Monitoring the Interannual Spatiotemporal Changes in the Land Surface Thermal Environment in Both Urban and Rural Regions from 2003 to 2013 in China Based on Remote Sensing
Yuanzheng Li
School of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450046, China huel.edu.cn
Academician Laboratory for Urban and Rural Spatial Data Mining of Henan Province, Henan University of Economics and Law, Zhengzhou 450046, China huel.edu.cn
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China cas.cn
Search for more papers by this authorCorresponding Author
Lan Wang
Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China cas.cn
Search for more papers by this authorLiping Zhang
Center for Environmental Zoning, Chinese Academy for Environmental Planning, Ministry of Environmental Protection of China, Beijing 100012, China mep.gov.cn
Search for more papers by this authorQing Wang
Guangdong Key Laboratory of Sugarcane Improvement and Biorefinery, Guangdong Provincial Bioengineering Institute (Guangzhou Sugarcane Industry Research Institute), Guangzhou, China
Search for more papers by this authorYuanzheng Li
School of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450046, China huel.edu.cn
Academician Laboratory for Urban and Rural Spatial Data Mining of Henan Province, Henan University of Economics and Law, Zhengzhou 450046, China huel.edu.cn
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China cas.cn
Search for more papers by this authorCorresponding Author
Lan Wang
Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China cas.cn
Search for more papers by this authorLiping Zhang
Center for Environmental Zoning, Chinese Academy for Environmental Planning, Ministry of Environmental Protection of China, Beijing 100012, China mep.gov.cn
Search for more papers by this authorQing Wang
Guangdong Key Laboratory of Sugarcane Improvement and Biorefinery, Guangdong Provincial Bioengineering Institute (Guangzhou Sugarcane Industry Research Institute), Guangzhou, China
Search for more papers by this authorAbstract
The thermal environment is closely related to human well-being. Diurnal and seasonal variations in surface urban heat islands (SUHIs) have been extensively studied. Nevertheless, interannual changes in SUHIs as well as in land surface temperatures (LSTs) in cities and their corresponding villages remain poorly understood, particularly using data from several continuous years to analyse change rates and corresponding significance levels. Using Aqua/Terra moderate resolution imaging spectroradiometer (MODIS) data for 2003–2013, we explored not only the interannual changes in annual and seasonal mean LSTs in rural and urban regions which were identified based on modified criteria, but also the SUHI intensities (SUHIIs) for these cities. The results showed that most of LSTs and SUHIIs did not change significantly (p ≥ 0.05). Their changes exhibited clear spatiotemporal agglomeration and variation laws. The rural region LST change rates, which exhibited significant changes, were generally highest in the summer, with most of values of 0.1–0.5°C (yr−1) during the daytime across China, except for the Xinjiang autonomous regions, and 0.1–0.2°C (yr−1) during the night-time. The rates were lowest in the winter, with most of values of −0.4 to −0.1°C (yr−1). The rates of daytime SUHIIs with significant changes were generally highest in the summer, with most of values of 0.1–0.3°C (yr−1), and lowest in the winter, even with most of values of −0.4 to −0.1°C (yr−1) in northern central China. During the night-time, most of rates were 0.0–0.1°C (yr−1). In China, most of the changes in the surface thermal environment were harmful to humans at both large national and local urban scales. The changes could lower thermal comfort levels, harm human health, affect human reproduction rates and lives, and increase the energy consumed for refrigeration or heating, thereby increase emissions of greenhouse gases.
Open Research
Data Availability
The digital elevation data were taken from http://westdc.westgis.ac.cn/data/92bb3089-cc0c-46d2-908d-aae810ef064e. The LST data were downloaded from http://www.gscloud.cn/. The land use data were provided by http://www.resdc.cn/. The impervious percentage data were provided by https://www.beijingcitylab.com/. The other data used to support the findings of this study are available from the corresponding author upon request.
Supporting Information
Filename | Description |
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adme8347659-sup-0001-f1.pdfPDF document, 619.1 KB | Supplementary Materials The following supporting information is available as part of the online article. Figure S1: the percentages of reference rural regions whose annual and seasonal variation rates of mean LSTs significantly changed during both the daytime and night-time from 2003 to 2013 in the five environmental regions of China. Figure S2: the percentages of reference rural regions whose annual and seasonal variation rates of mean LSTs significantly positively changed during both the daytime and night-time from 2003 to 2013 in the five environmental regions of China. Figure S3: the percentages of urban regions whose annual and seasonal variation rates of mean LSTs significantly changed during both the daytime and night-time from 2003 to 2013 in the five environmental regions of China. Figure S4: the percentages of urban regions whose annual and seasonal variation rates of mean LSTs significantly positively changed during both the daytime and night-time from 2003 to 2013 in the five environmental regions of China. Figure S5: the percentages of cities whose annual and seasonal variation rates of mean SUHIIs significantly changed during both the daytime and night-time from 2003 to 2013 in the five environmental regions of China. Figure S6: the percentages of cities whose annual and seasonal variation rates of mean SUHIIs significantly positively changed during the daytime and night-time, and differences between the daytime and night-time rates from 2003 to 2013 in the five environmental regions of China. Table S1: typical monitoring indicators of SUHIIs. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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