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  • Applying Airborne LiDAR to ...
    van Ardenne, Lee B.; Chmura, Gail L.

    Remote sensing, 11/2021, Letnik: 13, Številka: 21
    Journal Article

    The determination of rates and stocks of carbon storage in salt marshes, as well as their protection, require that we know where they and their boundaries are. Marsh boundaries are conventionally mapped through recognition of plant communities using aerial photography or satellite imagery. We examined the possibility of substituting the use of 1 m resolution LiDAR-derived digital elevation models (DEMs) and tidal elevations to establish salt marsh upper boundaries on the New Brunswick coasts of the Gulf of St. Lawrence and the Bay of Fundy, testing this method at tidal ranges from ≤2 to ≥4 m. LiDAR-mapped marsh boundaries were verified with high spatial resolution satellite imagery and a subset through field mapping of the upland marsh edge based upon vegetation and soil characteristics, recording the edge location and elevation with a Differential Geographic Positioning System. The results show that the use of high-resolution LiDAR and tidal elevation data can successfully map the upper boundary of salt marshes without the need to first map plant species. The marsh map area resulting from our mapping was ~30% lower than that in the province’s aerial-photograph-based maps. However, the difference was not primarily due to the location of the upper marsh boundaries but more so because of the exclusion of mudflats and large creeks (features that are not valued as carbon sinks) using the LiDAR method that are often mapped as marsh areas in the provincial maps. Despite some minor limitations, the development of DEMs derived from LiDAR can be applied to update and correct existing salt marsh maps along extensive sections of coastlines in less time than required to manually trace from imagery. This is vital information for governments and NGOs seeking to conserve these environments, as accurate mapping of the location and area of these ecosystems is a necessary basis for conservation prioritization indices.