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Analysis and mapping of present and future drivers of local urban climate using remote sensing: a case of Lahore, Pakistan

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Abstract

Urbanization is the main driver of expanding industry, transport, and buildings at the cost of green spaces in the world’s mega cities. Consequently, an immense land use change is related to local climate modification in urban areas. The process of urbanization in the city of Lahore is posing severe environmental issues such as recent smog events. The objective here is to determine and analyze the spatial variability of land surface temperature (LST) caused by the land use land cover (LULC) change between the year 1996 and 2016 in Lahore in the context of urbanization and, based on this, to predict the land use change and corresponding increase in LST in 2035. To quantify LULC change during the 1996–2016 period, we used supervised maximum likelihood method and ground observations from 400 locations to classify the satellite imagery from the Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) for the years 1996, 2010, and 2016. Moreover, to better understand spatial variability of surface urban heat island (UHI) with the process of urbanization, various indicators were derived from the remote sensing imagery, including the normalized difference vegetation and built-up indices (i.e., NDVI and NDBI, respectively). Moreover, we used an RS-integrated multi-layer perceptron-Markov chain analysis (MLP-MCA) model to predict the LULC change from the year 2016 to 2035 so that the predicted LULC change, as a driver of UHI, can be related to the future local climate of the city. Through relating LST with NDVI and NDBI, we reveal that rapid developments in the residential/infrastructural sectors are causing an immense degradation in the city vegetation areas. The LULC change analyses show that about 9% decrease in green areas during 1996–2016 caused an increase in 6∘C around the built-up areas and an overall difference of 4.8∘C between built-up and nearby sub-urban vegetation areas. Keeping this and MLP-MCA-based predictions for 2035 in view, we conclude that a future 3% decrease in vegetation-covered green areas will approximately cause an increase of 2∘C by 2035. The research output will help the city government and local developers to devise sustainable policies for land use planning and urban development.

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Authors and Affiliations

  1. Institute for Geo-information and Earth Observation (IGEO), PMAS Arid Agriculture University, Rawalpindi, 42000, Pakistan

    Muhammad Imran

  2. Center for Geographical Information Systems, University of the Punjab, Lahore, Pakistan

    Aqsa Mehmood

Authors
  1. Muhammad Imran
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  2. Aqsa Mehmood
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Correspondence to Muhammad Imran.

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Responsible Editor: Zhihua Zhang

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Imran, M., Mehmood, A. Analysis and mapping of present and future drivers of local urban climate using remote sensing: a case of Lahore, Pakistan. Arab J Geosci 13, 278 (2020). https://doi.org/10.1007/s12517-020-5214-2

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  • DOI: https://doi.org/10.1007/s12517-020-5214-2

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