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TitleMapping and monitoring temperate intertidal habitats: an object-based approach
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LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorLightfoot, P; Scott, C; Polunin, N; Fitzsimmons, C
SourceProgram and abstracts: 2017 GeoHab Conference, Dartmouth, Nova Scotia, Canada; by Todd, B JORCID logo; Brown, C J; Lacharité, M; Gazzola, V; McCormack, E; Geological Survey of Canada, Open File 8295, 2017 p. 79, Open Access logo Open Access
LinksGeoHab 2017
PublisherNatural Resources Canada
Meeting2017 GeoHab: Marine Geological and Biological Habitat Mapping; Dartmouth, NS; CA; May 1-4, 2017
Documentopen file
Mediaon-line; digital
RelatedThis publication is contained in Program and abstracts: 2017 GeoHab Conference, Dartmouth, Nova Scotia, Canada
File formatpdf
Subjectsmarine geology; surficial geology/geomorphology; environmental geology; geophysics; mapping techniques; oceanography; marine environments; coastal studies; conservation; marine organisms; marine ecology; resource management; biological communities; environmental studies; ecosystems; intertidal environment; remote sensing; planning; Biology; monitoring; unmanned aerial vehicles
ProgramOffshore Geoscience
Released2017 09 26
AbstractIntertidal habitat maps are needed at both fine and coarse scales to monitor change and inform conservation and management, but current methods of field survey and expert interpretation of aerial imagery can be time-consuming and subjective. Object-based image analysis (OBIA) of remote sensing data is an increasingly employed method for producing habitat or land cover maps. Users create automated workflows to segment imagery, creating ecologically meaningful objects which are then classified based on their spectral or geometric properties, relationships to other objects and contextual data.
Our research evaluates the potential of OBIA and remote sensing data for planning, managing and monitoring temperate intertidal Marine Protected Areas. We developed and tested OBIA workflows for interpreting ultra-high resolution imagery collected by an unmanned aerial vehicle (UAV) to map intertidal habitats at two thematic scales, comparing the accuracy, consistency and reproducibility of three supervised classification approaches. To evaluate the change-detection capability of OBIA in the intertidal environment, we developed and compared two OBIA methods for quantifying change in extent and distribution of habitats from freely available aerial and LiDAR time series data.
This talk will present and discuss our findings. We demonstrate that OBIA offers robust methods of mapping intertidal habitats from ultra-high resolution UAV imagery (mean accuracy 83.4% ± 3.8%) and lower resolution aerial and LiDAR imagery (mean accuracy 71.4% ± 1.6%) and of detecting change at different levels of sensitivity. Developed in partnership with the responsible monitoring authorities, OBIA methods could integrate ecological knowledge and remote sensing data as a basis for cost-effective intertidal monitoring protocols, providing solutions both for large-scale rapid assessment and more targeted, detailed surveys.
Summary(Plain Language Summary, not published)
The sixteenth annual GeoHab Conference was held this year (2017) at the Waterfront Campus of the Nova Scotia Community College in Dartmouth, Nova Scotia, Canada.

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