Comparison of handheld LiDAR point cloud filtering methods for complex mountain microtopography

doi:10.13474/j.cnki.11-2246.2024.0505

Bulletin of Surveying and Mapping ›› 2024, Vol. 0 ›› Issue (5): 24-28.doi: 10.13474/j.cnki.11-2246.2024.0505

Comparison of handheld LiDAR point cloud filtering methods for complex mountain microtopography

XU Yajing¹, YUAN Xiping^2,3,4, GAN Shu^1,2, LI Raobo¹, YE Junmin¹

1. School of Land and Resources Engineering, Kunming University of Science and technology, Kunming 650093, China;
2. Application Engineering Research Center of Spatial Information Surveying and Mapping Technology in Plateau and Mountainous Areas Set by Universities in Yunnan Province, Kunming 650093, China;
3. School of Earth Sciences and Engineering, West Yunnan University of Applied Sciences, Dali 671006, China;
4. West Yunnan University of Applied Sciences, Key Laboratory of Mountain Real Scene Point Cloud Data Processing and Application for Universities in Yunnan Province, Dali 671006, China

Received:2023-10-07 Published:2024-06-12

Abstract

Abstract: In this paper,a typical use case of hand-held laser point cloud data for measuring soil erosion and surface erosion in complex mountainous areas is presented,the performance of delta filter algorithm,slope filter algorithm and cloth simulation filter algorithm in point cloud classification of ground-based LiDAR is compared and analyzed. In order to obtain the highest performance,the parameters corresponding to three kinds of filters are used to test the test data set,and the optimal filtering of each algorithm is obtained through comparative analysis,the experimental results show that for smooth bare landform filtering,cloth simulation filtering is the best,progressive densification triangle filtering is the second,and slope filtering algorithm is the worst,the progressive encrypted triangle filter algorithm has the best filtering effect,the cloth simulation filter is the second,and the slope filter algorithm has the worst filtering effect. The experimental results provide valuable information for optimizing the parameters of the filtering algorithm to improve its performance in detecting micro-terrain changes,and verify the effectiveness of the progressive encrypted triangle filter in complex areas.

Key words: hand-held 3D laser point cloud, progressive encryption triangle filter, slope filter, cloth simulation filter, smooth bare landform, complex mountain landform

CLC Number:

P237

XU Yajing, YUAN Xiping, GAN Shu, LI Raobo, YE Junmin. Comparison of handheld LiDAR point cloud filtering methods for complex mountain microtopography[J]. Bulletin of Surveying and Mapping, 2024, 0(5): 24-28.

References

[1] 蒋钰峰,吴光,赵志明,等.基于地形地貌参数的山区铁路通道选线法[J].工程地质学报,2019,27(4):903-913.
[2] 董秀军.三维激光扫描技术获取高精度DTM的应用研究[J].工程地质学报,2007,15(3):428-432.
[3] 齐永良,李海鹏,王永国.明代石碑高精度真实纹理三维建模应用[J].测绘通报,2021(6):98-102.
[4] 王荀仟,胡海虔,胡旭峰,等.手持式三维激光扫描系统在古生物研究中的应用分析[J].四川地质学报,2020,40(2):318-322.
[5] 汪建波,孙亦东.手持式三维激光扫描仪在文物保护中的应用[J].江西测绘,2017(1):47-50.
[6] ZLOT R,BOSSE M,GREENOP K,et al.Efficiently capturing large,complex cultural heritage sites with a handheld mobile 3D laser mapping system[J].Journal of Cultural Heritage,2014,15(6):670-678.
[7] ALLEGRA D,GALLO G,INZERILLO L,et al.Hand held 3D scanning for cultural heritage:experimenting low cost structure sensor scan[M].[S.l.]:Handbook of research on emerging technologies for architectural and archaeological heritage,2017.
[8] 石明旺,张均,刘学思.手持三维激光扫描仪在规划竣工测量中的应用[J].测绘通报,2022(S2):122-125.
[9] 马赶,郭恒林,谢坤,等.手持三维激光扫描仪在平立面测量中的应用[J].测绘通报,2020(S1):247-250.
[10] 冯晓珂,吕沛娴,张卡,等.面向滩涂DEM构建的机载LiDAR点云滤波方法[J].测绘通报,2023(7):58-62.
[11] 张昌赛,刘正军,杨树文,等.基于LiDAR数据的布料模拟滤波算法的适用性分析[J].激光技术,2018,42(3):410.
[12] BAILEY G,LI Yingkui,MCKINNEY N,et al.Comparison of ground point filtering algorithms for high-density point clouds collected by terrestrial LiDAR[J].Remote Sensing,2022,14(19):4776.
[13] 杨在松,甘淑,袁希平,等.禄丰恐龙谷UAV-LiDAR点云构建背斜数字地貌模型研究[J].激光与红外,2023,53(6):859-868.
[14] 钱金菊,张昌赛,王柯,等.机载LiDAR点云数据抽稀算法研究述评[J].测绘通报,2017(S1):33-35.
[15] AXELSSON P.Dem generation from laser scanner data using adaptive tin models[J].International Archives of Photogrammetry and Remote Sensing,2000,23(B4):110-117.
[16] 罗为东,甘淑,袁希平,等.恐龙谷南缘山区DIM点云的PTD滤波改进试验研究[J].激光与红外,2022,52(6):938-944.
[17] VOSSELMAN G.Slope based filtering of laser altimetry data[J].International Archives of Photogrammetry and Remote Sensing,Vol 33,Part B3/2,2000,33(Part B3/2):678-684.
[18] 刘帅,栾奎峰,谭凯,等.基于无人机LiDAR点云的多类型植被覆盖滩涂地形滤波[J].遥感技术与应用,2021,36(6):1272-1283.
[19] ZHANG Wuming,QI Jianbo,WAN Peng,et al.An easy-to-use airborne LiDAR data filtering method based on cloth simulation[J].Remote Sensing,2016,8(6):501.

Comparison of handheld LiDAR point cloud filtering methods for complex mountain microtopography

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 5

Recommended Articles

Metrics

Comments

[1]	HUANG Hua, GE Weiliao, LIU Weiwei, QIAN Rongrong, LI Jie. Building change detection using tilted image reconstruction point cloud [J]. Bulletin of Surveying and Mapping, 2023, 0(5): 125-129.
[2]	WANG Peng, XIN Peikang, LIU Yin, YU Fangqiang. Ground extraction of oblique photography point cloud in construction site based on improved cloth simulation filtering algorithm [J]. Bulletin of Surveying and Mapping, 2023, 0(10): 85-90,110.
[3]	SHI Zhuang, DU Quanye, WANG Qingdong, MA Dongling, CUI Yan. Cloth simulation filtering method of dense matching point cloud based on virtual grid classification [J]. Bulletin of Surveying and Mapping, 2022, 0(2): 73-77.
[4]	FU Xiangxiang, DENG Yunyuan, ZHENG Wenwu, ZHOU Shaoning, ZHOU Jialu. Ground point extraction and DEM generation of traditional village landing surface points based on dense matching point cloud of UAV image: taking Dehang village in western Hunan as an example [J]. Bulletin of Surveying and Mapping, 2021, 0(12): 1-5.
[5]	WANG Yanfeng, SHENG Yehua, QIN Jiarui, ZHANG Siyang, MIN Xiangqiang. Purification of single building point cloud data using cloth simulation filter [J]. Bulletin of Surveying and Mapping, 2020, 0(9): 72-75,84.