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Time Series Analyses and Forecasting of Surface Urban Heat Island Intensity Using ARIMA Model in Punjab, Pakistan

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  • Muhammad Sajid Mehmood

    (The College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng 475004, China
    Key Research Institute of Yellow River Civilization and Sustainable Development, Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475004, China
    Center for Computational Geography, The College of Geography and Environmental Science, Henan University, Kaifeng 475004, China)

  • Zeeshan Zafar

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China
    These authors contributed equally to this work.)

  • Muhammad Sajjad

    (Centre for Geo-Computation Studies, Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China)

  • Sadam Hussain

    (Department of Agricultural Extension, Faculty of Crop and Food Sciences, PMAS Arid Agriculture University, Rawalpindi 46000, Pakistan)

  • Shiyan Zhai

    (The College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng 475004, China
    Center for Computational Geography, The College of Geography and Environmental Science, Henan University, Kaifeng 475004, China)

  • Yaochen Qin

    (The College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng 475004, China
    Key Research Institute of Yellow River Civilization and Sustainable Development, Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475004, China)

Abstract

In the context of rapid urbanization, Urban Heat Island (UHI) is considered as a major anthropogenic alteration in Earth environments, and its temporal trends and future forecasts for large areas did not receive much attention. Using land surface temperature (LST) data from MODIS (Moderate Resolution Imaging Spectro-radiometer) for years 2006 to 2020, we quantified the temporal trends of daytime and nighttime surface UHI intensity (SUHII, difference of urban temperature to rural temperature) using the Mann-Kendall (MK) trend test in six major cities of the Punjab province of Pakistan and estimated the future SUHII for the year 2030 using the ARIMA model. Results from the study revealed that the average mean SUHII for daytime was noted as 2.221 °C and the average mean nighttime SUHII was noted as 2.82 °C for the years 2006 to 2020. The average mean SUHII for daytime and nighttime exhibited increasing trends for all seasons and annually, and for the daytime spring season it showed a maximum upward trend of 0.486 °C/year ( p < 0.05) and for the nighttime annual SUHII with an increasing rate of 0.485 °C/year ( p < 0.05) which exhibited a maximum upward trend. The ARIMA model forecast suggested an increase of 0.04 °C in the average daytime SUHII and an increase of 0.1 °C in the average nighttime SUHII until 2030. The results from this study highlight the increasing trends of daytime and nighttime SUHII, ARIMA also forecasted an increase in daytime and nighttime SUHII, suggesting various strategies are needed for an effective mitigation of the UHI effect.

Suggested Citation

  • Muhammad Sajid Mehmood & Zeeshan Zafar & Muhammad Sajjad & Sadam Hussain & Shiyan Zhai & Yaochen Qin, 2022. "Time Series Analyses and Forecasting of Surface Urban Heat Island Intensity Using ARIMA Model in Punjab, Pakistan," Land, MDPI, vol. 12(1), pages 1-20, December.
    • Handle: RePEc:gam:jlands:v:12:y:2022:i:1:p:142-:d:1021933
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    References listed on IDEAS

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