Investigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands

In the process of studying the spatiotemporal cause mechanism of urban heat island (UHI) effects, the classification method used will directly affect the robustness of urban surface heat classification. Applying five commonly used standard classification methods, we divided Beijing's urba...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yingshuang Lu, Tong He, Xinliang Xu, Zhi Qiao
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST) robustness standard classification method urban heat island (UHI) effect urban thermal grades Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809
Acceso en línea:	https://doaj.org/article/2a52b3e2e01b4229b76eb1f53a106830
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:2a52b3e2e01b4229b76eb1f53a106830
record_format	dspace
spelling	oai:doaj.org-article:2a52b3e2e01b4229b76eb1f53a1068302021-11-19T00:00:15ZInvestigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands2151-153510.1109/JSTARS.2021.3124558https://doaj.org/article/2a52b3e2e01b4229b76eb1f53a1068302021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9599515/https://doaj.org/toc/2151-1535In the process of studying the spatiotemporal cause mechanism of urban heat island (UHI) effects, the classification method used will directly affect the robustness of urban surface heat classification. Applying five commonly used standard classification methods, we divided Beijing's urban surface temperatures in the summer of 2020 into five levels. We then compared the reliability of the five classification methods in resolving 12-period data and the seasonal average temperature in UHI patches, based on two indicators: UHI area and UHI intensity. The actual land-use composition of the UHI patches obtained with traditional methods was applied to confirm our results. The mean-standard deviation method and natural breaks (Jenks) method were more robust with regard to UHI classification and 12-period data reliability. For the UHI area index, the mean-standard deviation method produced the smallest total area of UHI patches for summer days and nights. For the UHI intensity index, the quantile method, mean-standard deviation method, and natural breaks (Jenks) method were associated with smaller errors. Considering the composition of land-use types in UHI patches, the mean-standard deviation method, and natural breaks (Jenks) method were more rigorous. Thus, our research results provide guidance for method selection when classifying UHI.Yingshuang LuTong HeXinliang XuZhi QiaoIEEEarticleModerate resolution imaging spectroradiometer (MODIS) land surface temperature (LST)robustnessstandard classification methodurban heat island (UHI) effecturban thermal gradesOcean engineeringTC1501-1800Geophysics. Cosmic physicsQC801-809ENIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 11386-11394 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST) robustness standard classification method urban heat island (UHI) effect urban thermal grades Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809
spellingShingle	Moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST) robustness standard classification method urban heat island (UHI) effect urban thermal grades Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809 Yingshuang Lu Tong He Xinliang Xu Zhi Qiao Investigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands
description	In the process of studying the spatiotemporal cause mechanism of urban heat island (UHI) effects, the classification method used will directly affect the robustness of urban surface heat classification. Applying five commonly used standard classification methods, we divided Beijing's urban surface temperatures in the summer of 2020 into five levels. We then compared the reliability of the five classification methods in resolving 12-period data and the seasonal average temperature in UHI patches, based on two indicators: UHI area and UHI intensity. The actual land-use composition of the UHI patches obtained with traditional methods was applied to confirm our results. The mean-standard deviation method and natural breaks (Jenks) method were more robust with regard to UHI classification and 12-period data reliability. For the UHI area index, the mean-standard deviation method produced the smallest total area of UHI patches for summer days and nights. For the UHI intensity index, the quantile method, mean-standard deviation method, and natural breaks (Jenks) method were associated with smaller errors. Considering the composition of land-use types in UHI patches, the mean-standard deviation method, and natural breaks (Jenks) method were more rigorous. Thus, our research results provide guidance for method selection when classifying UHI.
format	article
author	Yingshuang Lu Tong He Xinliang Xu Zhi Qiao
author_facet	Yingshuang Lu Tong He Xinliang Xu Zhi Qiao
author_sort	Yingshuang Lu
title	Investigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands
title_short	Investigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands
title_full	Investigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands
title_fullStr	Investigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands
title_full_unstemmed	Investigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands
title_sort	investigation the robustness of standard classification methods for defining urban heat islands
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/2a52b3e2e01b4229b76eb1f53a106830
work_keys_str_mv	AT yingshuanglu investigationtherobustnessofstandardclassificationmethodsfordefiningurbanheatislands AT tonghe investigationtherobustnessofstandardclassificationmethodsfordefiningurbanheatislands AT xinliangxu investigationtherobustnessofstandardclassificationmethodsfordefiningurbanheatislands AT zhiqiao investigationtherobustnessofstandardclassificationmethodsfordefiningurbanheatislands
_version_	1718420658836209664

Investigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands

Ejemplares similares