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Article: Inventory of mangrove wetlands in the Pearl River Estuary of China using remote sensing

TitleInventory of mangrove wetlands in the Pearl River Estuary of China using remote sensing
Authors
KeywordsBiomass
Change Detection
China
Mangrove Wetlands
Radar Remote Sensing
Issue Date2006
PublisherScience Press. The Journal's web site is located at http://springerlink.com/content/1009-637X
Citation
Journal Of Geographical Sciences, 2006, v. 16 n. 2, p. 155-164 How to Cite?
AbstractMangrove forests have important ecological functions in protecting the environment. However, the mangrove wetlands have been largely lost because of intensified human activities in the study area. Remote sensing can be conveniently used for the inventory of mangrove forests because field investigation is very difficult. In this study, a knowledge-based system is developed to retrieve spatio-temporal dynamics of mangrove wetlands using multi-temporal remote sensing data. Radar remote sensing data are also used to provide complementary information for the quantitative analysis of mangrove wetlands. Radar remote sensing is able to penetrate mangrove forests and obtain the trunk information about mangrove structures. The integration of radar remote sensing with optical remote sensing can significantly improve the accuracies of classifying mangrove wetland types and estimating wetland biomass. © Science in China Press 2006.
Persistent Identifierhttp://hdl.handle.net/10722/176288
ISSN
2015 Impact Factor: 1.923
2015 SCImago Journal Rankings: 0.800
References

 

DC FieldValueLanguage
dc.contributor.authorLi, Xen_US
dc.contributor.authorYeh, Aen_US
dc.contributor.authorLiu, Ken_US
dc.contributor.authorWang, Sen_US
dc.date.accessioned2012-11-26T09:08:14Z-
dc.date.available2012-11-26T09:08:14Z-
dc.date.issued2006en_US
dc.identifier.citationJournal Of Geographical Sciences, 2006, v. 16 n. 2, p. 155-164en_US
dc.identifier.issn1009-637Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/176288-
dc.description.abstractMangrove forests have important ecological functions in protecting the environment. However, the mangrove wetlands have been largely lost because of intensified human activities in the study area. Remote sensing can be conveniently used for the inventory of mangrove forests because field investigation is very difficult. In this study, a knowledge-based system is developed to retrieve spatio-temporal dynamics of mangrove wetlands using multi-temporal remote sensing data. Radar remote sensing data are also used to provide complementary information for the quantitative analysis of mangrove wetlands. Radar remote sensing is able to penetrate mangrove forests and obtain the trunk information about mangrove structures. The integration of radar remote sensing with optical remote sensing can significantly improve the accuracies of classifying mangrove wetland types and estimating wetland biomass. © Science in China Press 2006.en_US
dc.languageengen_US
dc.publisherScience Press. The Journal's web site is located at http://springerlink.com/content/1009-637Xen_US
dc.relation.ispartofJournal of Geographical Sciencesen_US
dc.subjectBiomassen_US
dc.subjectChange Detectionen_US
dc.subjectChinaen_US
dc.subjectMangrove Wetlandsen_US
dc.subjectRadar Remote Sensingen_US
dc.titleInventory of mangrove wetlands in the Pearl River Estuary of China using remote sensingen_US
dc.typeArticleen_US
dc.identifier.emailYeh, A: hdxugoy@hkucc.hku.hken_US
dc.identifier.authorityYeh, A=rp01033en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/s11442-006-0203-2en_US
dc.identifier.scopuseid_2-s2.0-33748999009en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33748999009&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume16en_US
dc.identifier.issue2en_US
dc.identifier.spage155en_US
dc.identifier.epage164en_US
dc.publisher.placeChinaen_US
dc.identifier.scopusauthoridLi, X=34872691500en_US
dc.identifier.scopusauthoridYeh, A=7103069369en_US
dc.identifier.scopusauthoridLiu, K=35170138700en_US
dc.identifier.scopusauthoridWang, S=14009964800en_US

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