Digital terrain from a two-step segmentation and outlier-based algorithm

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....

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Main Authors: Hingee, Kassel, Caccetta, P., Caccetta, Louis, Wu, X., Devereaux, D.
Format: Conference Paper
Published: 2016
Online Access:http://hdl.handle.net/20.500.11937/61526
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author Hingee, Kassel
Caccetta, P.
Caccetta, Louis
Wu, X.
Devereaux, D.
author_facet Hingee, Kassel
Caccetta, P.
Caccetta, Louis
Wu, X.
Devereaux, D.
author_sort Hingee, Kassel
building Curtin Institutional Repository
collection Online Access
description 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.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-615262018-08-06T01:12:39Z Digital terrain from a two-step segmentation and outlier-based algorithm Hingee, Kassel Caccetta, P. Caccetta, Louis Wu, X. Devereaux, D. 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. 2016 Conference Paper http://hdl.handle.net/20.500.11937/61526 10.5194/isprs-archives-XLI-B3-233-2016 http://creativecommons.org/licenses/by/3.0/ fulltext
spellingShingle Hingee, Kassel
Caccetta, P.
Caccetta, Louis
Wu, X.
Devereaux, D.
Digital terrain from a two-step segmentation and outlier-based algorithm
title Digital terrain from a two-step segmentation and outlier-based algorithm
title_full Digital terrain from a two-step segmentation and outlier-based algorithm
title_fullStr Digital terrain from a two-step segmentation and outlier-based algorithm
title_full_unstemmed Digital terrain from a two-step segmentation and outlier-based algorithm
title_short Digital terrain from a two-step segmentation and outlier-based algorithm
title_sort digital terrain from a two-step segmentation and outlier-based algorithm
url http://hdl.handle.net/20.500.11937/61526