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Sensitivity of watershed attributes to spatial resolution and interpolation method of LiDAR DEMs in three distinct landscapes
Author(s) -
Goulden T.,
Hopkinson C.,
Jamieson R.,
Sterling S.
Publication year - 2014
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2013wr013846
Subject(s) - inverse distance weighting , digital elevation model , watershed , remote sensing , lidar , kriging , elevation (ballistics) , scale (ratio) , scaling , interpolation (computer graphics) , image resolution , hydrology (agriculture) , geography , multivariate interpolation , geology , cartography , geometry , mathematics , statistics , animation , computer graphics (images) , geotechnical engineering , machine learning , artificial intelligence , computer science , bilinear interpolation
This study investigates scaling relationships of watershed area and stream networks delineated from LiDAR DEMs. The delineations are tested against spatial resolution, including 1, 5, 10, 25, and 50 m, and interpolation method, including Inverse Distance Weighting (IDW), Moving Average (MA), Universal Kriging (UK), Natural Neighbor (NN), and Triangular Irregular Networks (TIN). Study sites include Mosquito Creek, Scotty Creek, and Thomas Brook, representing landscapes with high, low, and moderate change in elevation, respectively. Results show scale‐dependent irregularities in watershed area due to spatial resolution at Thomas Brook and Mosquito Creek. The highest sensitivity of watershed area to spatial resolution occurred at Scotty Creek, due to high incidence of LiDAR sensor measurement error and subtle changes in elevation. Length of drainage networks did not show a scaling relationship with spatial resolution, due to algorithmic complications of the stream initiation threshold. Stream lengths of main channels at Thomas Brook and Mosquito Creek displayed systematic increases in length with increasing spatial resolution, described through an average fractal dimension of 1.059. The scaling relationship between stream length and DEM resolution allows estimation of stream lengths from low‐resolution DEMs in the absence of high‐resolution DEMs. Single stream validation at Thomas Brook showed the 1 m DEM produced the lowest length error and highest spatial accuracy, at 3.7% and 71.3%, respectively. Single stream validation at Mosquito Creek showed the 25 m DEM produced the lowest length error, and the 1 m DEM the highest spatial accuracy, at 0.6% and 61.0%, respectively.