Biodiversity assessment in coral Reef Benthic habitats using hyperspectral images

Abstract. Yuanike, Yulianda F, Bengen DG, Dahuri R, Souhoka J. 2019. A biodiversity assessment of hard corals in dive spots within Dampier Straits Marine Protected Area in Raja Ampat, West Papua, Indonesia. Biodiversitas 20: 1198-1207. Hard coral dominates coral reef ecosystems and has important functions and interactions in communities of marine biota. The structure and diversity of hard coral communities is very important to quantify, especially for the management of coral reef ecosystems. The purpose of this research is to identify the diversity of hard coral types, and quantify the condition of hard coral and their distributions in 10 marine stations in Dampier Straits Marine Protected Areas, Raja Ampat. The research method used was line intercept transects measured at two depths, 3 m and 6 m. The results showed there were 141 hard coral species included in 16 families. The percentage live cover of hard coral was in good conditions with an overall average coverage value of 64,24%. The biodiversity index (H) ranged from 0,84-1,23, the evenness index of species ranged from 0,73-0,94, and the species dominance index ranged from 0,05-0,25, indicating a high biodiversity and a lack of dominance by a single species. Although cover was slightly higher at 3m depth, diversity was slightly higher at 6m depth. In general, the 10 research stations in Dampier Straits has hard coral in good condition and the diversity of hard coral species is very productive and has stable growth compared with other sites in Indonesia.

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Enhancing the detection and classification of coral reef and associated benthic habitats: A hyperspectral remote sensing approach

Journal of Geophysical Research Atmospheres ◽

10.1029/2006jc003892 ◽

2007 ◽

Vol 112 (C8) ◽

Cited By ~ 47

Author(s):

Deepak R. Mishra ◽

Sunil Narumalani ◽

Donald Rundquist ◽

Merlin Lawson ◽

R. Perk

Keyword(s):

Remote Sensing ◽

Coral Reef ◽

Hyperspectral Remote Sensing ◽

Benthic Habitats

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Spatial Analyses of Benthic Habitats to Define Coral Reef Ecosystem Regions and Potential Biogeographic Boundaries along a Latitudinal Gradient

PLoS ONE ◽

10.1371/journal.pone.0030466 ◽

2012 ◽

Vol 7 (1) ◽

pp. e30466 ◽

Cited By ~ 26

Author(s):

Brian K. Walker

Keyword(s):

Coral Reef ◽

Latitudinal Gradient ◽

Spatial Analyses ◽

Coral Reef Ecosystem ◽

Benthic Habitats ◽

Reef Ecosystem

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Towards spatial management of fisheries in the Gulf: benthic diversity, habitat and fish distributions from Qatari waters

ICES Journal of Marine Science ◽

10.1093/icesjms/fsx116 ◽

2017 ◽

Vol 75 (1) ◽

pp. 178-189 ◽

Cited By ~ 1

Author(s):

Mark E M Walton ◽

Jamie Hayes ◽

Mohsin Al-Ansi ◽

Mohamed Abdallah ◽

Ibrahim Al Maslamani ◽

...

Keyword(s):

Coral Reef ◽

Fish Assemblages ◽

Habitat Type ◽

Fish Communities ◽

Video Data ◽

Benthic Habitat ◽

Soft Sediment ◽

Benthic Habitats ◽

Marine Habitats ◽

Spatial Management

Abstract As with many other regions in the world, more complete information on the distribution of marine habitats in the Gulf is required to inform environmental policy, and spatial management of fisheries resources will require better understanding of the relationships between habitat and fish communities. Towed cameras and sediment grabs were used to investigate benthic habitats and associated epifauna, infauna and fish communities in the central Gulf, offshore from the east coast of Qatar, in water depths of between 12 and 52 m. Six different habitats were identified: (i) soft sediment habitats of mud and (ii) sand, and structured habitats of (iii) macro-algal reef, (iv) coral reef, (v) mixed reef, and (vi) oyster bed. The epibenthic community assemblage of the mud habitat was significantly different to that of sand, which in turn differed from the structured habitats of coral reef, mixed reef and oyster bed, with the macroalgal assemblage having similarities to both sand and the other structured habitats. Fish assemblages derived from video data did not differ between habitats, although certain species were only associated with particular habitats. Epibenthic diversity indices were significantly lower in mud, sand and macro-algal habitats, with no differences recorded for fish diversity. Soft sediment grab samples indicated that mud habitats had the highest benthic diversity, with Shannon-Weiner values of >4, and were more diverse than sand with values of 3.3. The study demonstrates high biodiversity in benthic habitats in the central and southwestern Gulf, which may in part be due to the absence of trawling activity in Qatari waters. There is a strong influence of depth on benthic habitat type, so that depth can be used to predict habitat distribution with a high level of accuracy. The presence of outcrops of hard substrata creates a mosaic of patchy shallow structured benthic habitat across extensive areas of the offshore seabed. Such heterogeneity, and the association of commercially exploited fish species with specific habitats, indicates that this region is well suited to a spatial approach to fisheries management.

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Shallow-Water Benthic Habitat Mapping Using Drone with Object Based Image Analyses

Remote Sensing ◽

10.3390/rs13214452 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4452

Author(s):

Bisman Nababan ◽

La Ode Khairum Mastu ◽

Nurul Hazrina Idris ◽

James P. Panjaitan

Keyword(s):

Coral Reef ◽

Shallow Water ◽

Spatial Information ◽

Aerial Photographs ◽

Support Vector ◽

Benthic Habitat ◽

Benthic Habitats ◽

Object Based ◽

Svm Algorithm ◽

Level 2

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’s 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 × 50 cm squared transect of 434 observation points in March–April 2017. The DJI Phantom 3 Pro drone with a spatial resolution of 5.2 × 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.

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