Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 233-239, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/233/2016/
doi:10.5194/isprs-archives-XLI-B3-233-2016
 
09 Jun 2016
DIGITAL TERRAIN FROM A TWO-STEP SEGMENTATION AND OUTLIER-BASED ALGORITHM
Kassel Hingee1,2,3, Peter Caccetta2, Louis Caccetta3, Xiaoliang Wu2, and Drew Devereaux2 1School of Mathematics and Statistics, University of Western Australia, Stirling Highway, Perth, Western Australia
2CSIRO, Underwood Ave, Floreat, Perth, Australia
3Department of Mathematics and Statistics, Curtin University, Kent Street, Bentley, Western Australia
Keywords: Digital Elevation Models, DEM, DTM, DSM, ground filter, surface fitting, point cloud filtering Abstract. We present a novel ground filter for remotely sensed height data. Our filter has two phases: the first phase segments the DSM with a slope threshold and uses gradient direction to identify candidate ground segments; the second phase fits surfaces to the candidate ground points and removes outliers. Digital terrain is obtained by a surface fit to the final set of ground points. We tested the new algorithm on digital surface models (DSMs) for a 9600km2 region around Perth, Australia. This region contains a large mix of land uses (urban, grassland, native forest and plantation forest) and includes both a sandy coastal plain and a hillier region (elevations up to 0.5km). The DSMs are captured annually at 0.2m resolution using aerial stereo photography, resulting in 1.2TB of input data per annum. Overall accuracy of the filter was estimated to be 89.6% and on a small semi-rural subset our algorithm was found to have 40% fewer errors compared to Inpho’s Match-T algorithm.
Conference paper (PDF, 8802 KB)


Citation: Hingee, K., Caccetta, P., Caccetta, L., Wu, X., and Devereaux, D.: DIGITAL TERRAIN FROM A TWO-STEP SEGMENTATION AND OUTLIER-BASED ALGORITHM, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 233-239, doi:10.5194/isprs-archives-XLI-B3-233-2016, 2016.

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