A Methodology to Characterize Vertical Accuracies in Lidar-derived Products at Landscape Scales
Light detection and ranging (lidar) is the premier technology for high-resolution elevation measurements in complex landscapes. Lidar error assessments allow for objective interpretation of Digital Elevation Models (DEMs) and products reliant on these layers. The purpose of this
study is to spatially estimate the vertical error of a lidar-derived DEM across seven cover types through modeling of field survey data. We use thirty-four variables and ground-based field survey data in a Random Forest regression to predict elevation error. Four variables captured the variability
within the lidar errors, with three variables relevant to the distribution of returns within the vegetation and one relating to the terrain form. Good agreement was observed when comparing the survey against the model predictions (μ = .0.02 m, s = 0.13 m, and RMSE = 0.14 m). With most lidar
products reliant upon accurate production of DEMs, providing spatially explicit assessments of uncertainty at the landscape level will increase user confidence in lidar products.
Document Type: Research Article
Publication date: 01 August 2013
- The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.
Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies. - Editorial Board
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