Extraction of urban building damage using spectral, height and corner information from VHR satellite images and airborne LiDAR data

2020 ◽  
Vol 159 ◽  
pp. 322-336 ◽  
Author(s):  
Xue Wang ◽  
Peijun Li
Keyword(s):  
Satellite Images ◽  
Building Damage ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Airborne Lidar Data

scholarly journals A Quantitative Flood-Related Building Damage Evaluation Method Using Airborne LiDAR Data and 2-D Hydraulic Model

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 987 ◽  
Author(s):  
Dingtao Shen ◽  
Tianlu Qian ◽  
Wenlong Chen ◽  
Yao Chi ◽  
Jiechen Wang
Keyword(s):  
Rural Areas ◽  
Evaluation Method ◽  
Building Damage ◽  
Airborne Lidar ◽  
Flood Routing ◽  
Lidar Data ◽  
Damage Evaluation ◽  
Large Area ◽  
Building Information ◽  
Airborne Lidar Data

The evaluation of building damage is of great significance for flood management. Chinese floodplains usually contain small- and medium-sized towns with many other scattered buildings. Detailed building information is usually scarce, making it difficult to evaluate flood damage. We developed an evaluation method for building damage by using airborne LiDAR data to obtain large-area, high-precision building information and digital elevation models (DEMs) for potentially affected areas. These data were then used to develop a two-dimensional (2-D) flood routing model. Next, flood loss rate curves were generated by fitting historical damage data to allow rapid evaluation of single-building losses. Finally, we conducted an empirical study based on the Gongshuangcha detention basin in China’s Dongting Lake region. The results showed that the use of airborne LiDAR data for flood-related building damage evaluation can improve the assessment accuracy and efficiency; this approach is especially suitable for rural areas where building information is scarce.

Building Damage Extraction from Post-earthquake Airborne LiDAR Data

2016 ◽  
Vol 90 (4) ◽  
pp. 1481-1489 ◽  
Author(s):  
DOU Aixia ◽  
MA Zongjin ◽  
HUANG Shusong ◽  
WANG Xiaoqing
Keyword(s):  
Building Damage ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Airborne Lidar Data

scholarly journals Cloth simulation-based construction of pit-free canopy height models from airborne LiDAR data

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Wuming Zhang ◽  
Shangshu Cai ◽  
Xinlian Liang ◽  
Jie Shao ◽  
Ronghai Hu ◽  
...  
Keyword(s):  
Tree Height ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Canopy Height ◽  
Lidar Data ◽  
Cloth Simulation ◽  
Simulation Based ◽  
Maximum Tree Height ◽  
Airborne Lidar Data ◽  
Better Than

Abstract Background The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications.

The use of Otsu algorithm and multi-temporal airborne LiDAR data to detect building changes in urban space

2021 ◽  
Author(s):  
Renato César dos Santos ◽  
Mauricio Galo ◽  
André Caceres Carrilho ◽  
Guilherme Gomes Pessoa
Keyword(s):  
Urban Space ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Multi Temporal ◽  
Airborne Lidar Data
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