Land use land cover and land surface temperature changes and their relationship with human modification in Islamabad Capital Territory, Pakistan

• Published in: Brazilian journal of biology 2024, Vol.84, p.e281700
• Main Authors: Ullah, W, Ullah, S, Bräuning, A, Javed, M F, Subhanullah, M, Abdullah, M, Sajjad, R U, Ullah, R, Rahman, A
• Format: Article
• Language: English
• Subjects: Agriculture; BIOLOGY; Environmental Monitoring - methods; global human modification; Human Activities; Humans; land surface temperature; land use land cover; maximum likelihood classification; Pakistan; Satellite Imagery; Temperature; urban heat island; Urbanization
• ISSN: 1519-6984; 1678-4375; 1678-4375
• DOI: 10.1590/1519-6984.281700

Human activities are altering the existing patterns of Land Use Land Cover (LULC) and Land Surface Temperature (LST) on a global scale. However, long-term trends of LULC and LST are largely unknown in many remote mountain areas such as the Karakorum. . The objective of our study therefore was to evaluate the historical changes in land use and land cover (LULC) in an alpine environment located in Islamabad Capital Territory, Pakistan. We used Landsat satellite pictures (namely Landsat 5 TM and Landsat 8 OLI) from the years 1988, 2002, and 2016 and applied the Maximum Likelihood Classification (MLC) approach to categorize land use classes. Land Surface Temperatures (LST) were calculated using the thermal bands (6, 10, and 11) of Landsat series data. The correlation between the Human Modification Index (HMI) and LULC as well as LST was evaluated by utilizing data from Google Earth Engine (GEE). Over the study period, the urbanized area increased by 9.94%, whilst the agricultural and bare soil areas decreased by 3.81% and 3.94%, respectively. The findings revealed a significant change in the LULC with a decrease of 1.99% in vegetation. The highest LST class exhibited a progressive trend, with an increase from 12.27% to 48.48%. Based on the LST analysis, the built-up area shows the highest temperature, followed by the barren, agricultural, and vegetation categories. Similarly, the HMI for different LST categories indicates that higher LST categories have higher levels of human alteration compared to lower LST categories, with a strong correlation (R-value = 0.61) between HMI and LST. The findings can be utilized to promote sustainable urban management and for biodiversity conservation efforts. The work also has the potential of utilizing it to protect delicate ecosystems from human interference and to formulate strategies and regulations for sustainable urban growth, including aspects of land utilization and zoning, reduction of urban heat stress, and urban infrastructure.