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

Indonesian Journal of Geography · Vol. 50 No. 2 (2018) · hlm. 222–227

DOI
10.22146/ijg.16469
ISSN
2354-9114, 0024-9521
Terbit
2018-12-26
Penerbit
Faculty of Geography, Universitas Gadjah Mada
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-nc/4.0

Abstrak

The 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.

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  • Universitas Gadjah Mada
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Rekan penulisOrganisasiArtikel bersama
Muhammad KamalAfiliasi tidak diketahui3
Projo DanoedoroUniversitas Gadjah Mada2
Sigit HerumurtiAfiliasi tidak diketahui1
Yanuar Adji NugrohoAfiliasi tidak diketahui1
Prama Ardha AryagunaAfiliasi tidak diketahui1
Prima WidayaniAfiliasi tidak diketahui1
Muhammad Sufwandika WijayaAfiliasi tidak diketahui1
Hartono HartonoAfiliasi tidak diketahui1
Pramaditya WicaksonoAfiliasi tidak diketahui1
Novi Susetyo AdiAfiliasi tidak diketahui1
Intan LestariAfiliasi tidak diketahui1
Abimanyu Putra PratamaAfiliasi tidak diketahui1
Yusri KhoirurrizqiAfiliasi tidak diketahui1
Rohmad SasongkoAfiliasi tidak diketahui1
Nur Laila Eka UtamiAfiliasi tidak diketahui1
Amanda IrbahAfiliasi tidak diketahui1
Siti ZahrotunisaAfiliasi tidak diketahui1
Maulana Abdul HakimAfiliasi tidak diketahui1

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Sumber metadata: OAI-PMH (metadata jurnal) http://jurnal.ugm.ac.id/ijg/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Accuracy and Spatial Pattern Assessment of Forest Cover Change Datasets in Central Kalimantan</dc:title>
	<dc:creator>Arjasakusuma, Sanjiwana</dc:creator>
	<dc:creator>Pribadi, Uji Astrono</dc:creator>
	<dc:creator>Seta, Gilang Aria</dc:creator>
	<dc:subject xml:lang="en-US">Geography; Remote Sensing</dc:subject>
	<dc:subject xml:lang="en-US">Area-proportion matrix;Deforestation;Gain;Remote Sensing</dc:subject>
	<dc:subject xml:lang="en-US">Forestry</dc:subject>
	<dc:description xml:lang="en-US">The 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. </dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Geography, Universitas Gadjah Mada</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2018-12-26</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:type xml:lang="en-US">error-proportion matrix; euclidian distance</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijg/article/view/16469</dc:identifier>
	<dc:identifier>10.22146/ijg.16469</dc:identifier>
	<dc:source xml:lang="en-US">Indonesian Journal of Geography; Vol 50, No 2 (2018): Indonesian Journal of Geography; 222-227</dc:source>
	<dc:source>2354-9114</dc:source>
	<dc:source>0024-9521</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijg/article/view/16469/pdf</dc:relation>
	<dc:coverage xml:lang="en-US">Katingan, Central Kalimantan</dc:coverage>
	<dc:coverage xml:lang="en-US"></dc:coverage>
	<dc:coverage xml:lang="en-US"></dc:coverage>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 Authors</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-nc/4.0</dc:rights>
</oai_dc:dc>