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Assessing the Capability of Sentinel-2A Data for Mapping Seagrass Percent Cover in Jerowaru, East Lombok

Indonesian Journal of Geography · Vol. 49 No. 2 (2017) · hlm. 195–203

DOI
10.22146/ijg.28407
ISSN
2354-9114, 0024-9521
Terbit
2017-12-27
Penerbit
Faculty of Geography, Universitas Gadjah Mada
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-nc/4.0

Abstrak

Remote sensing technology has been widely used in various applications related to natural resources and environment monitoring. In this paper, we evaluated the capability of new Sentinel-2A image to map the distribution and percent cover of seagrass in optically shallow water of Jerowaru coastal area, East Lombok. Seagrass distribution map was produced from radiometrically and geometrically corrected Sentinel-2A image with overall accuracy of 61.9%. Using empirical model, seagrass percent cover was predicted with maximum coefficient of determination (R2) of 0.51 and standard error of estimate (SE) of 19.4%. The results suggest that Sentinel-2A image can be used to perform seagrass mapping time and cost-effectively and can be further improved by incorporating more robust empirical modeling technique.

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  • Universitas Gadjah Mada
  • Ministry of Marine Affairs and Fisheries
  • Indonesian Institute of Sciences
  • Indonesian National Institute of Aeronautics and Space
  • National Yang Ming Chiao Tung University
  • University of Technology Malaysia
  • The Ohio State University
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  • Organisasi berbeda
  • Organisasi sama
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Rekan penulisOrganisasiArtikel bersama
Novi Susetyo AdiMinistry of Marine Affairs and Fisheries2
Aisya Jaya DhannahisvaraUniversitas Gadjah Mada1
Hartono HarjoUniversitas Gadjah Mada1
Ferman Setia NugrohoIndonesian National Institute of Aeronautics and Space1
Arief WicaksonoUniversitas Gadjah Mada1
Akbar Muammar SyarifUniversitas Gadjah Mada1
Faza AdhimahUniversitas Gadjah Mada1
Hartono HartonoUniversitas Gadjah Mada1
Muhammad KamalUniversitas Gadjah Mada1
Sanjiwana ArjasakusumaUniversitas Gadjah Mada1
Dewayany SutrisnoAfiliasi tidak diketahui1
Peter Tian‐Yuan ShihNational Yang Ming Chiao Tung University1
Mazlan HashimUniversity of Technology Malaysia1
Rongjun QinThe Ohio State University1
Rahman SyaifoelAfiliasi tidak diketahui1
Suyarso SuyarsoIndonesian Institute of Sciences1
Muhammad HafiztNational Research and Innovation Agency1
Doddy Mendro YuwonoAfiliasi tidak diketahui1
Bayu PrayudhaIndonesian Institute of Sciences1
Purwani IstianaUniversitas Gadjah Mada1
Latifa Melani PutriUniversitas Gadjah Mada1
Projo DanoedoroUniversitas Gadjah Mada1
Fela PritianUniversitas Gadjah Mada1
Moh YasirMinistry of Marine Affairs and Fisheries1

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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">Assessing the Capability of Sentinel-2A Data for Mapping Seagrass Percent Cover in Jerowaru, East Lombok</dc:title>
	<dc:creator>Fauzan, Muhammad Afif</dc:creator>
	<dc:creator>Kumara, Ignatius S. W.</dc:creator>
	<dc:creator>Yogyantoro, Rifka N.</dc:creator>
	<dc:creator>Suwardana, Satrio W.</dc:creator>
	<dc:creator>Fadhilah, Nurul</dc:creator>
	<dc:creator>Nurmalasari, Intansania</dc:creator>
	<dc:creator>Apriyani, Santi</dc:creator>
	<dc:creator>Wicaksono, Pramaditya</dc:creator>
	<dc:subject xml:lang="en-US">Remote Sensing</dc:subject>
	<dc:subject xml:lang="en-US">Remote sensing; Sentinel-2; Seagrass; Mapping</dc:subject>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:description xml:lang="en-US">Remote sensing technology has been widely used in various applications related to natural resources and environment monitoring. In this paper, we evaluated the capability of new Sentinel-2A image to map the distribution and percent cover of seagrass in optically shallow water of Jerowaru coastal area, East Lombok. Seagrass distribution map was produced from radiometrically and geometrically corrected Sentinel-2A image with overall accuracy of 61.9%. Using empirical model, seagrass percent cover was predicted with maximum coefficient of determination (R2) of 0.51 and standard error of estimate (SE) of 19.4%. The results suggest that Sentinel-2A image can be used to perform seagrass mapping time and cost-effectively and can be further improved by incorporating more robust empirical modeling technique.</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>2017-12-27</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"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijg/article/view/28407</dc:identifier>
	<dc:identifier>10.22146/ijg.28407</dc:identifier>
	<dc:source xml:lang="en-US">Indonesian Journal of Geography; Vol 49, No 2 (2017): Indonesian Journal of Geography; 195-203</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/28407/pdf</dc:relation>
	<dc:coverage xml:lang="en-US"></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) 2017 Authors</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-nc/4.0</dc:rights>
</oai_dc:dc>