This article written by Amy S. Farris, et al on monitoring salt marsh shorelines with a UAS recently appeared in Drone Below.
Drones are now a vital tool in assessing the health of salt marshes which are crucial for the ecosystem. Salt marshes provide a critical habitat for many species, decrease storm surge by attenuating waves, improve ecosystem health by cycling nutrients and they sequester carbon. The threat to a healthy existence of salt marshes comes from anthropogenic factors, sea level rise and sediment deficits and can also be influenced by plant–herbivore interactions.
Given the substantial ecosystem services provided by marshes, it is important to be able to measure their extent and seaward edge at high temporal and spatial resolutions. While for individual marsh complexes, un-vegetated and vegetated areas are identified in order to compute actual marsh coverage, use of remote sensing to track the seaward edge along salt marsh shorelines is less evolved.
The shoreline is now often defined as the mean high water (MHW) elevation and is often extracted from light detection and ranging (LIDAR) elevation data. MHW elevations can be found in or calculated with the VDatum tool. The elevation along these transects is found from LIDAR (or other elevation) data and then the location of the MHW elevation is found on each transect. This leads to a datum-based, objective, and reproducible shoreline. Consistent estimates of shoreline change can then be calculated along these transects.
Use of UAV in Study Methods:
A research team which was formed by researchers Amy S. Farris, Zafer Defne and Neil K. Ganju and supported by the U.S. Geological Survey, Woods Hole, USA, developed the marsh edge from elevation data (MEED) method to calculate the “marsh scarp” which is the abrupt elevation change at the edge of most salt marshes. The MEED method calculates slope from elevation data and defines the marsh scarp to be the maximum slope between mean high water and the mean tide level. The team used elevation data lidar; structure from motion (SfM) aerial photogrammetry collected by unmanned aircraft systems (UAS) or unmanned aerial vehicle (UAV) or drone as they are more commonly known.
For the complete article click here.
Citation: Identifying Salt Marsh Shorelines from Remotely Sensed Elevation Data and Imagery, Amy S. Farris, Zafer Defne and Neil K. Ganju, U.S. Geological Survey, Woods Hole, MA 02543, USA
Remote Sens. 2019, 11(15), 1795; https://doi.org/10.3390/rs11151795, https://www.mdpi.com/2072-4292/11/15/1795
Note – If you liked this post click here to stay informed of all of the 3D laser scanning, geomatics, UAS, autonomous vehicle, Lidar News and more. If you have an informative 3D video that you would like us to promote, please forward to email@example.com and if you would like to join the Younger Geospatial Professional movement click here.