Effects of Digital Elevation Model Resolution on Unmanned Aerial Vehicle-Based Topographic Change Detection in Human-Altered Landscapes

UAV-based topographic change detection is widely used in geoscience communities. The change detection involves comparison of two digital elevation models (DEMs) produced by UAV surveys, which are affected by the DEM resolution. Coarse resolution DEMs introduce errors in change detection, but the DEM resolution effect remains poorly understood. Moreover, effective strategies for mitigating the resolution effect have yet to be investigated. This study generated UAV-based DEMs at resolutions ranging from 0.1 m to 10 m with various resampling methods. The impact of DEM resolution on topographic change detection was then evaluated by analyzing the difference of DEM (DoD) and volume budget errors with indices such as mean error (ME), standard deviation (STD), and Moran’s I. The results from two human-altered landscapes showed that the random errors of DoD increase rapidly with the DEM resolution coarsening, while DoD systematic errors (spatial distribution of errors) become stable after 4 m resolution. The volume budget errors also increase with DEM coarsening. Coarser resolution DEMs tend to underestimate the volume budget (gross erosion, gross deposition, and net changes). Moreover, selecting an appropriate method for generating DEM is beneficial in decreasing the errors caused by the resolution effect. Among the seven methods (MAX, MIN, MEAN, BIL, NEAR, NEB, and TIN), the BIL method is optimum for mitigating both DoD and volume errors. The NEAR, NEB, and TIN methods are equivalent, and they are superior to the aggregation methods (MAX, MIN, MEAN). The slope of DoD (SDoD) should be considered when selecting a resolution for change detection. Large errors tend to appear in areas with large SDoD and vice versa. Coarse resolution DEMs are tolerable in areas with low SDoD, while high resolution DEMs are necessary in areas with large SDoD.