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Spatio-temporal Analysis of Urban Heat Island and Heat Wave Evolution using Time-series Remote Sensing Images: Method and Applications

Yang, Bo
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1552398782461458

Abstract Details

2019, PhD, University of Cincinnati, Arts and Sciences: Geography.
With the rapid advance in remote sensing technology and the continuous improvement in ground-based observation devices, the recent decade has witnessed a tremendous growth in the collection of spatio-temporal data about the Earth’s environment. Thermal infrared (TIR) remote sensing provides an effective tool for mapping land surface temperature (LST), which is a useful parameter for modelling the urban heat island (UHI) and heat wave (HW) and evaluating anthropogenic influences on climate change. Unfortunately, no single satellite system provides the thermal measurements at both high spatial and high temporal resolution. Polar orbiting satellite systems like MODIS provide daily thermal data at a moderate spatial resolution (1 km). Landsat and ASTER satellite systems can acquire thermal data at relatively high spatial resolution (120 m for Landsat TM, 60 m for Landsat ETM+, 100 m for Landsat-8 TIRS, 90 m for ASTER) but with temporally infrequent coverage (16 day revisit for both Landsat and ASTER). In this study, A ST-Cokriging method was formulated and implemented for blending spatio-temporal data sets acquired by multi-source remote sensing systems. The ST-Cokriging method extends traditional Cokriging method from a solely spatial domain to a spatio-temporal domain, therefore exploiting not merely spatial covariance structure but also temporal covariance and spatio-temporal cross-covariance structures in the fusion computation. The application examples demonstrate that our method can e?ectively ?ll in data gaps (holes) caused by clouds and generate reliable results at both high spatial resolution and high temporal frequency. The ST-Cokriging method was utilized to enhance the time-series LST product from MODIS thermal remote sensing. In the first application, the ST-Cokriging method was used to enhance MODIS LST data. Based on the enhanced MODIS Terra (morning) and Aqua (afternoon) LST time series, we evaluated the impact of traffic volume on spatial extent and intensity of the UHI in the Beijing metropolitan area. In the second application, the daily MODIS thermal remote sensing data sharpened by ST-cokriging method are used to investigate heat wave phenomena. Given the global warming trend, it is expected that the frequency, severity, intensity and spatial extent of heat waves will increase worldwide in the future. It is anticipated that the detailed information about the start date, end date, duration, intensity, spatial extent, expansion, contraction and movement of the heat wave event derived from our method would be useful for issuing heat advisories, watches, and warnings and in developing heat wave response plans to reduce the heat-related illness, mortality and economic loss.
Hongxing Liu, Ph.D. (Committee Chair)
Richard Beck, Ph.D. (Committee Member)
Kenneth Hinkel, Ph.D. (Committee Member)
Emily Kang, Ph.D. (Committee Member)
Susanna Tong, Ph.D. (Committee Member)
118 p.
Geographic Information Science
Spatio-temporal data fusion; global warming; urban heat island; heat wave; object-oriented modelling

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Citations

  • Yang, B. (2019). Spatio-temporal Analysis of Urban Heat Island and Heat Wave Evolution using Time-series Remote Sensing Images: Method and Applications [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1552398782461458

    APA Style (7th edition)

  • Yang, Bo. Spatio-temporal Analysis of Urban Heat Island and Heat Wave Evolution using Time-series Remote Sensing Images: Method and Applications. 2019. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1552398782461458.

    MLA Style (8th edition)

  • Yang, Bo. "Spatio-temporal Analysis of Urban Heat Island and Heat Wave Evolution using Time-series Remote Sensing Images: Method and Applications." Doctoral dissertation, University of Cincinnati, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1552398782461458

    Chicago Manual of Style (17th edition)

ucin1552398782461458
183
© 2018, some rights reserved.Creative Commons License Spatio-temporal Analysis of Urban Heat Island and Heat Wave Evolution using Time-series Remote Sensing Images: Method and Applications by Bo Yang is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Cincinnati and OhioLINK.