A robust segmentation framework for closely packed buildings from airborne LiDAR point clouds-Reference-Cited by-同舟云学术

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A robust segmentation framework for closely packed buildings from airborne LiDAR point clouds

Published:2020-04-12 Issue:14 Volume:41 Page:5147-5165
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Wang Xinsheng¹²,Chan Ting On¹^ORCID,Liu Kai¹^ORCID,Pan Jun²,Luo Ming¹,Li Wenkai¹,Wei Chunzhu¹

Affiliation:

1. School of Geography and Planning, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou, China

2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2020.1727053

Reference35 articles.

1. An Automatic and Threshold-Free Performance Evaluation System for Building Extraction Techniques From Airborne LIDAR Data

2. Automatic Building Extraction From LIDAR Data Covering Complex Urban Scenes

3. Automatic detection of residential buildings using LIDAR data and multispectral imagery

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Algorithm for Generating Outdoor Floor Plans and 3D Models of Rural Houses Based on Backpack LiDAR;Sensors;2024-09-03

2. Scene Adaptive Building Individual Segmentation Based on Large-Scale Airborne LiDAR Point Clouds;IEEE Transactions on Geoscience and Remote Sensing;2024

3. A bottom-up method for roof plane extraction from airborne LiDAR point clouds;Measurement Science and Technology;2023-11-30

4. A Novel Approach to Match Individual Trees between Aerial Photographs and Airborne LiDAR Data;Remote Sensing;2023-08-23

5. Vo-Norvana : Versatile Framework for Efficient Segmentation of Large Point Cloud Data Sets;Journal of Computing in Civil Engineering;2023-07

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