Publication Date:
2022-05-26
Description:
© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 9 (2017): 1020, doi:10.3390/rs9101020.
Description:
The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when 〈50 cm) have little influence on the classification accuracy.
Description:
This project was funded by the U.S. Geological Survey (USGS) Coastal and Marine Geology
Program and the Department of the Interior Northeast Climate Science Center.
Keywords:
Coastal change
;
Drones
;
Elevation model
;
Geomorphic feature extraction
;
Land cover classification
;
Photogrammetry
;
Structure-from-motion
;
Unmanned aerial systems
Repository Name:
Woods Hole Open Access Server
Type:
Article
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