UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery
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Abstract
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.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery |
| Series title | Remote Sensing |
| DOI | 10.3390/rs9101020 |
| Volume | 9 |
| Issue | 10 |
| Year Published | 2017 |
| Language | English |
| Publisher | MDPI |
| Contributing office(s) | Woods Hole Coastal and Marine Science Center |
| Description | 20 p. |
| First page | 1 |
| Last page | 20 |
| Country | United States |
| State | Massachusetts |
| Other Geospatial | Buzzards Bay |
| Google Analytic Metrics | Metrics page |