scholarly journals FIRST PRISMATIC BUILDING MODEL RECONSTRUCTION FROM TOMOSAR POINT CLOUDS

2016 ◽  
Vol XLI-B3 ◽  
pp. 381-386 ◽  
Author(s):  
Y. Sun ◽  
M. Shahzad ◽  
X. Zhu
Keyword(s):  
Point Clouds ◽  
Denoising Method ◽  
Building Model ◽  
Line Simplification ◽  
Building Models ◽  
Convention Center ◽  
The Individual ◽  
First Time ◽  
The City ◽  
Large Building

This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR) point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007) and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce) the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center) in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.

scholarly journals FIRST PRISMATIC BUILDING MODEL RECONSTRUCTION FROM TOMOSAR POINT CLOUDS

2016 ◽  
Vol XLI-B3 ◽  
pp. 381-386
Author(s):  
Y. Sun ◽  
M. Shahzad ◽  
X. Zhu
Keyword(s):  
Point Clouds ◽  
Denoising Method ◽  
Building Model ◽  
Line Simplification ◽  
Building Models ◽  
Convention Center ◽  
The Individual ◽  
First Time ◽  
The City ◽  
Large Building

This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR) point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007) and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce) the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center) in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.

scholarly journals HOLISTIC PARAMETRIC RECONSTRUCTION OF BUILDING MODELS FROM POINT CLOUDS

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 689-695
Author(s):  
Z. Li ◽  
W. Zhang ◽  
J. Shan
Keyword(s):  
Large Scale ◽  
Traditional Approach ◽  
Holistic Approach ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Reconstruction Method ◽  
Optimization Strategy ◽  
Building Roof ◽  
Building Model ◽  
Building Models

Abstract. Building models are conventionally reconstructed by building roof points via planar segmentation and then using a topology graph to group the planes together. Roof edges and vertices are then mathematically represented by intersecting segmented planes. Technically, such solution is based on sequential local fitting, i.e., the entire data of one building are not simultaneously participating in determining the building model. As a consequence, the solution is lack of topological integrity and geometric rigor. Fundamentally different from this traditional approach, we propose a holistic parametric reconstruction method which means taking into consideration the entire point clouds of one building simultaneously. In our work, building models are reconstructed from predefined parametric (roof) primitives. We first use a well-designed deep neural network to segment and identify primitives in the given building point clouds. A holistic optimization strategy is then introduced to simultaneously determine the parameters of a segmented primitive. In the last step, the optimal parameters are used to generate a watertight building model in CityGML format. The airborne LiDAR dataset RoofN3D with predefined roof types is used for our test. It is shown that PointNet++ applied to the entire dataset can achieve an accuracy of 83% for primitive classification. For a subset of 910 buildings in RoofN3D, the holistic approach is then used to determine the parameters of primitives and reconstruct the buildings. The achieved overall quality of reconstruction is 0.08 meters for point-surface-distance or 0.7 times RMSE of the input LiDAR points. This study demonstrates the efficiency and capability of the proposed approach and its potential to handle large scale urban point clouds.

Use of topographic LiDAR point clouds for building reconstruction

2021 ◽  
Author(s):  
Yipeng Yuan
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Point Clouds ◽  
Building Roof ◽  
Building Model ◽  
Building Models ◽  
Urban Models ◽  
Elevation Data ◽  
3D Building Model ◽  
Building Reconstruction

Demand for three-dimensional (3D) urban models keeps growing in various civil and military applications. Topographic LiDAR systems are capable of acquiring elevation data directly over terrain features. However, the task of creating a large-scale virtual environment still remains a time-consuming and manual work. In this thesis a method for 3D building reconstruction, consisting of building roof detection, roof outline extraction and regularization, and 3D building model generation, directly from LiDAR point clouds is developed. In the proposed approach, a new algorithm called Gaussian Markov Random Field (GMRF) and Markov Chain Monte Carlo (MCMC) is used to segment point clouds for building roof detection. The modified convex hull (MCH) algorithm is used for the extraction of roof outlines followed by the regularization of the extracted outlines using the modified hierarchical regularization algorithm. Finally, 3D building models are generated in an ArcGIS environment. The results obtained demonstrate the effectiveness and satisfactory accuracy of the developed method.

scholarly journals Epiphytic bryophytes in urban forests of Wrocław (SW Poland)

2019 ◽  
Vol 53 (1) ◽  
pp. 73-83 ◽  
Author(s):  
Ewa Fudali ◽  
Ludwik Żołnierz
Keyword(s):  
Urban Areas ◽  
Urban Forests ◽  
Primeval Forest ◽  
Ecological Requirements ◽  
Forested Areas ◽  
Sw Poland ◽  
The Individual ◽  
The 19Th Century ◽  
First Time ◽  
The City

Abstract Data documenting the occurrence of epiphytic bryophytes in the urban forests of the Wroclaw city were collected and reported for the first time. Research was carried out in 2015-2016, in forest areas situated within the city administrative boundaries, to find whether some epiphytic species reported from the Wroclaw environs in the 19th century and presently considered to be primeval forest relicts occur in urban forests. The survey was carried out using the established network of 50 study plots randomly scattered within the urban forested areas. In total 42 species (4 liverworts and 38 mosses) were recorded on 467 trees; three of them are primeval forest relicts. In this paper, the host-tree preferences, distribution in the individual forests, relative frequency, abundance and exposure to compass directions of the studied taxa are analysed. Of the species described, only 17 are obligatory epiphytes, while 22 of them are character forest species. However, 82% of the latter were noted on a small number of tree trunks. Two moss taxa, Hypnum cupressiforme and Platygyrium repens, were most frequently found (on 76 and 50% of the trees, respectively). Among the species recorded in the studied area, there are five that have been showing some expansive tendencies in Europe in recent decades. The potential ability of these species to spread in urban areas is discussed in relation to their general ecological requirements.

scholarly journals Accurate Reconstruction of the LoD3 Building Model by Integrating Multi-Source Point Clouds and Oblique Remote Sensing Imagery

2019 ◽  
Vol 8 (3) ◽  
pp. 135 ◽  
Author(s):  
Xuedong Wen ◽  
Hong Xie ◽  
Hua Liu ◽  
Li Yan
Keyword(s):  
Remote Sensing ◽  
Point Clouds ◽  
Reconstruction Method ◽  
Remote Sensing Imagery ◽  
Building Model ◽  
Building Models ◽  
Reconstruction Methods ◽  
Operational Decision Making ◽  
3D Information ◽  
Oblique Images

3D urban building models, which provide 3D information services for urban planning, management and operational decision-making, are essential for constructing digital cities. Unfortunately, the existing reconstruction approaches for LoD3 building models are insufficient in model details and are associated with a heavy workload, and accordingly they could not satisfy urgent requirements of realistic applications. In this paper, we propose an accurate LoD3 building reconstruction method by integrating multi-source laser point clouds and oblique remote sensing imagery. By combing high-precision plane features extracted from point clouds and accurate boundary constraint features from oblique images, the building mainframe model, which provides an accurate reference for further editing, is quickly and automatically constructed. Experimental results show that the proposed reconstruction method outperforms existing manual and automatic reconstruction methods using both point clouds and oblique images in terms of reconstruction efficiency and spatial accuracy.

scholarly journals GRAMMAR-SUPPORTED 3D INDOOR RECONSTRUCTION FROM POINT CLOUDS FOR “AS-BUILT” BIM

2015 ◽  
Vol II-3/W4 ◽  
pp. 17-24 ◽  
Author(s):  
S. Becker ◽  
M. Peter ◽  
D. Fritsch
Keyword(s):  
Point Clouds ◽  
Observation Data ◽  
Reconstruction Process ◽  
Building Model ◽  
3D Point Clouds ◽  
Building Models ◽  
Seamless Transition ◽  
Floor Plans ◽  
Knowledge Content ◽  
Realistic Geometries

The paper presents a grammar-based approach for the robust automatic reconstruction of 3D interiors from raw point clouds. The core of the approach is a 3D indoor grammar which is an extension of our previously published grammar concept for the modeling of 2D floor plans. The grammar allows for the modeling of buildings whose horizontal, continuous floors are traversed by hallways providing access to the rooms as it is the case for most office buildings or public buildings like schools, hospitals or hotels. The grammar is designed in such way that it can be embedded in an iterative automatic learning process providing a seamless transition from LOD3 to LOD4 building models. Starting from an initial low-level grammar, automatically derived from the window representations of an available LOD3 building model, hypotheses about indoor geometries can be generated. The hypothesized indoor geometries are checked against observation data - here 3D point clouds - collected in the interior of the building. The verified and accepted geometries form the basis for an automatic update of the initial grammar. By this, the knowledge content of the initial grammar is enriched, leading to a grammar with increased quality. This higher-level grammar can then be applied to predict realistic geometries to building parts where only sparse observation data are available. Thus, our approach allows for the robust generation of complete 3D indoor models whose quality can be improved continuously as soon as new observation data are fed into the grammar-based reconstruction process. The feasibility of our approach is demonstrated based on a real-world example.

THE LITERARY LANDSCAPE OF WESTERN SIBERIA IN N. A. LUKHMANOVA’S “ESSAYS FROM THE LIFE IN SIBERIA”

2020 ◽  
Vol 6 (2) ◽  
pp. 48-63
Author(s):  
Alyona I. Pershina ◽  
Elena N. Ertner
Keyword(s):  
Creative Thinking ◽  
Western Siberia ◽  
Climatic Conditions ◽  
Point Of View ◽  
Way Of Life ◽  
Old Believers ◽  
Literary Context ◽  
The Individual ◽  
First Time ◽  
The City

The subject of this article is the literary landscape of Western Siberia, which was represented in “Essays from life in Siberia” (1895) by Nadezhda Aleksandrovna Lukhmanova. The relevance of this research is determined by the increased importance of studying “local” texts of Russian culture, including the need for a more detailed study of the phenomenon of Siberia. The mythopoetics of landscape in N. Lukhmanova’s “Essays” is considered in the context of prose of the turn of the 19th-20th centuries (G. Uspensky, K. Nosilov). The literary context of the study of “Siberian” texts for the first time includes the stories by S. I. Kartsevsky. The geographical imagery of Western Siberia is reconstructed in the texts under consideration from the point of view of philological analysis, which allows determining the features of representation of the Place in the creative thinking of a particular writer and identifying the individual author’s view of the depicted locus. “Essays from life in Siberia” by N. Lukhmanova reflect different points of view on the landscape of the Siberian city. Geographical remoteness, climatic conditions, and the closed way of life of old believers form the image of a fortress city, “the country behind the Stone”. The reflected provincial way of life of the city is destroyed on the pages of “Essays” with the arrival of merchant children who were educated in the capital, the growth of industry, the laying of the railway. Siberia in the minds of newcomers appears “a remote, lost place”, while in the perception of Siberians it is the “native land”, “Paradise”. N. Lukhmanova’s “Essays” reflect the “double mythologem” of Western Siberia: it is “alien”, closed space and at the same time “one’s own”, “reserved”, and “secret”.

Representing 3D Model of Building From TLS Data Scanning in CityGML

2014 ◽  
Vol 71 (4) ◽  
Author(s):  
R. Akmaliaa ◽  
H. Setan ◽  
Z. Majid ◽  
D. Suwardhi
Keyword(s):  
3D Model ◽  
Semantic Information ◽  
Laser Scanner ◽  
Point Clouds ◽  
3D Models ◽  
Data Sources ◽  
Detailed Model ◽  
Building Model ◽  
Building Models ◽  
3D Building Model

Nowadays, 3D city models are used by the increasing number of applications. Most applications require not only geometric information but also semantic information. As a standard and tool for 3D city model, CityGML, provides a method for storing and managing both geometric and semantic information. Moreover, it also provides the multi-scale representation of 3D building model for efficient visualization. In CityGML, building models are represented in five LODs (Level of Detail), start from LOD0, LOD1, LOD2, LOD3, and LOD4. Each level has different accuracy and detail requirement for visualization. Usually, for obtaining multi-LOD of 3D building model, several data sources are integrated. For example, LiDAR data is used for generating LOD0, LOD1, and LOD2 as close-range photogrammetry data is used for generating more detailed model in LOD3 and LOD4. However, using additional data sources is increasing cost and time consuming. Since the development of TLS (Terrestrial Laser Scanner), data collection for detailed model can be conducted in a relative short time compared to photogrammetry. Point cloud generated from TLS can be used for generating the multi-LOD of building model. This paper gives an overview about the representation of 3D building model in CityGML and also method for generating multi-LOD of building from TLS data. An experiment was conducted using TLS. Following the standard in CityGML, point clouds from TLS were processed resulting 3D model of building in different level of details. Afterward, models in different LOD were converted into XML schema to be used in CityGML. From the experiment, final result shows that TLS can be used for generating 3D models of building in LOD1, LOD2, and LOD3.

scholarly journals Combined Rule-Based and Hypothesis-Based Method for Building Model Reconstruction from Photogrammetric Point Clouds

2021 ◽  
Vol 13 (6) ◽  
pp. 1107
Author(s):  
Linfu Xie ◽  
Han Hu ◽  
Qing Zhu ◽  
Xiaoming Li ◽  
Shengjun Tang ◽  
...  
Keyword(s):  
Linear Optimization ◽  
Three Dimensional ◽  
Recovery Process ◽  
Point Clouds ◽  
Rule Based ◽  
Building Model ◽  
Building Models ◽  
Potential Applications ◽  
3D Building Model ◽  
Oblique Images

Three-dimensional (3D) building models play an important role in digital cities and have numerous potential applications in environmental studies. In recent years, the photogrammetric point clouds obtained by aerial oblique images have become a major source of data for 3D building reconstruction. Aiming at reconstructing a 3D building model at Level of Detail (LoD) 2 and even LoD3 with preferred geometry accuracy and affordable computation expense, in this paper, we propose a novel method for the efficient reconstruction of building models from the photogrammetric point clouds which combines the rule-based and the hypothesis-based method using a two-stage topological recovery process. Given the point clouds of a single building, planar primitives and their corresponding boundaries are extracted and regularized to obtain abstracted building counters. In the first stage, we take advantage of the regularity and adjacency of the building counters to recover parts of the topological relationships between different primitives. Three constraints, namely pairwise constraint, triplet constraint, and nearby constraint, are utilized to form an initial reconstruction with candidate faces in ambiguous areas. In the second stage, the topologies in ambiguous areas are removed and reconstructed by solving an integer linear optimization problem based on the initial constraints while considering data fitting degree. Experiments using real datasets reveal that compared with state-of-the-art methods, the proposed method can efficiently reconstruct 3D building models in seconds with the geometry accuracy in decimeter level.

scholarly journals A DATA DRIVEN METHOD FOR BUILDING RECONSTRUCTION FROM LiDAR POINT CLOUDS

2014 ◽  
Vol XL-2/W3 ◽  
pp. 225-230 ◽  
Author(s):  
M. Sajadian ◽  
H. Arefi
Keyword(s):  
High Speed ◽  
Laser Scanning ◽  
Pulse Length ◽  
Three Dimensional ◽  
Point Clouds ◽  
Building Model ◽  
Building Models ◽  
Edge Points ◽  
Normal Vectors ◽  
Building Reconstruction

Airborne laser scanning, commonly referred to as LiDAR, is a superior technology for three-dimensional data acquisition from Earth's surface with high speed and density. Building reconstruction is one of the main applications of LiDAR system which is considered in this study. For a 3D reconstruction of the buildings, the buildings points should be first separated from the other points such as; ground and vegetation. In this paper, a multi-agent strategy has been proposed for simultaneous extraction and segmentation of buildings from LiDAR point clouds. Height values, number of returned pulse, length of triangles, direction of normal vectors, and area are five criteria which have been utilized in this step. Next, the building edge points are detected using a new method named "Grid Erosion". A RANSAC based technique has been employed for edge line extraction. Regularization constraints are performed to achieve the final lines. Finally, by modelling of the roofs and walls, 3D building model is reconstructed. The results indicate that the proposed method could successfully extract the building from LiDAR data and generate the building models automatically. A qualitative and quantitative assessment of the proposed method is then provided.

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