Automatic 3D reconstruction of urban area from low resolution aerial lidar data

2011 ◽  
Author(s):  
Yi Zheng ◽  
Zhiguo Cao
Keyword(s):  
3D Reconstruction ◽  
Urban Area ◽  
Lidar Data ◽  
Low Resolution

scholarly journals Mapping the Urban Atmospheric Carbon Stock by LiDAR and WorldView-3 Data

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 692
Author(s):  
MD Abdul Mueed Choudhury ◽  
Ernesto Marcheggiani ◽  
Andrea Galli ◽  
Giuseppe Modica ◽  
Ben Somers
Keyword(s):  
Remote Sensing ◽  
Urban Area ◽  
Tree Species ◽  
Carbon Stock ◽  
Dominant Species ◽  
Remote Sensing Data ◽  
Data Sources ◽  
Lidar Data ◽  
Urban Tree ◽  
Sensing Data

Currently, the worsening impacts of urbanizations have been impelled to the importance of monitoring and management of existing urban trees, securing sustainable use of the available green spaces. Urban tree species identification and evaluation of their roles in atmospheric Carbon Stock (CS) are still among the prime concerns for city planners regarding initiating a convenient and easily adaptive urban green planning and management system. A detailed methodology on the urban tree carbon stock calibration and mapping was conducted in the urban area of Brussels, Belgium. A comparative analysis of the mapping outcomes was assessed to define the convenience and efficiency of two different remote sensing data sources, Light Detection and Ranging (LiDAR) and WorldView-3 (WV-3), in a unique urban area. The mapping results were validated against field estimated carbon stocks. At the initial stage, dominant tree species were identified and classified using the high-resolution WorldView3 image, leading to the final carbon stock mapping based on the dominant species. An object-based image analysis approach was employed to attain an overall accuracy (OA) of 71% during the classification of the dominant species. The field estimations of carbon stock for each plot were done utilizing an allometric model based on the field tree dendrometric data. Later based on the correlation among the field data and the variables (i.e., Normalized Difference Vegetation Index, NDVI and Crown Height Model, CHM) extracted from the available remote sensing data, the carbon stock mapping and validation had been done in a GIS environment. The calibrated NDVI and CHM had been used to compute possible carbon stock in either case of the WV-3 image and LiDAR data, respectively. A comparative discussion has been introduced to bring out the issues, especially for the developing countries, where WV-3 data could be a better solution over the hardly available LiDAR data. This study could assist city planners in understanding and deciding the applicability of remote sensing data sources based on their availability and the level of expediency, ensuring a sustainable urban green management system.

3D reconstruction of a building from LIDAR data with first-and-last echo information

2007 ◽  
Author(s):  
Guoning Zhang ◽  
Jixian Zhang ◽  
Jie Yu ◽  
Haiquan Yang ◽  
Ming Tan
Keyword(s):  
3D Reconstruction ◽  
Lidar Data

Assessment of seismic loading on structures based on airborne LiDAR data from the Kalochori urban area (N. Greece)

2016 ◽  
Author(s):  
Emmanouil Rovithis ◽  
Emmanouil Kirtas ◽  
Eleftheria Marini ◽  
Dimitris Bliziotis ◽  
Evangelos Maltezos ◽  
...  
Keyword(s):  
Urban Area ◽  
Seismic Loading ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Airborne Lidar Data

scholarly journals Expectation-Maximization Based Approach to 3D Reconstruction From Single-Waveform Multispectral Lidar Data

2020 ◽  
Vol 6 ◽  
pp. 1033-1043
Author(s):  
Quentin Legros ◽  
Sylvain Meignen ◽  
Stephen McLaughlin ◽  
Yoann Altmann
Keyword(s):  
3D Reconstruction ◽  
Expectation Maximization ◽  
Lidar Data

3D reconstruction of cubic armoured rubble mound breakwaters from incomplete lidar data

2015 ◽  
Vol 36 (21) ◽  
pp. 5485-5503 ◽  
Author(s):  
M. Bueno Esposito ◽  
L. Díaz-Vilariño ◽  
J. Martínez-Sánchez ◽  
H. González -Jorge ◽  
P. Arias
Keyword(s):  
3D Reconstruction ◽  
Lidar Data ◽  
Rubble Mound ◽  
Rubble Mound Breakwaters

scholarly journals Analysis of spatial variation of height of tree in urban area, using lidar data

2016 ◽  
Vol 6 (2) ◽  
Author(s):  
Josiclêda D. Galvíncio ◽  
Tiago H. de Oliveira ◽  
Magna S. B. de Moura ◽  
Valéria S. de O. Costa
Keyword(s):  
Spatial Variation ◽  
Urban Area ◽  
Lidar Data
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