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Article: A new research paradigm for global land cover mapping

TitleA new research paradigm for global land cover mapping
Authors
Keywordsimage classification
universal sampling
on-line mapping
class definition
Remote sensing
all-in-one system
Issue Date2016
Citation
Annals of GIS, 2016, v. 22, n. 2, p. 87-102 How to Cite?
Abstract© 2016 Informa UK Limited, trading as Taylor & Francis Group. ABSTRACT: In this paper, we introduced major challenges in mapping croplands, settlements, water and wetlands, and discussed challenges in the use of multi-temporal and multi-sensor data. We then summarized some of the on-going efforts in improving qualities of global land cover maps. Existing technologies provide sufficient data for better map making if extra efforts can be made instead of harmonizing and integrating various global land cover products. Developing and selecting better algorithms, including more input variables (new types of data or features) for classification, having representative training samples are among conventional measures generally believed effective in improving mapping accuracies at local scales. We pointed out that data were more important in improving mapping accuracies than algorithms. Finally, we proposed a new paradigm for global land cover mapping, which included a view of vegetation classes based on their types and form, canopy cover and height. The new paradigm suggests that a universally applicable training sample set is not only possible but also effective in improving land cover classification at the continental and global scales. To ensure an easy transition from traditional land cover mapping to the new paradigm, we recommended that an all-in-one data management and analysis system be constructed.
Persistent Identifierhttp://hdl.handle.net/10722/296774
ISSN
2020 SCImago Journal Rankings: 0.685

 

DC FieldValueLanguage
dc.contributor.authorGong, Peng-
dc.contributor.authorYu, Le-
dc.contributor.authorLi, Congcong-
dc.contributor.authorWang, Jie-
dc.contributor.authorLiang, Lu-
dc.contributor.authorLi, Xuecao-
dc.contributor.authorJi, Luyan-
dc.contributor.authorBai, Yuqi-
dc.contributor.authorCheng, Yuqi-
dc.contributor.authorZhu, Zhiliang-
dc.date.accessioned2021-02-25T15:16:39Z-
dc.date.available2021-02-25T15:16:39Z-
dc.date.issued2016-
dc.identifier.citationAnnals of GIS, 2016, v. 22, n. 2, p. 87-102-
dc.identifier.issn1947-5683-
dc.identifier.urihttp://hdl.handle.net/10722/296774-
dc.description.abstract© 2016 Informa UK Limited, trading as Taylor & Francis Group. ABSTRACT: In this paper, we introduced major challenges in mapping croplands, settlements, water and wetlands, and discussed challenges in the use of multi-temporal and multi-sensor data. We then summarized some of the on-going efforts in improving qualities of global land cover maps. Existing technologies provide sufficient data for better map making if extra efforts can be made instead of harmonizing and integrating various global land cover products. Developing and selecting better algorithms, including more input variables (new types of data or features) for classification, having representative training samples are among conventional measures generally believed effective in improving mapping accuracies at local scales. We pointed out that data were more important in improving mapping accuracies than algorithms. Finally, we proposed a new paradigm for global land cover mapping, which included a view of vegetation classes based on their types and form, canopy cover and height. The new paradigm suggests that a universally applicable training sample set is not only possible but also effective in improving land cover classification at the continental and global scales. To ensure an easy transition from traditional land cover mapping to the new paradigm, we recommended that an all-in-one data management and analysis system be constructed.-
dc.languageeng-
dc.relation.ispartofAnnals of GIS-
dc.subjectimage classification-
dc.subjectuniversal sampling-
dc.subjecton-line mapping-
dc.subjectclass definition-
dc.subjectRemote sensing-
dc.subjectall-in-one system-
dc.titleA new research paradigm for global land cover mapping-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1080/19475683.2016.1164247-
dc.identifier.scopuseid_2-s2.0-84962633150-
dc.identifier.volume22-
dc.identifier.issue2-
dc.identifier.spage87-
dc.identifier.epage102-
dc.identifier.eissn1947-5691-
dc.identifier.issnl1947-5691-

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