State-of-the-Art of 3d National Mapping in 2016

Stoter, J.E.; Vallet, Bruno; Lithen, Thomas; Plá, María Carmen Borrego; Woźniak, Piotr A.; Kellenberger, Tobias; Streilein, André; Ilves, Risto; Ledoux, Hugo

doi:10.5194/isprs-archives-xli-b4-653-2016

Cited by 11 publications

(6 citation statements)

References 10 publications

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“…Hence, the reference model (BIM-CAREM) for controlling the BIM competence of AEC/FM processes, consists of two parts which are the BIM process reference model and the BIM measurement framework (Yilmaz et al 2019). Unfortunately, there are no standard approaches to measure the 3D model calculated from Lidar data quality (Stoter et al 2016 andWong andEllul 2016). Moreover, the absence of Lidar data and BIM regulations was the motivation for suggesting the employment of the Lidar data evaluation concept in the procedure of developing a 3D-BIM model based on Lidar point clouds (Warchol 2019).…”

Section: Related Workmentioning

confidence: 99%

Comparison of LiDAR Building Point Cloud with Reference Model for Deep Comprehension of Cloud Structure

Kurdi

Awrangjeb

2020

Canadian Journal of Remote Sensing

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This paper studies the fidelity level of the extracted Lidar (LIght Detection And Ranging) building point cloud in relation to the original building.In this context, the building point cloud is compared with a reference model. This comparison allows a deep understanding of the point cloud structure with respect to both the actual building and the constructed model. Consequently, the source of the incompatibility in a (reference or constructed) building model is determined and described. Thus, this study considers four aspects of the building point cloud.First, the errors of building point cloud extraction and the undesirable points are quantified. Hence, it is found that the percentages of undesirable points are sometimes considerable (between 15% and 70%). Second, the evaluation of the fit of the altimetry with the reference model shows that the roof plane equations calculated from Lidar data can be more precise than those of reference model, Third, it is noted that the segmentability level between different point densities and building typologies are variable. Finally, the per plane comparison mentions the incompatibility of the plane boundaries of point cloud with reference model. Moreover, considerable differences are noted between the theoretical and the true point densities.

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Section: Related Workmentioning

confidence: 99%

Comparison of LiDAR Building Point Cloud with Reference Model for Deep Comprehension of Cloud Structure

Kurdi

Awrangjeb

2020

Canadian Journal of Remote Sensing

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“…These plans are implemented as part of the project Public Administration Center for Spatial Analysis CAPAP organised by the Polish Head Office of Geodesy and Cartography (Stoter et al, 2016;Pilarska et al, 2017). This project provides a range of products and services related to spatial data, including 15 million of buildings in LOD2 standard based on the ALS elevation data and the building footprint from the topographic database BDOT10K.…”

Section: Capap Projectmentioning

confidence: 99%

Analysis of 3d Building Models Accuracy Based on the Airborne Laser Scanning Point Clouds

Ostrowski

Pilarska

Charyton

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Creating 3D building models in large scale is becoming more popular and finds many applications. Nowadays, a wide term "3D building models" can be applied to several types of products: well-known CityGML solid models (available on few Levels of Detail), which are mainly generated from Airborne Laser Scanning (ALS) data, as well as 3D mesh models that can be created from both nadir and oblique aerial images. City authorities and national mapping agencies are interested in obtaining the 3D building models. Apart from the completeness of the models, the accuracy aspect is also important. Final accuracy of a building model depends on various factors (accuracy of the source data, complexity of the roof shapes, etc.). In this paper the methodology of inspection of dataset containing 3D models is presented. The proposed approach check all building in dataset with comparison to ALS point clouds testing both: accuracy and level of details. Using analysis of statistical parameters for normal heights for reference point cloud and tested planes and segmentation of point cloud provides the tool that can indicate which building and which roof plane in do not fulfill requirement of model accuracy and detail correctness. Proposed method was tested on two datasets: solid and mesh model.

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“…Several studies have conducted different forms of requirements analysis of 3D data (Biljecki et al, 2015;Sargent et al, 2015;Stoter et al, 2013;Stoter et al, 2016;Walter, 2014;Wong and Ellul, 2017) -more details on these studies can be found in Wong and Ellul (2017). Two key points emerge from these studies.…”

Section: D Data Requirements Gatheringmentioning

confidence: 99%

User Requirements Gathering for a National 3d Mapping Product in the United Kingdom

Wong¹,

Ellul²

2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> One of the main barriers to the uptake of 3D GI is the lack of understanding of what the user requirements are. From the data acquisition and creation perspective – in particular, that of a National Mapping and Cadastral Agency who may need to prepare datasets with national coverage – this is an issue as each new 3D feature type and element within a feature added (such as doors, windows, chimneys, street lights) requires additional processing and cost to create. This paper reports the results of a user requirements gathering exercise for a national 3D mapping product in the United Kingdom. The study focuses on the user perception of ‘usefulness’ of different 3D geometry and semantic features. A web-based questionnaire with Likert-type items was selected as the primary data collection method and was conducted in May 2017. A total of 121 completed responses were from the UK. Descriptive analysis showed that ‘Air quality engineering’, ‘Infrastructure & transport’ and ‘Environmental services’ presented the most positive outlook on the usefulness of 3D. Correlation analysis showed that potential 3D product groups that could be formed in a multi-product approach. Cluster analysis showed that appetite for 3D information not only varies between sectors, but also within sectors between different practitioners. The results from exploratory factor analysis showed that users were more interested in additional information on non-building features rather than additional detail to building geometry. Further continued work is required to incorporate both non-GIS users and 3D users outside the GIS domain.</p>

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State-of-the-Art of 3d National Mapping in 2016

Cited by 11 publications

References 10 publications

Comparison of LiDAR Building Point Cloud with Reference Model for Deep Comprehension of Cloud Structure

Comparison of LiDAR Building Point Cloud with Reference Model for Deep Comprehension of Cloud Structure

Analysis of 3d Building Models Accuracy Based on the Airborne Laser Scanning Point Clouds

User Requirements Gathering for a National 3d Mapping Product in the United Kingdom

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