Abstract
Abstract. Unmanned Aerial Vehicles (UAV) have been widely used for Digital Elevation Model (DEM) generation in geographic applications. This paper proposes a novel framework of generating DEM from UAV images. It starts with the generation of the point clouds by image matching, where the flight control data are used as reference for searching for the corresponding images, leading to a significant time saving. Besides, a set of ground control points (GCP) obtained from field surveying are used to transform the point clouds to the user’s coordinate system. Following that, we use a multi-feature based supervised classification method for discriminating non-ground points from ground ones. In the end, we generate DEM by constructing triangular irregular networks and rasterization. The experiments are conducted in the east of Jilin province in China, which has been suffered from soil erosion for several years. The quality of UAV based DEM (UAV-DEM) is compared with that generated from contour interpolation (Contour-DEM). The comparison shows a higher resolution, as well as higher accuracy of UAV-DEMs, which contains more geographic information. In addition, the RMSE errors of the UAV-DEMs generated from point clouds with and without GCPs are ±0.5 m and ±20 m, respectively.
Highlights
Digital elevation model (DEM) plays an important roles in soil conservation (Rao et al, 2014), ecological restoration (Liang et al, 2015), mining (Maxwell and Warner, 2015), urban planning (Shi and Yu, 2014), and geological disaster monitoring (Demirkesen, 2012)
Unmanned Aerial Vehicles (UAV)-DEMs clearly and vividly exhibit complete context of undulating topography, while Contour-DEM only reflects the overall trend of decreasing from southwest to northeast
In view of the accuracy assessed through check points, the mean errors in z-coordinate of UAV based DEM (UAV-DEM) geoferenced with POS data and ground control points (GCP) are 1.27m and -0.25m, respectively
Summary
Digital elevation model (DEM) plays an important roles in soil conservation (Rao et al, 2014), ecological restoration (Liang et al, 2015), mining (Maxwell and Warner, 2015), urban planning (Shi and Yu, 2014), and geological disaster monitoring (Demirkesen, 2012). The methods of DEM generation are mainly divided into three categories: field surveying (Jones et al, 2012), aerial photogrammetry (Uysal et al, 2015) and satellite stereo imaging (Mukherjee et al, 2013). Many studies of DEMs generation with both UAV photogrammetry (De Souza et al, 2017; Rock et al, 2011) and contour interpolation (Ardiansyah and Yokoyama, 2002; Arun, 2013) can be found in literature and accuracy assessment of the achieved DEMs has been comprehensively investigated. This paper aims to evaluate the quality of DEMs obtained by UAV photogrammetry and contour interpolation through cross validation. Two validation strategies with regards to point-based and area-based methods are used in this study
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