Impacts of Grading Rule on Urban Thermal Landscape Pattern Research
Wei Zhang and
Feng Chen
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Wei Zhang: School of Geographical Sciences, Southwest University, Chongqing 400715, China
Feng Chen: Zhejiang Institute of Meteorological Sciences, Hangzhou 310008, China
Sustainability, 2018, vol. 10, issue 7, 1-16
Abstract:
The thermodynamic landscape method is becoming a more popular approach for urban heat island research with the development of remote sensing technology. However, a limited amount of research discusses the theoretical and methodological issues of this method. This paper analyzed the reliability and stability of the results of thermal landscape pattern analysis with six different grading rules through surface temperature retrieval, landscape pattern analysis, and Geographic Information System (GIS) spatial analysis. The results demonstrate the following points. (1) The six grading methods can be categorized into two types: pixel number methods and temperature range methods. The grading results of the two kinds of methods lack comparability, whereas the grading results within one kind of method have high comparability. The temperature range methods have good consistency. The average value of the consistency indices (Si) of thermal landscape levels reaches up to 81.55%. The anomaly temperature method and standard deviation method are recommended for future research. (2) The grading rule significantly affects the stability of landscape indices, and its average variation coefficient reaches up to 22.36%. The authors suggest the use of landscape indices that have strong stability, such as shape index and landscape division index, in future research. (3) The results of the sensitivity analysis show that the change of the temperature range of thermal landscape levels affects landscape indices slightly, whereas the effect of the change of the level number of thermal landscapes on landscape indices is intense. The authors suggest categorizing the thermal landscape into six levels in future research in order to enhance the consistency and comparability among case studies.
Keywords: grading rule; sensitivity; stability; thermal landscape; Hangzhou (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)
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