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Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of Lahore district Pakistan

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Abstract

This research aims to assess the urban growth and impact on land surface temperature (LST) of Lahore, the second biggest city in Pakistan. In this research, various geographical information system (GIS) and remote sensing (RS) techniques (maximum likelihood classification (MLC)) LST, and different normalized satellite indices have been implemented to analyse the spatio-temporal trends of Lahore city; by using Landsat for 1990, 2004, and 2018. The development of integrated use of RS and GIS and combined cellular automata–Markov models has provided new means of assessing changes in land use and land cover and has enabled the projection of trajectories into the future. Results indicate that the built-up area and bare area increased from 15,541 (27%) to 23,024 km2 (40%) and 5756 km2 (10%) to 13,814 km2 (24%). Meanwhile, water area and vegetation were decreased from 2302 km2 (4%) to 1151 km2 (2%) and 33,961 km2 (59%) to 19,571 km2 (34%) respectively. Under this urbanization, the LST of the city was also got affected. In 1990, the mean LST of most of the area was between 14 and 28 ℃, which rose to 22–28 ℃ in 2004 and 34 to 36 ℃ in 2018. Because of the shift of vegetation and built-up land, the surface reflectance and roughness of each land use land cover (LULC) class are different. The analysis established a direct correlation between Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI) with LST and an indirect correlation among Soil Adjusted Vegetation Index (SAVI), Normalized Difference Built-up Index (NDBI), and Built-up Index (BI) with LST. The results are important for the planning and development department since they may be used to guarantee the sustainable utilization of land resources for future urbanization expansion projects.

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Data availability

The datasets generated and/or analysed during the current study are not publicly available but from the corresponding author at reasonable request.

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Acknowledgements

We would like to pay extraordinary and heart whelming thanks to NASA-Earth data for providing us Landsat data for analysis. The authors would like to thank Stephen C. McClure for his enthusiastic support and valuable suggestions during the review of the manuscript.

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Authors and Affiliations

  1. Department of Wildlife, Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, 775 Stone Boulevard, Mississippi State, MS, 39762-9690, USA

    Aqil Tariq

  2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, 430079, China

    Aqil Tariq & Xing Zeng

  3. University of Chinese Academy of Sciences (UCAS), Beijing, 101408, China

    Faisal Mumtaz

  4. State Key Laboratory of Remote Sensing Sciences, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China

    Faisal Mumtaz

  5. Department of Botany, University of Gujrat, Hafiz Hayat Campus, Gujrat, Punjab, Pakistan

    Muhammad Majeed

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Contributions

Aqil Tariq and Faisal Mumtaz conducted the overall analysis and led the writing of the manuscript, design, and data analysis. Xing Zheng provided technical inputs for reviewed the paper. Faisal Mumtaz and Muhammad Majeed lend their support to the authors for writing the analysis of Landsat data.

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Correspondence to Aqil Tariq.

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Tariq, A., Mumtaz, F., Majeed, M. et al. Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of Lahore district Pakistan. Environ Monit Assess 195, 114 (2023). https://doi.org/10.1007/s10661-022-10738-w

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