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Examining the impacts of urbanization on surface radiation using Landsat imagery
Kuang, Wenhui1; Liu, Ailin1,2; Dou, Yinyin3; Li, Guiying4,5; Lu, Dengsheng4,5
2019-04-03
Source PublicationGISCIENCE & REMOTE SENSING
ISSN1548-1603
Volume56Issue:3Pages:462-484
Corresponding AuthorKuang, Wenhui(kuangwh@igsnrr.ac.cn) ; Lu, Dengsheng(dengshenglu@gmail.com)
AbstractMetropolitan Beijing is facing many environmental problems such as haze and urban heat island due to the rapid urbanization. Surface shortwave, longwave, and net radiations are key components of the surface-atmosphere radiation budget. Since megacities are affected by the thermal radiation of complex landscape structures and atmospheric environments, quantitative and spatially explicit retrieval from remotely sensed data remains a challenge. We collected the surface radiation fluxes from seven fixed sites representing different land-use types to calibrate the local parameters for remotely sensed retrieval of net radiation. We proposed a remote sensing-based surface radiation retrieval method by embedding the underlying land covers and integrating the observational data. The improved method is feasible to accurately retrieve surface radiation and delineate spatial characteristics in metropolitan areas. The accuracy evaluation indicated that the difference between remotely sensed and in situ observed net radiation ranged within 0 similar to +/- 40 W center dot m(-2). The root mean squared error of the estimated net surface radiation was 32.71 W center dot m(-2). The strongly spatial heterogeneity of surface radiation components in metropolitan Beijing was closely related to land-cover patterns from urban area to outskirts. We also found that the surface net radiation had a decreasing trend from 1984 to 2014, and the net radiation in the urban area was lower than that in the outskirts. According to the surface radiation budgets, urbanization resulted in the cooling effect in net radiation flux in the daytime, which was stemmed from low atmospheric transmittances from massive aerosol concentration and high surface albedo from light building materials.
Keywordradiation budget shortwave radiation longwave radiation net radiation atmospheric transmittance Landsat
DOI10.1080/15481603.2018.1508931
WOS KeywordSPATIOTEMPORAL CHARACTERISTICS ; FLUX PARAMETERIZATIONS ; LONGWAVE RADIATION ; DRIVING FORCES ; BOUNDARY-LAYER ; ENERGY BALANCE ; NET-RADIATION ; URBAN ; TEMPERATURE ; COVER
Indexed BySCI
Language英语
Funding ProjectKey Project of Beijing Natural Science Foundation[8171004] ; National Natural Science Foundation of China[41371408]
Funding OrganizationKey Project of Beijing Natural Science Foundation ; National Natural Science Foundation of China
WOS Research AreaPhysical Geography ; Remote Sensing
WOS SubjectGeography, Physical ; Remote Sensing
WOS IDWOS:000457866600007
PublisherTAYLOR & FRANCIS LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/49948
Collection中国科学院地理科学与资源研究所
Corresponding AuthorKuang, Wenhui; Lu, Dengsheng
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Coll Resources & Environm, 19A Yuquan Rd, Beijing 100049, Peoples R China
3.Beijing Normal Univ, Ctr Human Environm Syst Sustainabil, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China
4.Fujian Normal Univ, Fujian Prov Key Lab Subtrop Resources & Environm, Fuzhou 350007, Fujian, Peoples R China
5.Fujian Normal Univ, Sch Geog Sci, Fuzhou 350007, Fujian, Peoples R China
Recommended Citation
GB/T 7714
Kuang, Wenhui,Liu, Ailin,Dou, Yinyin,et al. Examining the impacts of urbanization on surface radiation using Landsat imagery[J]. GISCIENCE & REMOTE SENSING,2019,56(3):462-484.
APA Kuang, Wenhui,Liu, Ailin,Dou, Yinyin,Li, Guiying,&Lu, Dengsheng.(2019).Examining the impacts of urbanization on surface radiation using Landsat imagery.GISCIENCE & REMOTE SENSING,56(3),462-484.
MLA Kuang, Wenhui,et al."Examining the impacts of urbanization on surface radiation using Landsat imagery".GISCIENCE & REMOTE SENSING 56.3(2019):462-484.
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