Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987-2015)

被引:191
|
作者
Estoque, Ronald C. [1 ]
Murayama, Yuji [2 ]
机构
[1] Natl Inst Environm Studies, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan
[2] Univ Tsukuba, Fac Life & Environm Sci, 1-1-1 Tennodai, Tsukuba, Ibaraki 3058572, Japan
基金
日本学术振兴会;
关键词
Urban heat island; Land surface temperature; Remote sensing; Impervious surface; Green space; Baguio City; SERVICE VALUE CHANGES; LANDSCAPE PATTERN; AIR-TEMPERATURE; IMPERVIOUS SURFACE; SPATIAL-PATTERN; VEGETATION; COVER; IMPACTS; CONFIGURATION; BAGUIO;
D O I
10.1016/j.isprsjprs.2017.09.008
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Since it was first described about two centuries ago and due to its adverse impacts on urban ecological environment and the overall livability of cities, the urban heat island (UHI) phenomenon has been, and still is, an important research topic across various fields of study. However, UHI studies on cities in mountain regions are still lacking. This study aims to contribute to this endeavor by monitoring and examining the formation of surface UHI (SUHI) in a tropical mountain city of Southeast Asia-Baguio City, the summer capital of the Philippines- using Landsat data (1987-2015). Based on mean surface temperature difference between impervious surface (IS) and green space (GS1), SUHI intensity (SUHII) in the study area increased from 2.7 degrees C in 1987 to 3.4 degrees C in 2015. Between an urban zone (>86% impervious) and a rural zone (<10% impervious) along the urban-rural gradient, it increased from 4.0 degrees C in 1987 to 8.2 degrees C in 2015. These results are consistent with the rapid urbanization of the area over the same period, which resulted in a rapid expansion of impervious surfaces and substantial loss of green spaces. Together with landscape composition variables (e.g. fraction of IS), topographic variables (e.g. hillshade) can help explain a significant amount of spatial variations in surface temperature in the area (R-2 = 0.56-0.85) (p < 0.001). The relative importance of the 'fraction of IS' variable also increased, indicating that its unique explanatory and predictive power concerning the spatial variations of surface temperature increases as the city size becomes bigger and SUHI gets more intense. Overall, these results indicate that the cool temperature of the study area being situated in a mountain region did not hinder the formation of SUHI. Thus, the formation and effects of UHIs, including possible mitigation and adaptation measures, should be considered in landscape planning for the sustainable urban development of the area. (C) 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:18 / 29
页数:12
相关论文
共 50 条
  • [41] SPATIO-TEMPORAL ANALYSIS OF SURFACE URBAN HEAT ISLAND BASED ON LANDSAT ETM plus AND OLI/TIRS IMAGERY IN THE CITY OF KOSICE, SLOVAKIA
    Onacillova, Katarina
    Gallay, Michal
    CARPATHIAN JOURNAL OF EARTH AND ENVIRONMENTAL SCIENCES, 2018, 13 (02): : 395 - 408
  • [42] The Effects of Land Indices on Thermal State in Surface Urban Heat Island Formation: A Case Study on Agra City in India Using Remote Sensing Data (1992-2019)
    Pathak, Chandan
    Chandra, Subhanshu
    Maurya, Gaurav
    Rathore, Aditya
    Sarif, Md. Omar
    Gupta, Rajan Dev
    EARTH SYSTEMS AND ENVIRONMENT, 2021, 5 (01) : 135 - 154
  • [43] Analyzing the Urban Heat Island Using Time Series Land Surface Temperature (LST) data
    Wang, Weimin
    Liang, Hong
    Yang, Lijun
    Liu, Kai
    Su, Hongbo
    Li, Xueke
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 5874 - 5876
  • [44] Using Landsat 8 data to compare percent impervious surface area and normalized difference vegetation index as indicators of urban heat island effects in Connecticut, USA
    Zhiyuan Yang
    Chandi Witharana
    James Hurd
    Kao Wang
    Runmei Hao
    Siqin Tong
    Environmental Earth Sciences, 2020, 79
  • [45] Thermal comfort conditions at microclimate scale and surface urban heat island in a tropical city: A study on Joao Pessoa city, Brazil
    e Silva, Regiane de Souza
    da Silva, Richarde Marques
    de Freitas, Anne Falcao
    dos Santos, Joel Silva
    Guimaraes Santos, Celso Augusto
    Viana de Lima, Eduardo Rodrigues
    INTERNATIONAL JOURNAL OF BIOMETEOROLOGY, 2022, 66 (06) : 1079 - 1093
  • [46] ARIMA modeling for forecasting land surface temperature and determination of urban heat island using remote sensing techniques for Chennai city, India
    Kesavan R.
    Muthian M.
    Sudalaimuthu K.
    Sundarsingh S.
    Krishnan S.
    Arabian Journal of Geosciences, 2021, 14 (11)
  • [47] A Remote Sensing Approach for Surface Urban Heat Island Modeling in a Tropical Colombian City Using Regression Analysis and Machine Learning Algorithms
    Garzon, Julian
    Molina, Inigo
    Velasco, Jesus
    Calabia, Andres
    REMOTE SENSING, 2021, 13 (21)
  • [48] Measuring the Urban Land Surface Temperature Variations Under Zhengzhou City Expansion Using Landsat-Like Data
    Yang, Haibo
    Xi, Chaofan
    Zhao, Xincan
    Mao, Penglei
    Wang, Zongmin
    Shi, Yong
    He, Tian
    Li, Zhenhong
    REMOTE SENSING, 2020, 12 (05)
  • [49] Spatio-temporal Assessment of Urban Heat Island Effects in Kuala Lumpur Metropolitan City Using Landsat Images
    Yusuf Ahmed Yusuf
    Biswajeet Pradhan
    Mohammed O. Idrees
    Journal of the Indian Society of Remote Sensing, 2014, 42 : 829 - 837
  • [50] Thermal comfort conditions at microclimate scale and surface urban heat island in a tropical city: A study on João Pessoa city, Brazil
    Regiane de Souza e Silva
    Richarde Marques da Silva
    Anne Falcão de Freitas
    Joel Silva dos Santos
    Celso Augusto Guimarães Santos
    Eduardo Rodrigues Viana de Lima
    International Journal of Biometeorology, 2022, 66 : 1079 - 1093