Digital Elevation Accuracy and Grid Cell Size: Effects on Estimated Terrain Attributes

Abstract

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.

How does grid-resolution modulate the topographic expression of geomorphic processes?

“…most sensitive to resolution decreases. Work by Erskine et al (2007) considering models of crop yields in Colorado, USA, demonstrated that on relatively flat surfaces, such as agricultural fields, the spatial resolution is less important than the vertical accuracy when predicting crop yields, with significant errors being produced due to centimeter-scale vertical displacements. Decreasing the grid resolution from 5 to 30 m had limited effect on the yield calculations.…”

“…Although considerable work has been carried out on the sensitivity of various factors to grid resolution, much of it has been focused on a specific application (e.g., Wolock and Price, 1994, Schoorl et al, 2000, Erskine et al, 2007, and Sørensen and Seibert, 2007 with few studies considering the impact of DEM grid resolution within a geomorphic context. Here we aim to extend existing methodologies to constrain the utility of low-resolution data products across a suite of geomorphic analyses to understand the following: (1) how hillslope length, topographic curvature, and relief vary with grid resolution; (2) how best to extract channel networks in lower-resolution datasets in order to minimize errors; and (3) whether it is possible to estimate sediment transport coefficients from low-resolution topographic data, where an independent constraint on erosion rate is available.…”

“…However, unlike other key landscape properties such as gradient (Gao, 1997;Wolock and McCabe, 2000;Warren et al, 2004;Vaze et al, 2010), hydrology (Wolock and Price, 1994;Zhang and Montgomery, 1994;Murphy et al, 2008;Wu et al, 2008), or soil characteristics (Schoorl et al, 2000;Erskine et al, 2007), the influence of grid resolution on curvature has not been fully explored, particularly within a geomorphic context. This is particularly important with the proliferation of high-resolution topographic data from lidar, allowing the analysis of curvature on increasingly fine scales.…”

Global terrain classification using 280 m DEMs: segmentation, clustering, and reclassification

“…However, high-resolution DEMs may create considerable problems in terrain classification owing to the appearance of artificial smoothing or cutting of land. An additional method from using the original elevations, instead of their derivatives, will be needed for more detailed classification of plains because the derivatives may emphasize artificial errors (Erskine et al 2007). …”

Effect of Digital Elevation Model Mesh Size on Geomorphic Indices: A Case Study of the Ivaí River Watershed - State of Paraná, Brazil

“…The quality of the geomorphic indices depends on the production technique and its parameters (El Hage et al 2012), on the terrain morphology and its landcover (El Hage et al 2017) as well as on the mesh size (Thompson, Bell and Butler 2001, Tang 2003, Kienzle 2004, Erskine et al 2007, Vaze and Teng 2007, Wu, Li and Huang 2007, El Hage et al 2010, Vaze, Teng and Spencer 2010, Polidori et al 2012. The mesh size constitutes one of the main DEM characteristics and it is part of the triple scale concept manifested by dimension, extension and spacing, directly controlling the size of objects that could be extracted from DEMs (Blöschl and Sivapalan 1995).…”