{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T01:00:22Z","timestamp":1775869222725,"version":"3.50.1"},"reference-count":102,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,5]],"date-time":"2021-11-05T00:00:00Z","timestamp":1636070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Universiti Teknologi Malaysia-RUG Iconic RA Research Grant; and the Directorate Research Strengthening and Development, Ministry of Research and Technolo-gy\/National Research and Innovation Agency, Republic of Indonesia","award":["Vot 09G73; and 1\/E1\/KP.PTNBH\/2020"],"award-info":[{"award-number":["Vot 09G73; and 1\/E1\/KP.PTNBH\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Spatial information on benthic habitats in Wangiwangi island waters, Wakatobi District, Indonesia was very limited in recent years. However, this area is one of the marine tourism destinations and one of the Indonesia\u2019s triangle coral reef regions with a very complex coral reef ecosystem. The drone technology that has rapidly developed in this decade, can be used to map benthic habitats in this area. This study aimed to map shallow-water benthic habitats using drone technology in the region of Wangiwangi island waters, Wakatobi District, Indonesia. The field data were collected using a 50 \u00d7 50 cm squared transect of 434 observation points in March\u2013April 2017. The DJI Phantom 3 Pro drone with a spatial resolution of 5.2 \u00d7 5.2 cm was used to acquire aerial photographs. Image classifications were processed using object-based image analysis (OBIA) method with contextual editing classification at level 1 (reef level) with 200 segmentation scale and several segmentation scales at level 2 (benthic habitat). For level 2 classification, we found that the best algorithm to map benthic habitat was the support vector machine (SVM) algorithm with a segmentation scale of 50. Based on field observations, we produced 12 and 9 benthic habitat classes. Using the OBIA method with a segmentation value of 50 and the SVM algorithm, we obtained the overall accuracy of 77.4% and 81.1% for 12 and 9 object classes, respectively. This result improved overall accuracy up to 17% in mapping benthic habitats using Sentinel-2 satellite data within the similar region, similar classes, and similar method of classification analyses.<\/jats:p>","DOI":"10.3390\/rs13214452","type":"journal-article","created":{"date-parts":[[2021,11,7]],"date-time":"2021-11-07T20:42:54Z","timestamp":1636317774000},"page":"4452","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Shallow-Water Benthic Habitat Mapping Using Drone with Object Based Image Analyses"],"prefix":"10.3390","volume":"13","author":[{"given":"Bisman","family":"Nababan","sequence":"first","affiliation":[{"name":"Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University, Bogor 16680, Indonesia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2706-6280","authenticated-orcid":false,"given":"La Ode Khairum","family":"Mastu","sequence":"additional","affiliation":[{"name":"Program Study of Fisheries Sciences, Muhammadiyah Business and Technology Institute, Wakatobi 93791, Indonesia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3772-2149","authenticated-orcid":false,"given":"Nurul Hazrina","family":"Idris","sequence":"additional","affiliation":[{"name":"Geoscience and Digital Earth Centre, Research Institute of Sustainable Environment, Universiti Teknologi Malaysia, Skudai 81310, Malaysia"},{"name":"Tropical Resource Mapping Research Group, Department of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Skudai 81310, Malaysia"}]},{"given":"James P.","family":"Panjaitan","sequence":"additional","affiliation":[{"name":"Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University, Bogor 16680, Indonesia"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,5]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Geomorphic zones mapping of coral reef ecosystem with OBIA method, case study in Pari Island","volume":"12","author":"Anggoro","year":"2015","journal-title":"J. Penginderaan Jauh"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.ecss.2013.09.018","article-title":"Object-based benthic habitat mapping in the Florida Keys from hyperspectral imagery","volume":"134","author":"Zhang","year":"2013","journal-title":"Estuar. Coast. Shelf Ser."},{"key":"ref_3","unstructured":"Wilson, J.R., Ardiwijaya, R.L., and Prasetia, R. (2012). A Study of the Impact of the 2010 Coral Bleaching Event on Coral Communities in Wakatobi National Park, The Nature Conservancy, Indo-Pacific Division. Report No.7\/12."},{"key":"ref_4","unstructured":"and Budiyanto, A. (2008). Studi Baseline Terumbu Karang di Lokasi DPL Kabupaten Wakatobi, COREMAP II (Coral Reef Rehabilitation and Management Program)-LIPI."},{"key":"ref_5","unstructured":"Anonim (2001). Coral reef rehabilitation and management program. CRITC Report: Base line study Wakatobi Sulawesi Tenggara, COREMAP."},{"key":"ref_6","unstructured":"Balai Taman Nasional Wakatobi (2008). Rencana pengelolaan taman nasional Wakatobi Tahun 1998\u20132023, The Nature Conservancy dan WWF-Indonesia. Proyek kerjasama departemen kehutanan PHKA balai taman nasional Wakatobi, Pemerintah Kabupaten Wakatobi."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"105","DOI":"10.3354\/dao02160","article-title":"Spation-temporal coral disease dynamics in the Wakatobi marine national park. South-East Sulawesi Indonesia","volume":"87","author":"Haapkyla","year":"2009","journal-title":"Dis. Aquat. Org."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1017\/S0025315407055828","article-title":"Coral disease prevalence and coral health in the Wakatobi marine park, Southeast Sulawesi, Indonesia","volume":"87","author":"Haapkyla","year":"2007","journal-title":"J. Mar. Biol. Assoc."},{"key":"ref_9","first-page":"469","article-title":"Preliminary comparison of three coral reef sites in the Wakatobi marine national park (S.E. Sulawesi, Indonesia): Estimated recruitment dates compared with discovery Bay, Jamaica","volume":"74","author":"Crabbe","year":"2004","journal-title":"Bull. Mar. Sci."},{"key":"ref_10","unstructured":"Pet-Soede, L., and Erdmann, M.V. (2003). Coral diversity and distribution. Rapid ecologica assessment, Wakatobi National Park, TNC-SEA-CMPA; WWF Marine Program."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1007\/s00338-002-0250-9","article-title":"Comparison of two reef sites in the Wakatobi marine national park (S.E. Sulawesi, Indonesia) using digital image analysis","volume":"21","author":"Crabbe","year":"2002","journal-title":"Coral Reefs"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.ecss.2006.10.006","article-title":"Diel trophic structuring of seagrass bed fish assemblages in the Wakatobi Marine National Park, Indonesia","volume":"72","author":"Unsworth","year":"2007","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"9","DOI":"10.29244\/jitkt.v12i1.26598","article-title":"Seagrass ecosystem mapping with and without water column correction in Pajenekang island waters, South Sulawesi","volume":"12","author":"Ilyas","year":"2020","journal-title":"J. Ilmu Teknol. Kelaut. Trop."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"012044","DOI":"10.1088\/1755-1315\/429\/1\/012044","article-title":"Accuracy assessment of several classification algorithms with and without hue saturation intensity input features on object analyses on benthic habitat mapping in the Pajenekang island waters, South Sulawesi","volume":"429","author":"Pragunanti","year":"2020","journal-title":"IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Wicaksono, P., Aryaguna, P.A., and Lazuardi, W. (2019). Benthic habitat mapping model and cross validation using machine-learning classification algorithms. Remote Sens., 11.","DOI":"10.3390\/rs11111279"},{"key":"ref_16","first-page":"176","article-title":"Integrating remote sensing and field survey to map shallow water benthic habitat for the Kingdom of Bahrain","volume":"6","author":"Ghoneim","year":"2017","journal-title":"J. Environ. Sci. Eng."},{"key":"ref_17","first-page":"89","article-title":"Multiscale classification for geomorphic zone and benthic habitats mapping using OBIA method in Pari Island","volume":"14","author":"Anggoro","year":"2017","journal-title":"J. Penginderaan Jauh"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1016\/j.proenv.2015.03.029","article-title":"Object-based image analysis for coral reef benthic habitat mapping with several classification algorithms","volume":"24","author":"Wahiddin","year":"2015","journal-title":"Procedia Environ. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.isprsjprs.2014.06.005","article-title":"Applying data fusion techniques for benthic habitat mapping","volume":"104","author":"Zhang","year":"2014","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_20","first-page":"453","article-title":"Pemetaan habitat dasar dan estimasi stok ikan terumbu dengan citra satelit resolusi tinggi","volume":"5","author":"Siregar","year":"2013","journal-title":"J. Ilmu Teknol. Kelaut. Trop."},{"key":"ref_21","first-page":"19","article-title":"Pemetaan Substrat Dasar Perairan Dangkal Karang Congkak dan Lebar Kepulauan Seribu Menggunakan Citra Satelit QuickBird","volume":"2","author":"Siregar","year":"2010","journal-title":"J. Ilmu Teknol. Kelaut. Trop."},{"key":"ref_22","first-page":"95","article-title":"Aplikasi citra quickbird untuk pemetaan 3D substrat dasar di gusung karang","volume":"8","author":"Selamat","year":"2012","journal-title":"J. Imiah Geomatika"},{"key":"ref_23","first-page":"17","article-title":"Geomorphology zonation and column correction for bottom substrat mapping using quickbird image","volume":"2","author":"Selamat","year":"2012","journal-title":"J. Ilmu Teknol. Kelaut. Trop."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3768","DOI":"10.1080\/01431161.2011.633122","article-title":"Multi-scale, object-based image analysis for mapping geomorphic and ecological zones on coral reefs","volume":"33","author":"Phinn","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1809","DOI":"10.3390\/rs5041809","article-title":"Image-based coral reef classification and thematic mapping","volume":"5","author":"Shihavuddin","year":"2013","journal-title":"Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.rse.2003.04.005","article-title":"Multi-site evaluation of IKONOS data for classification of tropical coral reef environments","volume":"88","author":"Kramer","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/S0034-4257(02)00041-X","article-title":"Mapping marine environments with IKONOS imagery: Enhanced spatial resoltion can deliver greater thematic accuracy","volume":"82","author":"Mumby","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1080\/014311698216521","article-title":"Benefits of water column correction and contextual editing for mapping coral reefs","volume":"19","author":"Mumby","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2805","DOI":"10.1080\/0143116031000066954","article-title":"Remote sensing of the coastal zone: An overview and priorities for future research","volume":"24","author":"Malthus","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"5655","DOI":"10.1080\/014311602331291215","article-title":"Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery","volume":"25","author":"Wang","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2349","DOI":"10.1080\/01431161.2017.1297548","article-title":"UAS, sensors, and data processing in agroforestry: A review towards practical applications","volume":"38","author":"Vanko","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3027","DOI":"10.1080\/01431161.2017.1285087","article-title":"Autonomous 3D metric reconstruction from uncalibrated aerial images captured from UAVs","volume":"38","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_33","first-page":"695","article-title":"Measurement of rill erosion through a new UAV-GIS methodology","volume":"10","author":"Bazzoffi","year":"2015","journal-title":"Ital. J. Agron."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1175\/JTECH-D-14-00122.1","article-title":"Surfzone monitoring using rotary wing unmanned aerial vehicles","volume":"32","author":"Brouwer","year":"2015","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_35","first-page":"125","article-title":"Pemetaan pulau kecil dengan pendekatan berbasis objek menggunakan data unmanned aerial vehicle (UAV)","volume":"17","author":"Ramadhani","year":"2015","journal-title":"Maj. Ilm. Globe"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Udin, W.S., and Ahmad, A. (2014). Assessment of photogrammetric mapping accuracy based on variation flying altitude using unmanned aerial vehicle. 8th International Symposium of the Digital Earth (ISDE8). IOP Conf. Ser. Earth Environ. Sci., 18.","DOI":"10.1088\/1755-1315\/18\/1\/011001"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1007\/s12555-010-0105-z","article-title":"Autopilots for small unmanned aerial vehicles: A survey","volume":"8","author":"Chao","year":"2010","journal-title":"Int. J. Contr. Autom. Syst."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1007\/s10846-008-9303-9","article-title":"Architecture for cooperative airborne simulataneous localization and mapping","volume":"55","author":"Mitch","year":"2009","journal-title":"J. Intell. Robot Syst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1109\/TGRS.2008.2010314","article-title":"UAV-borne 3-D mapping system by multisensory integration","volume":"47","author":"Nagai","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","unstructured":"Rango, A.S., Laliberte, A.S., Herrick, J.E., Winters, C., and Havstad, K. (2008, January 7\u20139). Development of an operational UAV\/remote sensing capability for rangeland management. Proceedings of the 23rd Bristol International Unmanned Air Vehicle Systems (UAVS) Conference, Bristol, UK."},{"key":"ref_42","unstructured":"Patterson, M.C.L., and Brescia, A. (2008, January 7\u20139). Integrated sensor systems for UAS. Proceedings of the 23rd Bristol International Unmanned Air Vehicle Systems (UAVS) Conference, Bristol, UK."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1017\/S1466046606060224","article-title":"Using unmanned aerial vehicles for rangelands: Current applications and future potentials","volume":"8","author":"Rango","year":"2006","journal-title":"Environ. Pract."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2535","DOI":"10.1080\/01431161.2016.1277043","article-title":"Drone-based land-cover mapping using a fuzzy unordered rule induction algorithm integrated into object-based image analysis","volume":"38","author":"Kalanter","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Poblete-Echeverr\u00eda, C., Omeldo, G.F., Ingram, B., and Bardeen, M. (2017). Detection and segmentation of vine canopy in ultra-high spatial resolution RGB imagery obtained from unmanned aerial vehicle (UAV): A case study in a commercial vineyard. Remote Sens., 9.","DOI":"10.3390\/rs9030268"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2903","DOI":"10.1080\/01431161.2016.1277045","article-title":"UAV and TLS for monitoring a creek in an alpine environment, Styria, Austria","volume":"38","author":"Seier","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Weiss, M., and Baret, F. (2017). Using 3D point clouds derived from UAV RGB imagery to describe vineyard 3D macrosStructure. Remote Sens., 9.","DOI":"10.3390\/rs9020111"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2603","DOI":"10.1080\/01431161.2016.1278313","article-title":"Automatic mapping of land surface elevation changes from UAV-based imagery","volume":"38","author":"Lizarazo","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1111\/wre.12026","article-title":"Potential uses of small unmanned aircraft systems (UAS) in weed research","volume":"53","author":"Rasmussen","year":"2013","journal-title":"Weed Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1007\/s11119-012-9274-5","article-title":"The application of small unmanned aerial systems for precision agriculture: A review","volume":"13","author":"Zhang","year":"2012","journal-title":"Precis. Agric."},{"key":"ref_51","first-page":"583","article-title":"Archeological site monitoring: UAV photogrammetry can be an answer","volume":"Volume XXXIX-B5","author":"Shortis","year":"2012","journal-title":"Proceedings of the XXII ISPRS Congress: Imaging a Sustainable Future"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1175\/JTECH-D-12-00036.1","article-title":"Three-dimensional UAV-based atmospheric tomography","volume":"30","author":"Rogers","year":"2013","journal-title":"J. Atmos. Oceanic Technol."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Kalacska, M., Lucanus, O., Sousa, L., Vieira, T., and Arroyo-Mora, J.P. (2018). Freshwater fish habitat complexity mapping using above and underwater structure-from-motion photogrammetry. Remote Sens., 10.","DOI":"10.3390\/rs10121912"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Meneses, N.C., Brunner, F., Baier, S., Geist, J., and Schneider, T. (2018). Quantification of extent density, and status of aquatic reed beds using point clouds derived from UAV\u2013RGB imagery. Remote Sens., 10.","DOI":"10.3390\/rs10121869"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2883","DOI":"10.1080\/01431161.2017.1280636","article-title":"Comparing remote-sensing techniques collecting bathymetric data from a gravel-bed river","volume":"38","author":"Shintani","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Husson, E., Reese, H., and Ecke, F. (2016). Combining spectral data and a DSM from UAS-images for improved classification of non-submerged aquatic vegetation. Remote Sens., 9.","DOI":"10.3390\/rs9030247"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Casado, M.R., Gonzalez, R.B., Wright, R., and Bellamy, P. (2016). Quantifying the effect of aerial imagery resolution in automated hydromorphological river characterization. Remote Sens., 8.","DOI":"10.3390\/rs8080650"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Carvajal-Ram\u00edrez, F., da Silva, J.R.M., Ag\u00fcera-Vega, F., Mart\u00ednez-Carricondo, P., Serrano, J., and Moral, F.J. (2019). Evaluation of fire seve-rity indices based on pre- and post-fire multispectral imagery sensed from UAV. Remote Sens., 11.","DOI":"10.3390\/rs11090993"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"2954","DOI":"10.1080\/01431161.2017.1285083","article-title":"An integrated UAV-borne lidar system for 3D habitat mapping in three forest ecosystems across China","volume":"38","author":"Guo","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Nevalainen, O., Honkavaara, H., Tuominen, S., Viljanen, N., Hakala, T., Yu, X., Hyypp\u00e4, J., Saari, H., P\u00f6l\u00f6nen, I., and Imai, N.N. (2017). Individual tree detection and classification with UAV-based photogrammetric point clouds and hyperspectral imaging. Remote Sens., 9.","DOI":"10.3390\/rs9030185"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Kvicera, M., Perez-Fontan, F., and Pechac, P. (2017). A new propagation channel synthesizer for UAVs in the presence of tree canopies. Remote Sens., 9.","DOI":"10.3390\/rs9020151"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"2427","DOI":"10.1080\/01431161.2016.1252477","article-title":"Forestry applications of UAVs in Europe: A review","volume":"38","author":"Torresan","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Kachamba, D.J., \u00d8rka, H.O., Gobakken, T., Eid, T., and Mwase, W. (2016). Biomass Estimation Using 3D Data from Unmanned Aerial Vehicle Imagery in a Tropical Woodland. Remote Sens., 8.","DOI":"10.3390\/rs8110968"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"2818","DOI":"10.1080\/01431161.2016.1275058","article-title":"Autonomous cyanobacterial harmful algal blooms monitoring using multirotor UAS","volume":"38","author":"Lyu","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Long, N., Millescamps, B., Guillot, B., Pouget, F., and Bertin, X. (2016). Monitoring the topography of a dynamic tidal inlet using UAV imagery. Remote Sens., 8.","DOI":"10.3390\/rs8050387"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Hodgson, A., Kelly, N., and Peel, D. (2013). Unmanned aerial vehicles (UAVs) for surveying marine fauna: A dugong case study. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0079556"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.isprsjprs.2015.02.009","article-title":"UAV photogrammetry for topographic monitoring of coastal areas","volume":"104","author":"Goncalves","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"2199","DOI":"10.1080\/01431161.2016.1239288","article-title":"Using unmanned aerial vehicles for high-resolution remote sensing to map invasive Phragmites australis in coastal wetlands","volume":"38","author":"Samiappan","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Su, L., and Gibeaut, J. (2017). Using UAS hyperspatial RGB imagery for identifying beach zones along the South Texas coast. Remote Sens., 9.","DOI":"10.3390\/rs9020159"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1260","DOI":"10.2112\/JCOASTRES-D-15-00005.1","article-title":"Coastal and environmental remote sensing from unmanned aerial vehicles: An overview","volume":"31","author":"Klemas","year":"2015","journal-title":"J. Coast. Res."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.3390\/rs10091331","article-title":"Mapping and classification of ecologically sensitive marine habitats using unmanned aerial vehicle (UAV) imagery and object-based image analysis (OBIA)","volume":"10","author":"Ventura","year":"2018","journal-title":"Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Papakonstantinou, A., Stamati, C., and Topouzelis, K. (2020). Comparison of true-color and multispectral unmanned aerial systems imagery for marine habitat mapping using object-based image analysis. Remote Sens., 12.","DOI":"10.3390\/rs12030554"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Rende, S.F., Bosman, A., Di Mento, R., Bruno, F., Lagudi, A., Irving, A.D., Dattola, L., Di Giambattista, L., Lanera, P., and Proietti, R. (2020). Ultra-High-Resolution Mapping of Posidonia oceanica (L.) Delile Meadows through Acoustic, Optical Data and Object-based Image Classification. J. Mar. Sci. Eng., 8.","DOI":"10.3390\/jmse8090647"},{"key":"ref_74","first-page":"277","article-title":"Generation of large-scale map of surface sedimentary facies in intertidal zone by using UAV data and object-based image analysis (OBIA)","volume":"36","author":"Kim","year":"2020","journal-title":"Korean J. Remote Sens."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"012037","DOI":"10.1088\/1755-1315\/98\/1\/012037","article-title":"Benthic habitat mapping by combining lyzenga\u2019s optical model and relative water depth model in Lintea Island, Southeast Sulawesi. The 5th Geoinformation Science Symposium","volume":"98","author":"Hafizt","year":"2017","journal-title":"IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_76","first-page":"59","article-title":"Coral reef spatial distribution in Wangiwangi island waters, Wakatobi","volume":"7","author":"Arifin","year":"2015","journal-title":"J. Ilmu Teknol. Kelaut. Trop."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"73","DOI":"10.14203\/mri.v39i2.87","article-title":"Suitability analysis of multispectral satellite sensors for mapping coral reefs in Indonesia case study: Wakatobi marine national park","volume":"39","author":"Adji","year":"2014","journal-title":"Mar. Res. Indones."},{"key":"ref_78","first-page":"137","article-title":"Beach characteristics of Wakatobi National Park to support marine eco-tourism: A case study of Wangiwangi island","volume":"3","author":"Purbani","year":"2014","journal-title":"Depik"},{"key":"ref_79","unstructured":"Balai Taman Nasional Wakatobi (2009). Informasi Taman Nasional Wakatobi, Balai Taman Nasional Wakatobi."},{"key":"ref_80","unstructured":"Supriatna, J. (2008). Melestarikan Alam Indonesia, Yayasan Obor."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"151","DOI":"10.20473\/jipk.v4i2.11566","article-title":"Potensi dan kesesuaian lahan budidaya rumput laut (Kappaphycus alvarezii) di sekitar perairan Kab. Wakatobi Prov. Sulawesi Tenggara","volume":"4","author":"Rangka","year":"2012","journal-title":"J. Ilm. Perikan. Kelaut."},{"key":"ref_82","unstructured":"DroneDeploy (2017). Drone Buyer\u2019s Guide: The Ultimate Guide to Choosing a Mapping Drone for Your Business, DroneDeploy."},{"key":"ref_83","unstructured":"DroneDeploy (2017). Crop Scouting with Drones: Identifying Crop Variability with UAVs (a Guide to Evaluating Plant Health and Detecting Crop Stress with Drone Data), DroneDeploy."},{"key":"ref_84","unstructured":"Da-Jiang Innovations Science and Technology (2016). Phantom 3 Professional: User Manual, DJI."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Congalton, R.G., and Green, K. (2009). Assessing the Accuracy of Remotely Sensed Data Principles and Practices, CRC Taylor & Francis. [2nd ed.].","DOI":"10.1201\/9781420055139"},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Frouin, R.J., Andrefouet, S., Kawamura, H., Lynch, M.J., Pan, D., and Platt, T. (2008). Evaluating eight field and remote sensing approaches for mapping the benthos of three different coral reef environments in Fiji. Remote Sensing of Inland, Coastal, and Oceanic Waters, SPIE\u2014The International Society for Optical Engineering.","DOI":"10.1117\/12.804806"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/s00338-016-1522-0","article-title":"Mapping coral reefs using consumer-grade drones and structure from motion photogrammetry techniques","volume":"36","author":"Casella","year":"2017","journal-title":"Coral Reefs"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"407","DOI":"10.14358\/PERS.71.12.1407","article-title":"Acquisition of through-water aerial survey images: Surface effects and the prediction of sun glitter and subsurface illumination","volume":"71","author":"Mount","year":"2005","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1080\/14498596.2007.9635106","article-title":"Rapid monitoring of extent and condition of seagrass habitats with aerial photography \u201cmega- quadrats\u201d","volume":"52","author":"Mount","year":"2007","journal-title":"Spat. Sci."},{"key":"ref_90","unstructured":"Green, E., Edwards, A.J., and Clark, C. (2000). Remote Sensing Handbook for Tropical Coastal Management, Unesco Pub."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based image analysis for remote sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogram"},{"key":"ref_92","doi-asserted-by":"crossref","unstructured":"Navulur, K. (2007). Multispectral Image Analysis Using the Object-Oriented Paradigm, Taylor and Francis Group, LLC.","DOI":"10.1201\/9781420043075"},{"key":"ref_93","unstructured":"Trimble (2014). Ecognition Developer: User Guide, Trimble Germany GmbH."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"5047","DOI":"10.1080\/01431160701258062","article-title":"Mapping the distribution of coral reefs and associated sublittoral habitats in Pacific Panama: A comparison of optical satellite sensors and classification methodologies","volume":"28","author":"Benfield","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_95","unstructured":"Zitello, A.G., Bauer, L.J., Battista, T.A., Mueler, P.W., Kendall, M.S., and Monaco, M.E. (2009). Shallow-Water Benthic Habitats of St. Jhon, U.S. Virgin Island, NOS NCCOS 96; NOAA Technical Memorandum."},{"key":"ref_96","unstructured":"Ahmad, A., Tahar, K.N., Udin, W.S., Hashim, K.A., Darwin, N., Room, M.H.M., Hamid, N.F.A., Azhar, N.A.M., and Azmi, S.M. (December, January 29). Digital aerial imagery of unmanned aerial vehicle for various applications. Proceedings of the IEEE International Conference on System, Computing and Engineering, Penang, Malaysia."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1080\/19475705.2013.802748","article-title":"Evaluation of various image classification techniques on Landsat to identify coral reefs","volume":"5","author":"Kondraju","year":"2013","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.isprsjprs.2010.11.001","article-title":"Support vector machines in remote sensing: A review","volume":"66","author":"Mountrakis","year":"2011","journal-title":"ISPRS J. Photogramm."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1007\/s13157-012-0373-x","article-title":"Object-based vegetation mapping in the Kissimmee river watershed using hymap data and machine learning techniques","volume":"33","author":"Zhang","year":"2013","journal-title":"Wetlands"},{"key":"ref_100","unstructured":"Afriyie, E.O., Mariano, V.Y., and Luna, D.A. (2015, January 19\u201323). Digital aerial images for coastal remote sensing application. In Proceeding of the 36th Asian conference on remote sensing, Fostering Resilient Growth in Asia, Quezon City, Philippines."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"381","DOI":"10.29244\/jitkt.v10i2.21039","article-title":"Object based mapping on benthic habitat using Sentinel-2 imagery of the Wangiwangi island waters of the Wakatobi District","volume":"10","author":"Mastu","year":"2018","journal-title":"J. Ilmu Teknol. Kelaut. Trop."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1364\/AO.39.000456","article-title":"Remote-sensing reflectance determinations in the coastal ocean environment: Impact of instrumental characteristics and environmental variability","volume":"39","author":"Toole","year":"2000","journal-title":"Appl. Opt."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4452\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:26:35Z","timestamp":1760167595000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4452"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,5]]},"references-count":102,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13214452"],"URL":"https:\/\/doi.org\/10.3390\/rs13214452","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,5]]}}}