Główne pojęcia
The study compares five roughness descriptors for LiDAR-derived digital elevation models, highlighting the importance of multiple descriptors in characterizing terrain surface roughness.
Streszczenie
The study compares five commonly used roughness descriptors to quantify terrain surface roughness across three terrains with distinct spatial variations. It explores correlations among the quantified roughness maps and investigates the impacts of spatial scales and interpolation methods. The findings emphasize the significance of incorporating multiple descriptors in studies where local roughness values are crucial. Different algorithms yield diverse roughness values, impacting subsequent analyses. The study suggests that the choice of roughness descriptors can influence results significantly, especially in quantitative studies relying on local roughness values.
Statystyki
Terrain surfaces exhibit distinctive spatial variation characteristics: hilly rough, flat rough, and flat smooth.
Average data spacing is 0.63-0.64 meters.
Spatial grid resolution of 1 meter is employed for constructing DEM maps.
Five commonly used descriptors include RMSH, standard deviation of locally detrended residual elevations, standard deviation of residual topography, standard deviation of slope, and standard deviation of curvature.
Cytaty
"The findings highlight both global pattern similarities and local pattern distinctions in the derived roughness maps."
"The choice of roughness descriptors can impact the results of subsequent analyses."
"Greater similarity was observed for rougher terrain surfaces with noisy spatial variations."