Published online June 29, 2007
Digital Elevation Accuracy and Grid Cell Size: Effects on Estimated Terrain Attributes Robert H. Erskine* Timothy R. Green USDA-ARS Agricultural Systems Research Unit 2150 Centre Ave. Bldg. D Suite 200 Fort Collins, CO 80526
Jorge A. Ramirez Dep. of Civil Engineering Colorado State Univ. Fort Collins, CO 80523
Lee H. MacDonald Dep. of Forest Rangeland, and Watershed Stewardship Colorado State Univ. Fort Collins, CO 80523
Terrain attributes are commonly used to explain the spatial variability of agronomic, pedologic, and hydrologic variables. The terrain attributes studied here (elevation, slope, aspect, and curvature) are estimated readily from digital elevation models (DEMs), but questions remain about how the accuracy and sample spacing of the elevation data affect the estimated attributes. The main objective of this study was to quantify differences in each terrain attribute due to factors affecting DEM accuracy and grid cell size. Three data sources were compared: (i) real-time kinematic global positioning system (RTKGPS); (ii) satellite-differentially corrected global positioning system (DGPS); and (iii) U.S. Geological Survey (USGS) 30-m DEMs. The GPS data from three undulating agricultural fields in northeastern Colorado were interpolated onto 5-, 10-, 20-, and 30-m grid DEMs. The DGPS and USGS DEMs produced similar elevation differences relative to RTKGPS DEMs, but elevation differences in USGS DEMs were more spatially correlated. Estimates of curvature were highly sensitive to DEM differences and the sensitivity of slope, aspect, and curvature estimates decreased as grid cell size increased. The impacts of DEM accuracy and grid cell size were investigated using correlations between wheat (Triticum aestivum L.) grain yields and estimated terrain attributes. The highest correlation coefficients were obtained using RTKGPS data, and decreasing the sample spacing or grid cell size below 30 m did not consistently improve the correlations. These analyses on agricultural lands indicate the importance of accurate elevation data for detailed terrain analyses on grid cell sizes of 30 m or less. Abbreviations: DEM, digital elevation model; DGPS, satellite-differentially corrected global positioning system; GPS, global positioning system; RMSD, root mean squared difference; RMSE, root mean squared error; RTKGPS, real-time kinematic global positioning system.
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Soil Sci. Soc. Am. J. 71:1371–1380 doi:10.2136/sssaj2005.0142 Received 4 May 2005. *Corresponding author (
[email protected]). © Soil Science Society of America 677 S. Segoe Rd. Madison WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.
SSSAJ: Volume 71: Number 4 • July–August 2007
cell size (Chang and Tsai, 1991; Jenson, 1991; Panuska et al., 1991; Wolock and Price, 1994; Zhang and Montgomery, 1994; Thieken et al., 1999; Thompson et al., 2001). Digital elevation model accuracy and grid cell size are related intrinsically to the data source and sampling method. Elevation data can be measured very accurately using a dualfrequency RTKGPS, which is comprised of an on-site base GPS for differential correction and a rover GPS for data collection. The RTKGPS data are typically accurate within 0.01 m RMSE horizontally and 0.02 m RMSE vertically based on static measurements. Rapid data acquisition is possible by mounting the rover GPS on a vehicle and taking measurements while driving the terrain. Using this approach, RTKGPS can be used to create DEMs in agricultural lands. Elevation errors for RTKGPSderived elevation contours were
