LST over the cities across the globe (Adeyeri, Akinsanola et al, 2017;Ahmed, Kamruzzaman et al, 2013;Chandra, Sharma et al, 2018;Daramola, Eresanya et al, 2018;Hale, Gallo et al, 2006;Huang and Lin, 2013;Imran, Hossain et al, 2021;Jun, Kim et al, 2017;Kottmeier, Biegert et al, 2007;Lu, Yue et al, 2021;Pal and Ziaul, 2017;Rehman, Qin et al, 2022;Tran, Pla et al, 2017). Heatwaves are triggered by these changes in urban landscape pattern and LST, which further exacerbates the phenomena of urban heat island (UHI).…”

Spatial prediction of the urban inter-annual land surface temperature variability: An integrated modeling approach in a rapidly urbanizing semi-arid region

“…In this case, Khan et al (2022) predicted future LULC and LST changes in the Swabi District of Pakistan using an integrated weighted cellular automata (CA) model, finding that appropriate allocation of LULC classes might alleviate the creation of UHis associated with urbanization and built-up areas. Rehman et al (2022) analyzed a time-series LULC and its associated LST changes using a combination of remote sensing, statistical methods, and the spatial CA model. They found that urban area expansion is the primary cause of increased LST in urban areas.…”