Trends and projections of land use land cover and land surface temperature using an integrated weighted evidence-cellular automata (WE-CA) model

Environ Monit Assess. 2022 Jan 24;194(2):120. doi: 10.1007/s10661-022-09785-0.

Abstract

Land use land cover (LULC) change has become a major concern for biodiversity, ecosystem alteration, and modifying the climatic pattern especially land surface temperature (LST). The present study assessed past and predicted future LULC and LST change in the Swabi District of Pakistan. LULC maps were generated from satellite data for years 1987, 2002, and 2017 using supervised classification. Mean LST and its areal change were estimated for different LULC classes from thermal bands of satellite images. LULC and LST were projected for the year 2047 using the integrated weighted evidence-cellular automata (WE-CA) model and a regression equation developed in this study, respectively. LULC change revealed an increase of > 5% in the built-up while a decrease in the agricultural area by ~ 9%. There was an increase of ~ 63% area in the LST class ≥ 27 °C which may create urban heat island (UHI). Simulation results indicated that the built-up area will further be increased by ~ 3% until 2047. Area associated with LST class > 30 °C indicated a further increase of ~ 38% till 2047 with reference to year 2017. Findings of this study suggested proper utilization of LULC in order to mitigate the creation of UHIs associated with urbanization and built-up areas.

Keywords: Built-up areas and urbanization; Maximum likelihood classification (MLC); Multi-spectral Landsat imageries; Normalized difference vegetation index (NDVI); Transition potential matrix; Urban warming.

MeSH terms

  • Cellular Automata*
  • Cities
  • Ecosystem*
  • Environmental Monitoring
  • Hot Temperature
  • Temperature
  • Urbanization