Assessing the vertical accuracy of digital elevation models by quality level and land cover
The vertical accuracy of elevation data in coastal environments is critical because small variations in elevation can affect an area’s exposure to waves, tides, and storm-related flooding. Elevation data contractors typically quantify the vertical accuracy of lidar-derived digital elevation models (DEMs) on a per-project basis to gauge whether the datasets meet quality and accuracy standards. Here, we collated over 5200 contractor elevation checkpoints along the Atlantic and Gulf of Mexico coasts of the United States that were collected for project-level analyses produced for assessing DEMs acquired for the U.S. Geological Survey’s Three-Dimensional Elevation Program. We used land cover data to quantify non-vegetated vertical accuracy and vegetated vertical accuracy statistics (overall and by point spacing bins) and assessed elevation error by land cover class. We found the non-vegetated vertical accuracy had an overall root mean square error of 6.9 cm and vegetated areas had a 95th percentile vertical error of 22.3 cm. Point spacing was generally positively correlated to elevation accuracy, but sample size limited the ability to interpret results from accuracy by land cover, particularly in wetlands. Based on the specific questions a researcher may be asking, use of literature or fieldwork could assist with enhancing error statistics in underrepresented classes.
Citation Information
Publication Year | 2024 |
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Title | Assessing the vertical accuracy of digital elevation models by quality level and land cover |
DOI | 10.1080/2150704X.2024.2368924 |
Authors | Minoo Han, Nicholas Enwright, Dean B. Gesch, Jason M. Stoker, Jeffrey J. Danielson, Christopher J. Amante |
Publication Type | Article |
Publication Subtype | Journal Article |
Series Title | Remote Sensing Letters |
Index ID | 70256017 |
Record Source | USGS Publications Warehouse |
USGS Organization | Earth Resources Observation and Science (EROS) Center; Wetland and Aquatic Research Center |