GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD

Separating point clouds into ground and non-ground points is a necessary step to generate digital terrain model (DTM) from LiDAR dataset. In this research, a new method based on multi-scale analysis of height difference threshold is proposed for ground filtering of LiDAR data. The proposed method ut...

Full description

Bibliographic Details
Main Authors: P. Rashidi, H. Rastiveis
Format: Article
Language:English
Published: Copernicus Publications 2017-09-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W4/225/2017/isprs-archives-XLII-4-W4-225-2017.pdf
id doaj-17e1cca41c9842098869d92810d26f1b
record_format Article
spelling doaj-17e1cca41c9842098869d92810d26f1b2020-11-25T01:42:57ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342017-09-01XLII-4-W422522910.5194/isprs-archives-XLII-4-W4-225-2017GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLDP. Rashidi0H. Rastiveis1School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranSeparating point clouds into ground and non-ground points is a necessary step to generate digital terrain model (DTM) from LiDAR dataset. In this research, a new method based on multi-scale analysis of height difference threshold is proposed for ground filtering of LiDAR data. The proposed method utilizes three windows with different sizes in small, average and large to cover the entire LiDAR point clouds, then with a height difference threshold, point clouds can be separated to ground and non-ground in each local window. Meanwhile, the best threshold values for size of windows are considered based on physical characteristics of the ground surface and size of objects. Also, the minimum of height of object in each window selected as height difference threshold. In order to evaluate the performance of the proposed algorithm, two datasets in rural and urban area were applied. The overall accuracy in rural and urban area was 96.06% and 94.88% respectively. These results of the filtering showed that the proposed method can successfully filters non-ground points from LiDAR point clouds despite of the data area.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W4/225/2017/isprs-archives-XLII-4-W4-225-2017.pdf
collection DOAJ
language English
format Article
sources DOAJ
author P. Rashidi
H. Rastiveis
spellingShingle P. Rashidi
H. Rastiveis
GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet P. Rashidi
H. Rastiveis
author_sort P. Rashidi
title GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD
title_short GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD
title_full GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD
title_fullStr GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD
title_full_unstemmed GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD
title_sort ground filtering lidar data based on multi-scale analysis of height difference threshold
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2017-09-01
description Separating point clouds into ground and non-ground points is a necessary step to generate digital terrain model (DTM) from LiDAR dataset. In this research, a new method based on multi-scale analysis of height difference threshold is proposed for ground filtering of LiDAR data. The proposed method utilizes three windows with different sizes in small, average and large to cover the entire LiDAR point clouds, then with a height difference threshold, point clouds can be separated to ground and non-ground in each local window. Meanwhile, the best threshold values for size of windows are considered based on physical characteristics of the ground surface and size of objects. Also, the minimum of height of object in each window selected as height difference threshold. In order to evaluate the performance of the proposed algorithm, two datasets in rural and urban area were applied. The overall accuracy in rural and urban area was 96.06% and 94.88% respectively. These results of the filtering showed that the proposed method can successfully filters non-ground points from LiDAR point clouds despite of the data area.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W4/225/2017/isprs-archives-XLII-4-W4-225-2017.pdf
work_keys_str_mv AT prashidi groundfilteringlidardatabasedonmultiscaleanalysisofheightdifferencethreshold
AT hrastiveis groundfilteringlidardatabasedonmultiscaleanalysisofheightdifferencethreshold
_version_ 1725034101321236480