Mapping of coral reefs using hyperspectral CASI data; a case study: Fordata, Tanimbar, Indonesia

Bertels, Luc; Vanderstraete, Tony; Coillie, Samya Van; Knaeps, Els; Sterckx, Sindy; Goossens, Rudi; Deronde, Bart

doi:10.1080/01431160701408469

Cited by 55 publications

(33 citation statements)

References 34 publications

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“…The reference spectral library should have contained spectra for each benthos and substrate type at each depth mapped, which was not the case. Using site specific optical differences, rather than location-independent spectral signatures, also limits the application of the mapping approach [8]. Kutser et al [14] classified Hyperion image data using forward modelling of in-situ spectra to at-sensor radiance with raw image data, and remote sensing reflectance just above the water surface with atmospherically corrected imagery.…”

Section: Discussionmentioning

confidence: 99%

“…The Compact Airborne Spectrographic Imager (CASI) is a high spatial resolution hyperspectral airborne sensor, that has been used to map coral reef environments using both unsupervised [8] and supervised [9][10][11] classification approaches. Using a spectral reference library to supervise image classification has been shown to increase classification accuracy in comparison to supervised approaches using image-based statistics [12,13], and has the potential to automate coral reef mapping procedures independent of ancillary field surveys [2,14,15].…”

Section: Introductionmentioning

confidence: 99%

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Mapping Coral Reef Benthos, Substrates, and Bathymetry, Using Compact Airborne Spectrographic Imager (CASI) Data

et al. 2014

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This study used a reef-up approach to map coral reef benthos, substrates and bathymetry, with high spatial resolution hyperspectral image data. It investigated a physics-based inversion method for mapping coral reef benthos and substrates using readily available software: Hydrolight and ENVI. Compact Airborne Spectrographic Imager (CASI) data were acquired over Heron Reef in July 2002. The spectral reflectance of coral reef benthos and substrate types were measured in-situ, and using the HydroLight 4.2 radiative transfer model a spectral reflectance library of subsurface reflectance was simulated using water column depths from 0.5-10.0 m at 0.5 m intervals. Using the Spectral Angle Mapper algorithm, sediment, benthic micro-algae, algal turf, crustose coralline algae, macro-algae, and live coral were mapped with an overall accuracy of 65% to a depth of around 8.0 m; in waters deeper than 8.0 m the match between the classified image and field validation data was poor. Qualitative validation of the maps showed accurate mapping of areas dominated by sediment, benthic micro-algae, algal turf, live coral, and macro-algae. A bathymetric map was produced for water column depths 0.5-10.0 m, at 0.5 m intervals, and showed high correspondence with in-situ sonar data (R 2 value of 0.93). OPEN ACCESSRemote Sens. 2014, 6 6424

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mapping Coral Reef Benthos, Substrates, and Bathymetry, Using Compact Airborne Spectrographic Imager (CASI) Data

et al. 2014

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“…All the methods described have been successfully used in this type of situation; a few examples are the Lyzenga method used for bathymetry [9], the Hedley method for benthic cover mapping and classification [65], the Goodman method for classification based on a semi-analytical optical model [66]. However, there have been few comparative studies.…”

Section: Comments On the Methodsmentioning

confidence: 99%

Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: a Review of Methods for Visible and Near-Infrared Wavelengths

2009

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Sun glint, the specular reflection of light from water surfaces, is a serious confounding factor for remote sensing of water column properties and benthos. This paper reviews current techniques to estimate and remove the glint radiance component from imagery. Methods for processing of ocean color images use statistical sea surface models to predict the glint from the sun and sensor positions and wind data. Methods for higher resolution imaging, used in coastal and shallow water mapping, estimate the glint radiance from the near-infrared signal. The effects of some current methods are demonstrated and possibilities for future techniques are briefly addressed.

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“…Remote sensing data have proved to be extremely useful in providing maps of marine benthic habitats [13][14][15][16][17][18]. Different authors have used image-based classification method, which can provide benthic habitat maps from the coastal areas, but require extensive field studies [19][20][21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Classifying the Baltic Sea Shallow Water Habitats Using Image-Based and Spectral Library Methods

Vahtmäe

Kutser

2013

Remote Sensing

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Abstract:The structure of benthic macrophyte habitats is known to indicate the quality of coastal water. Thus, a large-scale analysis of the spatial patterns of coastal marine habitats enables us to adequately estimate the status of valuable coastal marine habitats, provide better evidence for environmental changes and describe processes that are behind the changes. Knowing the spatial distribution of benthic habitats is also important from the coastal management point of view.A big challenge in remote sensing mapping of benthic habitats is to define appropriate mapping classes that are also meaningful from the ecological point of view. In this study, the benthic habitat classification scheme was defined for the study areas in the relatively turbid north-eastern Baltic Sea coastal environment. Two different classification methods-image-based and the spectral library-method were used for image classification. The image-based classification method can provide benthic habitat maps from coastal areas, but requires extensive field studies. An alternative approach in image classification is to use measured and/or modelled spectral libraries. This method does not require fieldwork at the time of image collection if preliminary information about the potential benthic habitats and their spectral properties, as well as variability in optical water properties exists from earlier studies. A spectral library was generated through radiative transfer model HydroLight computations using measured reflectance spectra from representative benthic substrates and water quality measurements.Our previous results have shown that benthic habitat mapping should be done at high spatial resolution, owing to the small-scale heterogeneity of such habitats in the Estonian OPEN ACCESSRemote Sens. 2013, 5 2452 coastal waters. In this study, the capability of high spatial resolution hyperspectral airborne a Compact Airborne Spectrographic Imager (CASI) sensor and a high spatial resolution multispectral WorldView-2 satellite sensor were tested for mapping benthic habitats. Initial evaluations of habitat maps indicate that image-based classification provides higher quality benthic maps compared to the spectral library method.

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Mapping of coral reefs using hyperspectral CASI data; a case study: Fordata, Tanimbar, Indonesia

Cited by 55 publications

References 34 publications

Mapping Coral Reef Benthos, Substrates, and Bathymetry, Using Compact Airborne Spectrographic Imager (CASI) Data

Mapping Coral Reef Benthos, Substrates, and Bathymetry, Using Compact Airborne Spectrographic Imager (CASI) Data

Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: a Review of Methods for Visible and Near-Infrared Wavelengths

Classifying the Baltic Sea Shallow Water Habitats Using Image-Based and Spectral Library Methods

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