Refraction-corrected bathymetric point cloud from the UAS survey of the coral reef off Waiakane, Molokai, Hawaii, 24 June 2018
Dates
Publication Date
2022-03-21
Time Period
2018-06-24
Citation
Logan, J.B., and Storlazzi, C.D., 2022, Aerial imagery and structure-from-motion-derived shallow water bathymetry from a UAS survey of the coral reef off Waiakane, Molokai, Hawaii, June 2018: U.S. Geological Survey data release, https://doi.org/10.5066/P9XZT1FK.
Summary
This portion of the data release presents a bathymetric point cloud from an unoccupied aerial system (UAS) survey of the coral reef off Waiakane, Molokai, Hawaii, on 24 June 2018. The point cloud has been corrected for the effects of refraction using the techniques described in Dietrich (2017a). The point cloud was created from structure-from-motion (SfM) processing of aerial imagery collected using a UAS with a Ricoh GR II digital camera fitted with a circular polarizing filter. During the survey, a pressure sensor was deployed in the survey area to gain an accurate measurement of the water surface elevation (WSE). After a preliminary dense point cloud was derived from SfM processing, the WSE was used to calculate apparent water depths. [...]
Summary
This portion of the data release presents a bathymetric point cloud from an unoccupied aerial system (UAS) survey of the coral reef off Waiakane, Molokai, Hawaii, on 24 June 2018. The point cloud has been corrected for the effects of refraction using the techniques described in Dietrich (2017a). The point cloud was created from structure-from-motion (SfM) processing of aerial imagery collected using a UAS with a Ricoh GR II digital camera fitted with a circular polarizing filter. During the survey, a pressure sensor was deployed in the survey area to gain an accurate measurement of the water surface elevation (WSE). After a preliminary dense point cloud was derived from SfM processing, the WSE was used to calculate apparent water depths. These apparent depths along with the estimated camera positions and orientations were used as inputs for the multi-view refraction correction python script (py_sfm_depth.py) described in Dietrich (2017b). The refraction-corrected point cloud showed a substantial improvement in accuracy over the uncorrected point cloud. When compared to the 2013 U.S. Army Corps of Engineers Topobathy Lidar for the area in the central portion of the data set the vertical RMSE for the refraction-corrected point cloud was 0.241 meters with a mean residual of -0.010 meters, whereas the vertical RMSE for the uncorrected point cloud was 0.426 meters with a mean residual of -0.334 meters (see the Vertical Positional Accuracy Report in the metadata for a complete description of the accuracy analysis). For this data release, the final refraction-corrected point cloud is presented in the LAZ format (LAS 1.2 specification). The point cloud has 35,083,205 points with an average point spacing of 0.07 meters. Each point in the point cloud contains an explicit horizontal and vertical coordinate and red, green, and blue (RGB) color values.
These data were collected to characterize the morphology and rugosity of the shallow fringing coral reef off Waiakane, Molokai, Hawaii, as part of a larger USGS study of nearshore circulation and hydrodynamic properties of coral reefs. The point cloud can be used with geographic information systems (GIS) software or other three-dimensional analysis software for research purposes.
Preview Image
Point cloud and error dist. plots (purple = uncorrected; orange = refr. corr.)