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Article: An object-based classification approach in mapping tree mortality using high spatial resolution imagery

TitleAn object-based classification approach in mapping tree mortality using high spatial resolution imagery
Authors
Issue Date2007
Citation
GIScience and Remote Sensing, 2007, v. 44, n. 1, p. 24-47 How to Cite?
AbstractIn California, a newly discovered virulent pathogen (Phytophthora ramorum) has killed thousands of trees, including tanoak (Lithocarpus densiflorus), coast live oak (Quercus agrifolia), and black oak (Quercus kelloggii). Mapping the distribution of overstory mortality associated with the pathogen is an important part of disease management. In this study, we developed an object-based approach, including an image segmentation process and a knowledge-based classifier, to detect individual tree mortality in imagery of 1 in spatial resolution. The combined segmentation and classification methods provided an easy and intuitive way to incorporate human knowledge into the classification process. The object-based approach significantly outperformed a pixel-based maximum likelihood classification method in mapping the tree mortality on high-spatial-resolution multispectral imagery. Copyright © 2007 by V.H. Winston & Son, Inc. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/296603
ISSN
2023 Impact Factor: 6.0
2023 SCImago Journal Rankings: 1.756
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorGuo, Qinghua-
dc.contributor.authorKelly, Maggi-
dc.contributor.authorGong, Peng-
dc.contributor.authorLiu, Desheng-
dc.date.accessioned2021-02-25T15:16:15Z-
dc.date.available2021-02-25T15:16:15Z-
dc.date.issued2007-
dc.identifier.citationGIScience and Remote Sensing, 2007, v. 44, n. 1, p. 24-47-
dc.identifier.issn1548-1603-
dc.identifier.urihttp://hdl.handle.net/10722/296603-
dc.description.abstractIn California, a newly discovered virulent pathogen (Phytophthora ramorum) has killed thousands of trees, including tanoak (Lithocarpus densiflorus), coast live oak (Quercus agrifolia), and black oak (Quercus kelloggii). Mapping the distribution of overstory mortality associated with the pathogen is an important part of disease management. In this study, we developed an object-based approach, including an image segmentation process and a knowledge-based classifier, to detect individual tree mortality in imagery of 1 in spatial resolution. The combined segmentation and classification methods provided an easy and intuitive way to incorporate human knowledge into the classification process. The object-based approach significantly outperformed a pixel-based maximum likelihood classification method in mapping the tree mortality on high-spatial-resolution multispectral imagery. Copyright © 2007 by V.H. Winston & Son, Inc. All rights reserved.-
dc.languageeng-
dc.relation.ispartofGIScience and Remote Sensing-
dc.titleAn object-based classification approach in mapping tree mortality using high spatial resolution imagery-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.2747/1548-1603.44.1.24-
dc.identifier.scopuseid_2-s2.0-33846516990-
dc.identifier.volume44-
dc.identifier.issue1-
dc.identifier.spage24-
dc.identifier.epage47-
dc.identifier.isiWOS:000244371100002-
dc.identifier.issnl1548-1603-

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