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The use of small unmanned aerial system (UAS)-based structure-from-motion (SfM; photogrammetry) and LiDAR point clouds has been widely discussed in the remote sensing community. Here, we compared multiple aspects of the SfM and the LiDAR point clouds, collected concurrently in five UAS flights experimental fields of a short crop (snap bean), in order to explore how well the SfM approach performs compared with LiDAR for crop phenotyping. The main methods include calculating the cloud-to-mesh distance (C2M) maps between the preprocessed point clouds, as well as computing a multiscale model-to-model cloud comparison (M3C2) distance maps between the derived digital elevation models (DEMs) and crop height models (CHMs). We also evaluated the crop height and the row width from the CHMs and compared them with field measurements for one of the data sets. Both SfM and LiDAR point clouds achieved an average RMSE of ~0.02 m for crop height and an average RMSE of ~0.05 m for row width. The qualitative and quantitative analyses provided proof that the SfM approach is comparable to LiDAR under the same UAS flight settings. However, its altimetric accuracy largely relied on the number and distribution of the ground control points.
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Deriving Land and Water Surface Elevations in the Northeastern Yucatán Peninsula Using PPK GPS and UAV-Based Structure from Motion
While UAV-based imaging methods such as drone lidar scanning (DLS) and Structure from Motion (SfM) are now widely used in geographic research, accurate water surface elevation (WSE) measurement remains a difficult problem, as water absorbs wavelengths commonly used for lidar and SfM feature matching fails on these dynamic surfaces. We present a methodology for measuring WSE in a particularly challenging environment, the Yucatán Peninsula, where cenotes – exposed, water-filled sinkholes – provide an observation point into the critically important regional groundwater supply. In the northeastern Yucatán, elevations are very close to sea level, the area is of low relief, and the near-vertical edges of the walls of the cenotes complicate the use of the so-called “water edge” technique for WSE measurement. We demonstrate how post-processing kinematic (PPK) correction of even a single Real Time Kinematic (RTK) Global Positioning System (GPS) unit can be used to finely register the SfM-derived point cloud, and present evidence from both simulations and an empirical study that quantify the effect of “dip” in SfM-based environmental reconstructions. Finally, we present a statistical analysis of the problem of “thick” or “fuzzy” point clouds derived from SfM, with particular emphasis on their interactions with WSE measurement.
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- Award ID(s):
- 1852290
- PAR ID:
- 10213699
- Date Published:
- Journal Name:
- Papers in Applied Geography
- ISSN:
- 2375-4931
- Page Range / eLocation ID:
- 1 to 22
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1080/23754931.2021.1871937
