UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery
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.
Citation Information
| Publication Year | 2017 |
|---|---|
| Title | UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery |
| DOI | 10.3390/rs9101020 |
| Authors | Emily J. Sturdivant, Erika Lentz, E. Robert Thieler, Amy S. Farris, Kathryn M. Weber, David P. Remsen, Simon Miner, Rachel E. Henderson |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | Remote Sensing |
| Index ID | 70191276 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | Woods Hole Coastal and Marine Science Center |
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Erika Lentz, PhD
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Rob Thieler, PhD
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Amy S Farris
Oceanographer
Rachel Elizabeth Henderson
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Topographic, imagery, and raw data associated with unmanned aerial systems (UAS) flights over Black Beach, Falmouth, Massachusetts on 18 March 2016
Imagery acquired with unmanned aerial systems (UAS) and coupled with structure-from-motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Surv - Connect
Erika Lentz, PhD
Research GeologistEmailPhoneRob Thieler, PhD
Center DirectorEmailPhoneAmy S Farris
OceanographerEmailPhoneRachel Elizabeth Henderson
Physical ScientistEmail