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Object-Based Mangrove Mapping Comparison on Visible and NIR UAV Sensor

Indonesian Journal of Geography · Vol. 53 No. 2 (2021) · pp. 165–169

DOI
10.22146/ijg.50861
ISSN
2354-9114, 0024-9521
Published
2021-08-28
Publisher
Faculty of Geography, Universitas Gadjah Mada
Language
eng
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Mangrove ecosystems are natural resources that have potential value for development due to their high productivity. Mapping and identification of mangroves have always played a crucial role in mangrove ecosystem conservation efforts, especially to support the sustainable development goal of coastal resources and climate change issues. Several attempts have been made using Unmanned Aerial Vehicle (UAV) techniques acquisition of high spatial resolution aerial images data with various sensors and object-based classification for image processing with various levels of success. This study aims to identify mangrove objects using UAV with true color and NIR false-color sensors using the OBIA approach. The UAV used in this study was DJI Phantom 3 Pro with a true-color sensor (default) and NIR false-color (modified Canon IXUS 160 cameras). The comparison between the two types of sensor of aerial photographs as a source for mangrove mapping proved that the latter performed better than the former because of the near-infrared band can optimally discriminate between mangrove and non-mangrove objects. This will assist future research directions in the mangrove ecosystems mapping method.

Keywords

Collaboration network of the authors

40 authors · 152 co-authorship links · 4 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Indonesia
  • Universitas Gadjah Mada
  • Indonesian National Institute of Aeronautics and Space
  • IPB University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Ratih Dewanti DimyatiUniversitas Gadjah Mada3
Faris ZulkarnainUniversity of Indonesia3
Kustiyo KustiyoIndonesian National Institute of Aeronautics and Space2
Nurul Sri RahatiningtyasUniversity of Indonesia2
Akbar Cahyadhi Pratama PutraAffiliation unknown2
Tantri Utami WidhaningtyasAffiliation unknown2
Bachtiar W. MutaqinAffiliation unknown2
Babag PurbantoroAffiliation unknown2
Triarko NurlambangAffiliation unknown2
Nur Mohammad FardaAffiliation unknown2
Totok Wahyu WibowoAffiliation unknown2
Dimas Bayu IchsandyaUniversity of Indonesia1
Iqbal Putut Ash ShidiqUniversity of Indonesia1
Riza Putera SyamsuddinUniversity of Indonesia1
Farhan Makarim ZeinUniversity of Indonesia1
I Wayan Gede Krisna ArimjayaUniversity of Indonesia1
Ananda FitrianiAffiliation unknown1
Ahmad MukhlishinAffiliation unknown1
Aan SuhendriAffiliation unknown1
S SunartoAffiliation unknown1
Marimin MariminIPB University1
Etty RianiAffiliation unknown1
Uju UjuAffiliation unknown1
Rodiah Nurbaya SariAffiliation unknown1
Sri Suryo SukoraharjoAffiliation unknown1
Ema HastariniAffiliation unknown1
Franciscus Edi PriyonoAffiliation unknown1
Sunarto ZulkifliAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) http://jurnal.ugm.ac.id/ijg/oai, first harvested 8 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Object-Based Mangrove Mapping Comparison on Visible and NIR UAV Sensor</dc:title>
	<dc:creator>Khakhim, Nurul</dc:creator>
	<dc:creator>Marfai, Muh Aris</dc:creator>
	<dc:creator>Putri, Ratih Fitria</dc:creator>
	<dc:creator>Dimyati, Muhammad</dc:creator>
	<dc:creator>Untoro, Muhammad Adnan Shafry</dc:creator>
	<dc:creator>Adiwijaya, Raden Ramadhani Yudha</dc:creator>
	<dc:creator>Walinono, Taufik</dc:creator>
	<dc:creator>Lazuardi, Wahyu</dc:creator>
	<dc:creator>Pratama, Dimas Novandias Damar</dc:creator>
	<dc:creator>Wicaksono, Arief</dc:creator>
	<dc:creator>Musthofa, Azis</dc:creator>
	<dc:creator>Isnaen, Zulfikri</dc:creator>
	<dc:subject xml:lang="en-US">Geography; Mapping; Remote Sensing; UAV; Sensor; Mangrove</dc:subject>
	<dc:subject xml:lang="en-US">NIR-sensor; GEOBIA; Baros Mangrove Conservation Area; Bantul</dc:subject>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:description xml:lang="en-US">Mangrove ecosystems are natural resources that have potential value for development due to their high productivity. Mapping and identification of mangroves have always played a crucial role in mangrove ecosystem conservation efforts, especially to support the sustainable development goal of coastal resources and climate change issues. Several attempts have been made using Unmanned Aerial Vehicle (UAV) techniques acquisition of high spatial resolution aerial images data with various sensors and object-based classification for image processing with various levels of success. This study aims to identify mangrove objects using UAV with true color and NIR false-color sensors using the OBIA approach. The UAV used in this study was DJI Phantom 3 Pro with a true-color sensor (default) and NIR false-color (modified Canon IXUS 160 cameras). The comparison between the two types of sensor of aerial photographs as a source for mangrove mapping proved that the latter performed better than the former because of the near-infrared band can optimally discriminate between mangrove and non-mangrove objects. This will assist future research directions in the mangrove ecosystems mapping method.</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>2021-08-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijg/article/view/50861</dc:identifier>
	<dc:identifier>10.22146/ijg.50861</dc:identifier>
	<dc:source xml:lang="en-US">Indonesian Journal of Geography; Vol 53, No 2 (2021): Indonesian Journal of Geography; 165-169</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/50861/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) 2021 Authors</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-nc/4.0</dc:rights>
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