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2022-03-30Zeitschriftenartikel DOI: 10.3390/rs14071673
Mapping Impervious Surface Using Phenology-Integrated and Fisher Transformed Linear Spectral Mixture Analysis
dc.contributor.authorOuyang, Linke
dc.contributor.authorWu, Caiyan
dc.contributor.authorLi, Junxiang
dc.contributor.authorLiu, Yuhan
dc.contributor.authorWang, Meng
dc.contributor.authorHan, Ji
dc.contributor.authorSong, Conghe
dc.contributor.authorYu, Qian
dc.contributor.authorHaase, Dagmar
dc.date.accessioned2022-06-17T08:13:15Z
dc.date.available2022-06-17T08:13:15Z
dc.date.issued2022-03-30none
dc.date.updated2022-04-26T11:44:50Z
dc.identifier.urihttp://edoc.hu-berlin.de/18452/25455
dc.description.abstractThe impervious surface area (ISA) is a key indicator of urbanization, which brings out serious adverse environmental and ecological consequences. The ISA is often estimated from remotely sensed data via spectral mixture analysis (SMA). However, accurate extraction of ISA using SMA is compromised by two major factors, endmember spectral variability and plant phenology. This study developed a novel approach that incorporates phenology with Fisher transformation into a conventional linear spectral mixture analysis (PF-LSMA) to address these challenges. Four endmembers, high albedo, low albedo, evergreen vegetation, and seasonally exposed soil (H-L-EV-SS) were identified for PF-LSMA, considering the phenological characteristic of Shanghai. Our study demonstrated that the PF-LSMA effectively reduced the within-endmember spectral signature variation and accounted for the endmember phenology effects, and thus well-discriminated impervious surface from seasonally exposed soil, enhancing the accuracy of ISA extraction. The ISA fraction map produced by PF-LSMA (RMSE = 0.1112) outperforms the single-date image Fisher transformed unmixing method (F-LSMA) (RMSE = 0.1327) and the other existing major global ISA products. The PF-LSMA was implemented on the Google Earth Engine platform and thus can be easily adapted to extract ISA in other places with similar climate conditions.eng
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectimpervious surface areaeng
dc.subjectphenology informationeng
dc.subjectFisher transformationeng
dc.subjectlinear spectral mixture analysiseng
dc.subjectendmember variabilityeng
dc.subjectGoogle Earth Engineeng
dc.subjectseasonally exposed soileng
dc.subjectVIS modeleng
dc.subjectShanghaieng
dc.subjectLandsateng
dc.subject.ddc333.7 Landflächen, Naturräume für Freizeit und Erholung, Naturreservate, Energienone
dc.titleMapping Impervious Surface Using Phenology-Integrated and Fisher Transformed Linear Spectral Mixture Analysisnone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/25455-8
dc.identifier.doi10.3390/rs14071673none
dc.identifier.doihttp://dx.doi.org/10.18452/24789
dc.type.versionpublishedVersionnone
local.edoc.container-titleRemote sensingnone
local.edoc.pages19none
local.edoc.type-nameZeitschriftenartikel
local.edoc.institutionMathematisch-Naturwissenschaftliche Fakultätnone
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameMDPInone
local.edoc.container-publisher-placeBaselnone
local.edoc.container-volume14none
local.edoc.container-issue7none
dc.description.versionPeer Reviewednone
local.edoc.container-articlenumber1673none
dc.identifier.eissn2072-4292

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