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Article: Identifying patterns and hotspots of global land cover transitions using the ESA CCI land cover dataset

TitleIdentifying patterns and hotspots of global land cover transitions using the ESA CCI land cover dataset
Authors
Issue Date2018
Citation
Remote Sensing Letters, 2018, v. 9, n. 10, p. 972-981 How to Cite?
Abstract© 2018 Informa UK Limited, trading as Taylor & Francis Group. Land use/land cover change is a continuing research focus, not only because of its ecological and environmental effects but also because of the difficulties with accurate change detection and analysis uncertainty. The principal difficulty is the lack of a long time series of annual global land cover maps at a fine resolution. A new global long-term time series of annual datasets called the European Space Agency (ESA) Climate Change Initiative Land Cover (CCI-LC) has been published, making it possible to detect the global land cover changes. Using this ESA CCI-LC product from 1992–2015, we quantified the annual transitions of land cover change globally with the trajectory analysis method, analyzed the changes patterns and identified the land cover change hotspots. The total land cover change area for the world was 5.99 million km2, amounting to only 3.36% of the total continental area. Most changes happened in forest and cropland, accounting 32% of all the land cover changes. Most land cover changes happened in tropical ecoregions. Grassland changes were mainly distributed in the temperate ecoregions, while cropland expansion occurred mainly in the tropical or subtropical ecoregions. The hotspots identified in this paper could provide target areas for further research.
Persistent Identifierhttp://hdl.handle.net/10722/296861
ISSN
2023 Impact Factor: 1.4
2023 SCImago Journal Rankings: 0.458
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, Xiaoxuan-
dc.contributor.authorYu, Le-
dc.contributor.authorSia, Yali-
dc.contributor.authorZhang, Chi-
dc.contributor.authorLu, Hui-
dc.contributor.authorYu, Chaoqing-
dc.contributor.authorGong, Peng-
dc.date.accessioned2021-02-25T15:16:50Z-
dc.date.available2021-02-25T15:16:50Z-
dc.date.issued2018-
dc.identifier.citationRemote Sensing Letters, 2018, v. 9, n. 10, p. 972-981-
dc.identifier.issn2150-704X-
dc.identifier.urihttp://hdl.handle.net/10722/296861-
dc.description.abstract© 2018 Informa UK Limited, trading as Taylor & Francis Group. Land use/land cover change is a continuing research focus, not only because of its ecological and environmental effects but also because of the difficulties with accurate change detection and analysis uncertainty. The principal difficulty is the lack of a long time series of annual global land cover maps at a fine resolution. A new global long-term time series of annual datasets called the European Space Agency (ESA) Climate Change Initiative Land Cover (CCI-LC) has been published, making it possible to detect the global land cover changes. Using this ESA CCI-LC product from 1992–2015, we quantified the annual transitions of land cover change globally with the trajectory analysis method, analyzed the changes patterns and identified the land cover change hotspots. The total land cover change area for the world was 5.99 million km2, amounting to only 3.36% of the total continental area. Most changes happened in forest and cropland, accounting 32% of all the land cover changes. Most land cover changes happened in tropical ecoregions. Grassland changes were mainly distributed in the temperate ecoregions, while cropland expansion occurred mainly in the tropical or subtropical ecoregions. The hotspots identified in this paper could provide target areas for further research.-
dc.languageeng-
dc.relation.ispartofRemote Sensing Letters-
dc.titleIdentifying patterns and hotspots of global land cover transitions using the ESA CCI land cover dataset-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/2150704X.2018.1500070-
dc.identifier.scopuseid_2-s2.0-85055751082-
dc.identifier.volume9-
dc.identifier.issue10-
dc.identifier.spage972-
dc.identifier.epage981-
dc.identifier.eissn2150-7058-
dc.identifier.isiWOS:000442758200001-
dc.identifier.issnl2150-704X-

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