Accuracy and Spatial Pattern Assessment of Forest Cover Change Datasets in Central Kalimantan

Simple item page
cg.contributor.crpForests, Trees and Agroforestry
cg.coverage.countryIndonesia
cg.coverage.iso3166-alpha2ID
cg.coverage.regionSouth-eastern Asia
cg.identifier.doihttps://doi.org/10.22146/ijg.16469en
cg.issn2354-9114en
cg.issn0024-9521en
cg.issue2en
cg.journalIndonesian Journal of Geographyen
cg.subject.ciforCLIMATE CHANGEen
cg.subject.ciforSMART FORESTRYen
cg.volume50en
dc.contributor.authorArjasakusuma, S.en
dc.contributor.authorPribadi, U.A.en
dc.contributor.authorSeta, G.A.en
dc.date.accessioned2021-03-08T08:14:40Zen
dc.date.available2021-03-08T08:14:40Zen
dc.identifier.urihttps://hdl.handle.net/10568/111854
dc.titleAccuracy and Spatial Pattern Assessment of Forest Cover Change Datasets in Central Kalimantanen
dcterms.abstractThe accurate information of forest cover change is important to measure the amount of carbon release and sink. The newly-available remote sensing based products and method such as Daichi Forest/Non-Forest (FNF), Global Forest Change (GFC) datasets and Semi-automatic Claslite systems offers the benefit to derive these information in a quick and simple manner. We measured the accuracy by constructing area-proportion error matrix from 388 random sample points and assessed the consistency analysis by looking at the spatial pattern of deforestation and regrowth from built-up area, roads, and rivers from 2010 – 2015 in Katingan district, Central Kalimantan. Accuracy assessment showed that those 3 datasets indicate low to medium accuracy level in which the highest accuracy was achieved by Claslite who produced 71 % ± 5 % of overall accuracy. The consistency analysis provides a similar spatial pattern of deforestation and regrowth measured from the road, river, and built-up area though their distance sensitivity are different one to another.en
dcterms.accessRightsOpen Access
dcterms.available2018-12-26
dcterms.bibliographicCitationArjasakusuma, S., Pribadi, U.A., Seta, G.A. 2018. Accuracy and Spatial Pattern Assessment of Forest Cover Change Datasets in Central Kalimantan. Indonesian Journal of Geography, 50 (2): 222-227. https://doi.org/10.22146/ijg.16469en
dcterms.issued2018-12-29
dcterms.languageen
dcterms.licenseCC-BY-NC-4.0
dcterms.publisherUniversitas Gadjah Madaen
dcterms.subjectremote sensingen
dcterms.subjectforest coveren
dcterms.subjectcarbon sinksen
dcterms.subjectdeforestationen
dcterms.typeJournal Article

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