scholarly journals Three-Dimensional Reconstruction of Building Roofs from Airborne LiDAR Data Based on a Layer Connection and Smoothness Strategy

2016 ◽  
Vol 8 (5) ◽  
pp. 415 ◽  
Author(s):  
Yongjun Wang ◽  
Hao Xu ◽  
Liang Cheng ◽  
Manchun Li ◽  
Yajun Wang ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Three Dimensional Reconstruction ◽  
Dimensional Reconstruction ◽  
Airborne Lidar Data

Simulating and Mapping the Variations of Solar Radiation at the Lujiazui Region of Shanghai Using Airborne LiDAR Data

2012 ◽  
Vol 500 ◽  
pp. 511-516 ◽  
Author(s):  
Zhi Ming Hu ◽  
Jian Ping Wu ◽  
Bin Wu ◽  
Song Shu ◽  
Bai Lang Yu
Keyword(s):  
Solar Radiation ◽  
Three Dimensional ◽  
Temporal Variations ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Total Solar Radiation ◽  
Solar Radiation Intensity ◽  
Flux Model ◽  
Spatio Temporal ◽  
Airborne Lidar Data

This study utilizes high resolution airborne LiDAR data and topographic solar radiation model to quantify the impacts of three-dimensional morphology on the spatio-temporal variations of solar radiation at the Lujiazui Region, Shanghai, China. Monthly direct and non-direct (diffuse and reflection) plus seasonal total solar radiation distributions are simulated and mapped by using a radiation flux model. The results show that the crowded buildings at the Lujiazui Region have severely changed the spatial pattern of solar radiation intensity and duration. The derived monthly and seasonal solar radiation maps would benefit the understanding of the impacts of urban 3D morphology on the environmental factors and be the scientific basic for the further research.

Reconstruction of Three Dimensional City Model Based on LIDAR

2012 ◽  
Vol 518-523 ◽  
pp. 5648-5655
Author(s):  
Hui Lin ◽  
Ya Zhou Ji ◽  
Liang Liang ◽  
Wei Liu ◽  
Zhao Ling Hu
Keyword(s):  
Three Dimensional ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Building Model ◽  
3D Data ◽  
Topography Model ◽  
City Model ◽  
Three Dimensional Coordinate ◽  
Airborne Lidar Data ◽  
Acquisition Method

The research of Three Dimensional City Model (3DCM) has become a hot topic in GIS field in recent years, and it also has played an important role in traffic, land, mining, surveying and mapping, and other fields, especially in urban planning. However, the difficulty to acquire 3D data is the key obstacle to the further development of 3DCM. Airborne LIDAR, integrating GPS, INS and scanning laser rangefinder, can rapidly acquire the 3D position of ground by airplane, which is very economical, efficient and convenient to acquire 3D data. Because traditional three-dimensional data acquisition method can’t meet the need of the city’s fast development, airborne LIDAR technology is regarded as a convenient, swift, high-efficient three-dimensional data acquisition method. Compared with traditional methods, the airborne LIDAR technology has the following characteristics: 1) High efficiency: in 12 hours, the airborne LIDAR can scan 1000 square kilometers, next, with the help of the related post-processing software, LIDAR cloud data can transform them into GIS format or other receivable format in certain automatic or semiautomatic mode. 2) High precision: because the pulse of laser light isn’t easily subject to shadow and solar angle, it greatly improves the data quality. The flight height limit has no influence on its elevation data precision, which is superior to the conventional photogrammetry. The plane precision may achieve 0.15 to 1 meter, the elevation precision may achieve 10 centimeters. 3) All-weather feature: airborne LIDAR is active remote sensing without considering the digital aerial photogrammetry. 4) Rich information: with the aid of airborne LIDAR ,we can obtains not only the three dimensional coordinate of ground point, but also the three dimensional coordinate of terrain details, such as trees, buildings, roads. If it is integrated with CCD, it could gains image information. We acquired the airborne LIDAR data of 20 square kilometers in the central area of Shanghai using ALTM3100 airborne LIDAR system of the Optech company in 2006.This paper introduces the data processing procedure of the airborne LIDAR data, LIDAR system uses random commercial software to process plane GPS tracking data、plane attitude data、 laser ranging data and the swinging angle data of laser scanning mirror, finally, obtaining the three-dimensional coordinates(X,Y,Z) data of various surveying points. Which three-dimensional discrete dot matrix data is without attribute suspending in the air namely LIDAR original data, named “point cloud”. LIDAR data performs pre-processing to obtain digital surface model (DSM), which is classified and extracted, we acquire topography and object related to modeling, preparing for three-dimensional city model. Data pre-processing includes abnormal point deletion, coordinate transformation and flight strip combination. At present, we used famous business software TerraSolid, developed by Company of Finland to realize the classification and extraction from the LIDAR data TerraSolid depends on MicroStation platform, on the basis of classification and extraction algorithms presented by Axelsson, et al. of Swedish, including a lot of module such as TerraScan, TerraModeler and TerraPhoto. TerraScan is used in the field of LIDAR data classification and extraction, TerraModeler is used for producing and dealing with various planes, TerraPhoto is used for dealing with the primitive image, topography model and building model are got by using this software, complicated artificial building (Oriental Pearl, Jin Mao mansion etc.) need artificial repair and disposal, data processing of 20 sq. km. takes more than one month, efficiency has been improved greatly on the premise of guaranteeing the precision. Topography model and building model can be obtained by using TerraSolid and combining a few manual intervention based on DSM, The topography model is expressed with the triangulated irregular network (TIN), the building model is expressed with 3ds format, three dimensional model of non - texture of Lujiazui region of Shanghai was gained by LIDAR data. In order to achieving better visualization effect, the topography model overlaps orthophoto, and stuck true texture to building model, true city landscape of Lujiazui region of Shanghai is established. This paper has introduce post-processing procedure of airborne LIDAR data systematically, has realized the fast reconstruction of three-dimension urban model based on LIDAR data, enable this technology to serve the information construction of the city better.

scholarly journals Roof Plane Segmentation from Airborne LiDAR Data Using Hierarchical Clustering and Boundary Relabeling

2020 ◽  
Vol 12 (9) ◽  
pp. 1363 ◽  
Author(s):  
Li Li ◽  
Jian Yao ◽  
Jingmin Tu ◽  
Xinyi Liu ◽  
Yinxuan Li ◽  
...  
Keyword(s):  
Hierarchical Clustering ◽  
Three Dimensional ◽  
Region Growing ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Building Models ◽  
Novel Approach ◽  
Airborne Lidar Data ◽  
Seed Points

The roof plane segmentation is one of the key issues for constructing accurate three-dimensional building models from airborne light detection and ranging (LiDAR) data. Region growing is one of the most widely used methods to detect roof planes. It first selects one point or region as a seed, and then iteratively expands to neighboring points. However, region growing has two problems. The first problem is that it is hard to select the robust seed points. The other problem is that it is difficult to detect the accurate boundaries between two roof planes. In this paper, to solve these two problems, we propose a novel approach to segment the roof planes from airborne LiDAR point clouds using hierarchical clustering and boundary relabeling. For the first problem, we first extract the initial set of robust planar patches via an octree-based method, and then apply the hierarchical clustering method to iteratively merge the adjacent planar patches belonging to the same plane until the merging cost exceeds a predefined threshold. These merged planar patches are regarded as the robust seed patches for the next region growing. The coarse roof planes are generated by adding the non-planar points into the seed patches in sequence using region growing. However, the boundaries of coarse roof planes may be inaccurate. To solve this problem, namely, the second problem, we refine the boundaries between adjacent coarse planes by relabeling the boundary points. At last, we can effectively extract high-quality roof planes with smooth and accurate boundaries from airborne LiDAR data. We conducted our experiments on two datasets captured from Vaihingen and Wuhan using Leica ALS50 and Trimble Harrier 68i, respectively. The experimental results show that our proposed approach outperforms several representative approaches in both visual quality and quantitative metrics.

scholarly journals A PHYSICAL INVERSION METHOD OF CANOPY FPAR FROM AIRBORNE LIDAR DATA AND GROUND MEASUREMENTS

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 553-557
Author(s):  
X. Yang ◽  
X. Xi ◽  
C. Wang ◽  
J. Shi ◽  
Y. Huang
Keyword(s):  
Structural Information ◽  
Three Dimensional ◽  
Terrestrial Ecosystem ◽  
Field Measurements ◽  
Airborne Lidar ◽  
Inversion Method ◽  
Lidar Data ◽  
Growth Monitoring ◽  
Cloud Data ◽  
Airborne Lidar Data

Abstract. Fraction of absorbed Photosynthetically Active Radiation (FPAR) is one of the pivotal parameters in terrestrial ecosystem modelling and crop growth monitoring. Airborne LiDAR is an advanced active remote sensing technology which can acquire fine three-dimensional canopy structural information quickly and accurately. Although some previous studies have shown that LiDAR-derived metrics had strong relationships with canopy FPARs, these estimation models without physical meaning are hard to be extended to various vegetation canopies and different growth periods. This study proposed a physical FPAR inversion method based on airborne LiDAR data and field measurements. The method considered direct and diffuse radiations separately based on the SAIL model and energy budget balance principle. The canopy FPAR was inversed from the structural information provided by LiDAR point cloud data and the spectral information provided by ground measurements. The estimated FPAR was validated with the field-measured FPAR over 39 maize plots. Results showed that the proposed method had a good performance in estimating the total FPAR of maize canopy (R2 = 0.76, RMSE = 0.062, n = 39). This study provides the potential to estimate the total, direct, and diffuse FPARs of vegetation canopy from airborne LiDAR data.

Laser scanning as a tool for the analysis of the greenery on the example of Poremba district in Lublin

2015 ◽  
Vol 26 (3-4) ◽  
pp. 132-140
Author(s):  
P. G. Kotsyuba ◽  
I. D. Semko ◽  
I. I. Kozak ◽  
T. V. Parpan ◽  
G. G. Kozak ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Green Space ◽  
Three Dimensional ◽  
Tree Height ◽  
Field Measurements ◽  
Airborne Lidar ◽  
Dimensional Structure ◽  
Lidar Data ◽  
Definition Of ◽  
Airborne Lidar Data

World experience shows that the survey of green spaces by traditional methods is very time consuming, costly and does not always get all the information you need to make of adequate management decisions by municipal authorities. The aim of this article was to show the main stages of analysis and prospects of urban green space using aerial lidar data and submit the effect of three-dimensional visualization of the study area. There were presented the possibilities and perspectives of using the data obtained from airborne laser scanning (ALS) for the analysis of greenery on the example of Poremba district in Lublin (Poland). Research conducted in Poremba district in the Polish city of Lublin (district was built from 1988 to 2005 and is located in the western part of the city). Analysis of green space conducted using quantitative analytical methods. By detailed analysis of the study area were used aerial lidar data from the year 2015. To classify aerial lidar data such software were used: LP360, ArcMap 10.3, Toolbox LAStools. The process of analysis begins with the definition of points, belonging to ground (Ground - GR), and the classification was realized using «lasground» with tools LAStools. The article is dedicated to development the method of estimation the tree height based on airborne LiDAR data. Method applies more information about the three-dimensional structure of natural objects derived from the processing of airborne LiDAR data compared with known methods. Furthermore, the method is adapted to determine and calculate characteristics of stand which using for tree inventory in cities. Methodological and algorithmic instructions to determine the tree parameters in city were proposed. These instructions allow automatically calculating the characteristics of the tree parameters, such as the allocation of each tree and tree height. The study area was analyzed in terms of the distribution of vegetation (separately individual growing trees and groups of trees). For that purpose there was applied an available ALS data. Based on the ALS data there were separated the tops of the trees and their height. In order to verify the ALS data there were used the results of field measurements (coordinates for the tree trunks, the diameter at breast height of trees, their height, crown projection). The analysis of the greenery within the Poremba district using the ALS data after verification with the field measurements proved to be an effective tool for the characterization of the greenery areas in particular city. This research may be important in terms of planning the planting of greenery areas and spatial development of the Lublin.

scholarly journals FOREST SPECIES CLASSIFICATION BASED ON THREE-DIMENSIONAL COORDINATE AND INTENSITY INFORMATION OF AIRBORNE LIDAR DATA WITH RANDOM FOREST METHOD

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 117-123
Author(s):  
H. T. You ◽  
P. Lei ◽  
M. S. Li ◽  
F. Q. Ruan
Keyword(s):  
Classification Accuracy ◽  
Three Dimensional ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Forest Species ◽  
Species Classification ◽  
Combined Application ◽  
Intensity Information ◽  
Three Dimensional Coordinate ◽  
Airborne Lidar Data

Abstract. Forest species is a basic parameter of forest ecosystem. The accurate identification of forest species can not only improve the estimation accuracy of other forest structural parameters, but also have important significance for forest resource monitoring and management. As an active remote sensing technology, the LiDAR could not only acquire the three-dimensional coordinate information of the object, but also acquire the intensity information. The airborne LiDAR data have been successfully used in forest species classification research. However, most of the research is based on the three-dimensional coordinate information of LiDAR data. It's fact that the parameters derived from the intensity data are closely related to the spectral reflection of forest species and could be beneficial for forest species classification, but the research with LiDAR intensity data is fewer. Therefore, it is necessary to explore the potential of LiDAR intensity data on forest species classification and test if the combined application of the three-dimensional coordinate and intensity information can improve the forest species classification accuracy. In this paper, the Moon Lake National Forest Park located in Changchun is selected as the study area, which planted with Scotch pine, Larch pine, Mongolian oak, aspen and other tree species. Two kinds of parameters are separately derived from the three-dimensional coordinate and intensity information of airborne LiDAR data. Then Random Forest is used to classify the forest species based on the above parameters. The main purposes of this study are: (1) to test if the parameters derived from the three-dimensional coordinate information of LiDAR data can be used to identify the forest species; (2) to test if the parameters derived from the intensity information of LiDAR data can be used to identify the forest species; (3) to test if the combined application of the three-dimensional coordinate and the intensity information can improve the accuracy of forest tree species identification. It was found that the classification accuracy of forest species based on structural parameters derived from the three-dimensional coordinate information was 87.54% and Kappa coefficient was 0.81. The classification accuracy based on the parameters derived from LiDAR intensity information was 89.23% and Kappa coefficient was 0.83. And the classification accuracy based on three-dimensional coordinate and intensity information was 92.35% and Kappa coefficient was 0.88. The results demonstrated that both the parameters derived from LiDAR three-dimensional coordinate and intensity information can identify forest species. The results based on LiDAR intensity information are better than that of three-dimensional coordinate information. And the combined application of the two information can improve the classification accuracy of forest species. Therefore, further research should make use of the three-dimensional coordinates and intensity information of LiDAR data to improve the accuracy of results.

Methods for three-dimensional reconstruction of cellular components within a thick section

1986 ◽  
Vol 44 ◽  
pp. 18-21
Author(s):  
J. Frank ◽  
B. F. McEwen ◽  
M. Radermacher ◽  
C. L. Rieder
Keyword(s):  
Tilt Angle ◽  
Tomographic Reconstruction ◽  
3D Structure ◽  
Three Dimensional ◽  
Thick Section ◽  
Three Dimensional Reconstruction ◽  
Axis Ratio ◽  
Dimensional Reconstruction ◽  
Cellular Components

The tomographic reconstruction from multiple projections of cellular components, within a thick section, offers a way of visualizing and quantifying their three-dimensional (3D) structure. However, asymmetric objects require as many views from the widest tilt range as possible; otherwise the reconstruction may be uninterpretable. Even if not for geometric obstructions, the increasing pathway of electrons, as the tilt angle is increased, poses the ultimate upper limitation to the projection range. With the maximum tilt angle being fixed, the only way to improve the faithfulness of the reconstruction is by changing the mode of the tilting from single-axis to conical; a point within the object projected with a tilt angle of 60° and a full 360° azimuthal range is then reconstructed as a slightly elliptic (axis ratio 1.2 : 1) sphere.

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