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Het OWA, het open archief van het Waterbouwkundig Laboratorium heeft tot doel alle vrij toegankelijke onderzoeksresultaten van dit instituut in digitale vorm aan te bieden. Op die manier wil het de zichtbaarheid, verspreiding en gebruik van deze onderzoeksresultaten, alsook de wetenschappelijke communicatie maximaal bevorderen.
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| one publication added to basket [319661] |
Cost-effective coastal habitat mapping: detecting intertidal polychaete aggregations with low-altitude photogrammetry
Alves, R.M.S.; Van Colen, C.; Rabaut, M.; De Wulf, A.; Vincx, M.; Stal, C. (2019). Cost-effective coastal habitat mapping: detecting intertidal polychaete aggregations with low-altitude photogrammetry. Photogramm. Eng. Remote Sens. 85(12): 899-905. https://dx.doi.org/10.14358/PERS.85.12.899
In: Photogrammetric engineering and remote sensing. American Society of Photogrammetry: Falls Church, Va.. ISSN 0099-1112; e-ISSN 2374-8079, meer
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| Abstract |
Intertidal polychaete aggregations may be protected in the European Union under the Habitats Directive framework as reef habitats. Remote reef mapping remains challenging due to severe and dynamic conditions, as well as cover and spatial resolution requirements. This study (1) evaluated kite aerial photography and low-altitude digital photogrammetry to map and monitor intertidal aggregations of a sessile tube-building polychaete, Lanice conchilega (L. conchilega), and (2) developed a protocol for its remote identification. Monthly campaigns yielded 12 aerial image sets which were processed using structure-from-motion into high-precision digital terrain models and orthophoto mosaics. Maximum likelihood classification distinguished L. conchilega from bare sediment with an accuracy of 70% ± 23.2%. Aggregations were delineated by extracting elements of positive elevation from local difference models. The method has proven useful to detect high-value aggregations, distinguishing these consistently. Nevertheless, systematic biases were present during delineation, and further characterisation of reference aggregations may improve detection. |
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