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Habitat map of Danajon Bank, Philippines, derived from a high-spatial-resolution multi-spectral satellite image and georeferenced point intercept transect and spot-check survey field data, using an object-based image classification method

The University of Queensland
Associate Professor Chris Roelfsema (Aggregated by) Associate Professor Chris Roelfsema (Aggregated by) Professor Stuart Phinn (Aggregated by) Professor Stuart Phinn (Aggregated by) Roelfsema, Christiaan (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://espace.library.uq.edu.au/view/UQ:410004&rft.title=Habitat map of Danajon Bank, Philippines, derived from a high-spatial-resolution multi-spectral satellite image and georeferenced point intercept transect and spot-check survey field data, using an object-based image classification method&rft.publisher=The University of Queensland&rft.description=A mosaic of two WorldView-2 high resolution multispectral images (Acquisition dates: October 2010 and April 2012), in conjunction with field survey data, was used to create a habitat map of the Danajon Bank, Philippines (10°15'0'' N, 124°08'0'' E) using an object-based approach. To create the habitat map, we conducted benthic cover (seafloor) field surveys using two methods. Firstly, we undertook georeferenced point intercept transects (English et al., 1997). For ten sites we recorded habitat cover types at 1 m intervals on 10 m long transects (n= 2,070 points). Second, we conducted geo-referenced spot check surveys, by placing a viewing bucket in the water to estimate the percent cover benthic cover types (n = 2,357 points). Survey locations were chosen to cover a diverse and representative subset of habitats found in the Danajon Bank. Object-based image analysis, using the field data as calibration data, was used to classify the image mosaic at each of the reef, geomorphic and benthic community levels. The benthic community level segregated the image into a total of 17 pure and mixed benthic classes.&rft.creator=Associate Professor Chris Roelfsema&rft.creator=Associate Professor Chris Roelfsema&rft.creator=Professor Stuart Phinn&rft.creator=Professor Stuart Phinn&rft.creator=Roelfsema, Christiaan&rft.date=2016&rft.coverage=124.616667,10.266667&rft_rights=2016, The University of Queensland&rft_rights= http://creativecommons.org/licenses/by/3.0/deed.en_US&rft_subject=eng&rft_subject=ENVIRONMENTAL SCIENCE AND MANAGEMENT&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Conservation and Biodiversity&rft_subject=Environmental Management&rft.type=dataset&rft.language=English Access the data
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http://creativecommons.org/licenses/by/3.0/deed.en_US

2016, The University of Queensland

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c.roelfsema@uq.edu.au

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A mosaic of two WorldView-2 high resolution multispectral images (Acquisition dates: October 2010 and April 2012), in conjunction with field survey data, was used to create a habitat map of the Danajon Bank, Philippines (10°15'0'' N, 124°08'0'' E) using an object-based approach. To create the habitat map, we conducted benthic cover (seafloor) field surveys using two methods. Firstly, we undertook georeferenced point intercept transects (English et al., 1997). For ten sites we recorded habitat cover types at 1 m intervals on 10 m long transects (n= 2,070 points). Second, we conducted geo-referenced spot check surveys, by placing a viewing bucket in the water to estimate the percent cover benthic cover types (n = 2,357 points). Survey locations were chosen to cover a diverse and representative subset of habitats found in the Danajon Bank. Object-based image analysis, using the field data as calibration data, was used to classify the image mosaic at each of the reef, geomorphic and benthic community levels. The benthic community level segregated the image into a total of 17 pure and mixed benthic classes.

Issued: 2016

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  • Associated with Habitat map of Danajon Bank, Philippines, derived from a high-spatial-resolution multi-spectral satellite image and georeferenced point intercept transect and spot-check survey field data, using an object-based image classification method
    10.1594/PANGAEA.864306

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124.61667,10.26667

124.616667,10.266667

Subjects
Conservation and Biodiversity | Environmental Science and Management | Environmental Sciences | Environmental Management | eng |

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Other Information
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