Journal
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
Volume 76, Issue 6, Pages 701-712Publisher
AMER SOC PHOTOGRAMMETRY
DOI: 10.14358/PERS.76.6.701
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Funding
- National Science Foundation [EAR 0922307]
- Sierra Nevada Adaptive Management Project
- Division Of Earth Sciences
- Directorate For Geosciences [0922307] Funding Source: National Science Foundation
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This study aims to quantify the effects of topographic variability (measured by coefficient variation of elevation, CV) and lidar (Light Detection and Ranging) sampling density on the DEM (Digital Elevation Model) accuracy derived from several interpolation methods at different spatial resolutions. Interpolation methods include natural neighbor (NN), inverse distance weighted (IDW), triangulated irregular network (TIN), spline, ordinary kriging (OK), and universal kriging (UK). This study is unique in that a comprehensive evaluation of the combined effects of three influencing factors (CV, sampling density, and spatial resolution) on lidar-derived DEM accuracy is carried out using different interpolation methods. Results indicate that simple interpolation methods, such as IDW, NN, and TIN, are more efficient at generating DEMs from lidar data, but kriging-based methods, such as OK and UK, are more reliable if accuracy is the most important consideration. Moreover, spatial resolution also plays an important role when generating DEMs from lidar data. Our results could be used to guide the choice of appropriate lidar interpolation methods for DEM generation given the resolution, sampling density, and topographic variability.
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