New DTM extraction approach from airborne images derived DSM
In this work, a new filtering approach is proposed for a fully automatic Digital Terrain Model (DTM) extraction from very high resolution airborne images derived Digital Surface Models (DSMs). Our approach represents an enhancement of the existing DTM extraction algorithm Multi-directional and Slope...
| Main Authors: | , , |
|---|---|
| Format: | Conference Paper |
| Published: |
2017
|
| Online Access: | http://hdl.handle.net/20.500.11937/54321 |
| _version_ | 1848759343270330368 |
|---|---|
| author | Mousa, Y. Helmholz, Petra Belton, David |
| author_facet | Mousa, Y. Helmholz, Petra Belton, David |
| author_sort | Mousa, Y. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In this work, a new filtering approach is proposed for a fully automatic Digital Terrain Model (DTM) extraction from very high resolution airborne images derived Digital Surface Models (DSMs). Our approach represents an enhancement of the existing DTM extraction algorithm Multi-directional and Slope Dependent (MSD) by proposing parameters that are more reliable for the selection of ground pixels and the pixelwise classification. To achieve this, four main steps are implemented: Firstly, 8 well-distributed scanlines are used to search for minima as a ground point within a pre-defined filtering window size. These selected ground points are stored with their positions on a 2D surface to create a network of ground points. Then, an initial DTM is created using an interpolation method to fill the gaps in the 2D surface. Afterwards, a pixel to pixel comparison between the initial DTM and the original DSM is performed utilising pixelwise classification of ground and non-ground pixels by applying a vertical height threshold. Finally, the pixels classified as non-ground are removed and the remaining holes are filled. The approach is evaluated using the Vaihingen benchmark dataset provided by the ISPRS working group III / 4. The evaluation includes the comparison of our approach, denoted as Network of Ground Points (NGPs) algorithm, with the DTM created based on MSD as well as a reference DTM generated from LiDAR data. The results show that our proposed approach over performs the MSD approach. |
| first_indexed | 2025-11-14T09:58:22Z |
| format | Conference Paper |
| id | curtin-20.500.11937-54321 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:58:22Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-543212017-09-13T15:50:28Z New DTM extraction approach from airborne images derived DSM Mousa, Y. Helmholz, Petra Belton, David In this work, a new filtering approach is proposed for a fully automatic Digital Terrain Model (DTM) extraction from very high resolution airborne images derived Digital Surface Models (DSMs). Our approach represents an enhancement of the existing DTM extraction algorithm Multi-directional and Slope Dependent (MSD) by proposing parameters that are more reliable for the selection of ground pixels and the pixelwise classification. To achieve this, four main steps are implemented: Firstly, 8 well-distributed scanlines are used to search for minima as a ground point within a pre-defined filtering window size. These selected ground points are stored with their positions on a 2D surface to create a network of ground points. Then, an initial DTM is created using an interpolation method to fill the gaps in the 2D surface. Afterwards, a pixel to pixel comparison between the initial DTM and the original DSM is performed utilising pixelwise classification of ground and non-ground pixels by applying a vertical height threshold. Finally, the pixels classified as non-ground are removed and the remaining holes are filled. The approach is evaluated using the Vaihingen benchmark dataset provided by the ISPRS working group III / 4. The evaluation includes the comparison of our approach, denoted as Network of Ground Points (NGPs) algorithm, with the DTM created based on MSD as well as a reference DTM generated from LiDAR data. The results show that our proposed approach over performs the MSD approach. 2017 Conference Paper http://hdl.handle.net/20.500.11937/54321 10.5194/isprs-archives-XLII-1-W1-75-2017 unknown |
| spellingShingle | Mousa, Y. Helmholz, Petra Belton, David New DTM extraction approach from airborne images derived DSM |
| title | New DTM extraction approach from airborne images derived DSM |
| title_full | New DTM extraction approach from airborne images derived DSM |
| title_fullStr | New DTM extraction approach from airborne images derived DSM |
| title_full_unstemmed | New DTM extraction approach from airborne images derived DSM |
| title_short | New DTM extraction approach from airborne images derived DSM |
| title_sort | new dtm extraction approach from airborne images derived dsm |
| url | http://hdl.handle.net/20.500.11937/54321 |