Volume Based DTM Generation From Very High Resolution Photogrammetric DSMS

Abstract

ABSTRACT:In this paper we propose a new algorithm for digital terrain (DTM) model reconstruction from very high spatial resolution digital surface models (DSMs). It represents a combination of multi-directional filtering with a new metric which we call normalized volume above ground to create an above-ground mask containing buildings and elevated vegetation. This mask can be used to interpolate a ground-only DTM. The presented algorithm works fully automatically, requiring only the processing parameters minimum height and maximum width in metric units. Since slope and breaklines are not decisive criteria, low and smooth and even very extensive flat objects are recognized and masked. The algorithm was developed with the goal to generate the normalized DSM for automatic 3D building reconstruction and works reliably also in environments with distinct hillsides or terrace-shaped terrain where conventional methods would fail. A quantitative comparison with the ISPRS data sets Potsdam and Vaihingen show that 98-99% of all building data points are identified and can be removed, while enough ground data points (~66%) are kept to be able to reconstruct the ground surface. Additionally, we discuss the concept of size dependent height thresholds and present an efficient scheme for pyramidal processing of data sets reducing time complexity to linear to the number of pixels, !(#$).

Spatial parameters for transportation: A multi-modal approach for modelling the urban spatial structure using deep learning and remote sensing

“…To validate the city-wide nDSM from SPOT-7, we used DSM data with a pixel spacing of 0.12m derived from VHR DSM of DLR MACS (Lehmann et al, 2011) processed by an algorithm for VHR input data (Piltz, Bayer, & Poznanska, 2016). The airborne VHR data cover a strip in north-eastern Santiago with a total area of about 17.6km² (Figure 2d).…”

Detection of Parking Cars in Stereo Satellite Images

“…For deriving the DTM from the photogrammetric DSM over Barcelona city, we used the volume-based filtering approach developed by Piltz et al [38] and implemented in the OPALS software. The mask for the open terrain was computed by setting the minimum height of the off-terrain objects to 3 m and the maximum width to 80 m. The width was set in accordance with the maximum length/width of existing buildings in the Barcelona dataset.…”

“…Therefore, it is not suitable for ortho-rectification, as it would cause distortion, artifacts, and double mapping effects (Figure A3). Therefore, from the photogrammetric DSM over Barcelona city, we derived the Digital Terrain Model (DTM) by using the volume based filtering approach developed by Piltz et al [38]. The workflow for DSM and DTM derivation for Barcelona study site was performed with the scientific software OPALS (Orientation and Processing of Airborne Laser Scanning data) [39].…”

Geospecific terrain databases for military simulation environments

“…The first automatic terrain extraction algorithm computes the mask of elevated objects to be filtered along one-dimensional scanlines of four directions over the DSM. 10 For each scanline instance, the cross-sectional areas of potential elevated objects of a custom minimum height that start at the current scanline pixel and extend by no more than a predefined length threshold are maximized with respect to the normalized volume above ground (nAVG) metric. The set of DSM profile segments found with the largest nAVG value subsequently are considered candidates for elevated objects.…”