Terrain extraction by integrating terrestrial laser scanner data and spectral information
The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain...
Published in: | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
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Language: | English |
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International Society for Photogrammetry and Remote Sensing
2015
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2-s2.0-84974578293 Lau C.L.; Halim S.; Zulkepli M.; Mohd Azwan A.; Tang W.L.; Chong A.K. Terrain extraction by integrating terrestrial laser scanner data and spectral information 2015 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 40 2W4 10.5194/isprsarchives-XL-2-W4-45-2015 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84974578293&doi=10.5194%2fisprsarchives-XL-2-W4-45-2015&partnerID=40&md5=8f27b5f12b14e5185f6c547c3a5c6bf2 The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction. International Society for Photogrammetry and Remote Sensing 16821750 English Conference paper All Open Access; Gold Open Access |
author |
Lau C.L.; Halim S.; Zulkepli M.; Mohd Azwan A.; Tang W.L.; Chong A.K. |
spellingShingle |
Lau C.L.; Halim S.; Zulkepli M.; Mohd Azwan A.; Tang W.L.; Chong A.K. Terrain extraction by integrating terrestrial laser scanner data and spectral information |
author_facet |
Lau C.L.; Halim S.; Zulkepli M.; Mohd Azwan A.; Tang W.L.; Chong A.K. |
author_sort |
Lau C.L.; Halim S.; Zulkepli M.; Mohd Azwan A.; Tang W.L.; Chong A.K. |
title |
Terrain extraction by integrating terrestrial laser scanner data and spectral information |
title_short |
Terrain extraction by integrating terrestrial laser scanner data and spectral information |
title_full |
Terrain extraction by integrating terrestrial laser scanner data and spectral information |
title_fullStr |
Terrain extraction by integrating terrestrial laser scanner data and spectral information |
title_full_unstemmed |
Terrain extraction by integrating terrestrial laser scanner data and spectral information |
title_sort |
Terrain extraction by integrating terrestrial laser scanner data and spectral information |
publishDate |
2015 |
container_title |
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
container_volume |
40 |
container_issue |
2W4 |
doi_str_mv |
10.5194/isprsarchives-XL-2-W4-45-2015 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84974578293&doi=10.5194%2fisprsarchives-XL-2-W4-45-2015&partnerID=40&md5=8f27b5f12b14e5185f6c547c3a5c6bf2 |
description |
The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction. |
publisher |
International Society for Photogrammetry and Remote Sensing |
issn |
16821750 |
language |
English |
format |
Conference paper |
accesstype |
All Open Access; Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809678162011881472 |