Effect of image‐matching parameters and local morphology on the geomorphological quality of SPOT DEMs

Abstract

Digital elevation models (DEMs) are used for many applications, including geomorphological feature identification. This study assesses, for selected regions of Lebanon, the impact of matching parameters on the geomorphic indices extracted from photogrammetrically derived DEMs. Three parameters are shown to have a significant effect on the geomorphic indices: the template size and the correlation and curvature thresholds. The most influential parameter is the template size, an increase in which decreases the proportion of interpolated points and leads to more reliable matching, but it also tends to smooth the morphology of the DEM. A small template size tends to preserve the details of the terrain, especially for steep slopes, but it also increases noise in the DEM. For the present study, the optimal value for this parameter is about 13 9 13 pixels. High threshold values lead to more reliable matches but also increase the proportion of interpolated points, which has a significant effect on the resulting geomorphology.

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

“…There is also an influence caused by other factors such as DEM elevation error that propagates in the geomorphic indices (Tang et al 2001, El Hage et al 2017.…”

“…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).…”

Digital Elevation Model Quality Assessment Methods: A Critical Review

“…. [84,[136][137][138][139][140]), as well as by the local slope and the landcover [84,[140][141][142][143][144][145]. There is an almost linear relationship between the DEM elevation error and the terrain slope [146][147][148][149], although the impact on the landform quality is more severe in low-slope areas [85].…”

“…• Whatever the input point cloud, the interpolator imposes its form to some extent, mainly in low density areas. • Even if the initial point cloud is dense, this does not guarantee a high resolution because each point can be the result of a calculation requiring information over a neighborhood (e.g., case of a large template for image matching [84,140]), and this is not an effect of the interpolation. For these different reasons, the elevation of each point of the DEM is influenced by an area around this point.…”

“…The impact of image acquisition parameters on the DEM accuracy (which must be studied to optimize the values of these parameters) also depends on slope and landcover [140,179].…”