Visualisation and personalisation of multi-representations city models

Gaillard, Jérémy; Peytavie, Adrien; Gesquière, Gilles

doi:10.1080/17538947.2018.1550122

Cited by 10 publications

(8 citation statements)

References 15 publications

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“…In 2020, Hu Z et al [7] adopted a loose quadtree to partition the pipe segment and point models in b3dm format to complete the visualization of the pipe network. Jérémy Gaillard et al [8] proposed a multi-scale hierarchical approach for the universal representation of cities for the fast generation and visualization of user-specified tiles. The first and the last layer of this hierarchical structure consist of tiles and features, respectively.…”

Section: Related Workmentioning

confidence: 99%

An adaptive quadtree index reconstruction algorithm for massive 3D city models

Shang,

Jia,

et al. 2024

Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023)

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Oblique photogrammetry models are organized in an index tree which incorporates the concept of Hierarchical Level of Detail (HLOD) for optimal rendering of spatial data in the widely used 3D Tiles specification. The inefficient data structure of the index tree, such as gird, may cause problems such as rendering delay and memory overflow on the client-side. This paper proposes an adaptive quadtree index reconstruction algorithm to construct an upper quadtree filled with virtual nodes for tiled tiles of a single oblique photogrammetry dataset using the named coordinates and the actual geographic coordinates of the tiles. The improved structure enables fast elimination of invisible tiles by exploiting the visibility relationship between parent and child nodes, thus improving the traversal rate of tiles. Experiments prove that the algorithm is effective in improving the loading efficiency of local tiles in a single tileset as well as tiles at the junction of multiple tilesets, which is applicable to most browsing scenarios. In addition, the algorithm minimizes the negative impact of the adaptive quadtree structure when observing panoramic tiles by adequately balancing the number of virtual nodes, the depth of the quadtree and the efficiency of tile culling, and experiments demonstrate that the time consumption is within an acceptable range, and the negative impact is insufficient to offset the positive effect of the performance enhancement.

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Section: Related Workmentioning

confidence: 99%

An adaptive quadtree index reconstruction algorithm for massive 3D city models

Shang,

Jia,

et al. 2024

Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023)

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“…Hence, we can see approaches where building structures are mapped with their image‐based texture (Zhou et al, 2006) giving quasi‐total realistic information. CAD (Constructed Aided Design) based models may also give an almost realistic impression, but such detailed models are difficult to visualize for large‐scale visualization of cities, because of current technical limitations (Gaillard et al, 2020). To build a generic and open urban digital twin, UD‐SV ensures the possibility of sharing urban data and interoperability of standards.…”

Section: Urban Digital Twin: Computation Processes and Usagesmentioning

confidence: 99%

UD‐SV: Urban data services and visualization framework for sharing multidisciplinary research

Samuel

Jaillot

Colin

et al. 2023

Transactions in GIS

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With the widespread availability of a large volume of urban data, stakeholders from different domains require advanced tools to manage, visualize and understand cities and their evolution. During the last few years, researchers have proposed numerous research works and applications to illustrate the cities of the past and possible scenarios of the future under different conditions. However, many of these approaches are one‐time solutions and not based on standards, making them obsolete and unusable for reproducible research. In this article, we present UD‐SV: an Urban data‐Services and Visualization open‐source framework for multidisciplinary research to handle complex processing, analysis, and visualization of urban data. However, our goal is not to present a one‐time monolithic software solution for urban data management and analysis, but we demonstrate the design and development of an open and interoperable software framework driven by use cases from diverse users to solve applied research challenges. The main contribution of UD‐SV is that it uses open standards and open data with documented and reproducible processes with a particular emphasis on the reuse of existing open‐source software components. We also show an enhanced use of standards to enable a shift toward components that are interchangeable or composable with other existing components in the GIS community.

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“…This solution is justified by the performance of this format for this type of data, in particular thanks to the spa tial organization of the objects in tiles. An example of this per formance is demonstrated by (Kulawiak and Kulawiak, 2017), allowing a smooth visualization of about 500Gb of point cloud data, at a precision of about 19 points/m 2 , on an area of about 1400km 2 • At the city scale, (Gaillard et al, 2018, Mao et al, 2020 fo cused on the conversion of CityGML data to 3D Tiles in two approaches. The first one for the exchange and representation of city data; the second one allowing the visualization of simu lations of the city.…”

Section: Geospatial Data Visualization Using 3d Tilesmentioning

confidence: 99%

“…To address the emerging need for solutions to visualize massive, large-area, multi-scale 3D geospatial content, Cesium and OGC have introduced the 3D Tiles 2 community standard. The con version of the most common geospatial data models to this format is a solution increasingly adopted by the community (Chen et al, 2018, Gaillard et al, 2018, Jaillot et al, 2020 to visualize these data on the web. 3D Tiles is an evolving stand ard supported by the community.…”

Section: Introductionmentioning

confidence: 99%

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Py3dtilers: An Open Source Toolkit for Creating and Managing 2d/3d Geospatial Data

Marnat

C.²,

C.³

et al. 2022

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

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Abstract. In recent years, the production of 3D geospatial data using formats such as IFC, CityGML and GeoJSON, has increased. Visualizing this data on the web requires solving a variety of problems, such as the massive amount of 3D objects to be visualized at the same time and the creation of geometry suitable for a 3D viewer. Cesium and OGC introduced the 3D Tiles format in 2015 to solve these issues. They have created a specific format optimized for streaming and rendering 3D geospatial content, based on the glTF format developed by Khronos. The recency of the 3D Tiles format implies the need to experiment around this format and to test its interoperability with other geospatial and urban data formats. There is also the will to innovate on the organization of 3D objects in order to offer a better control on the visualization. Therefore, there is a need for an open source tool capable of converting 3D geospatial data into 3D Tiles to visualize them on the web, but also to test and develop new methods of spatial clustering and creating Levels of Detail (LoD) of urban objects. We propose Py3DTilers in this paper, an open source tool to convert and manipulate 3D Tiles from the most common 3D geospatial data models: CityGML, IFC, OBJ, and GeoJSON. With this tool, we ensure that the generated 3D Tiles respect the specification described by the OGC, in order to be used in various viewers. We provide a generic solution for spatially organizing objects and for creating LoDs, while allowing the community to customize these methods to go further in finding efficient solutions for visualizing geospatial objects on the web.

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Visualisation and personalisation of multi-representations city models

Cited by 10 publications

References 15 publications

An adaptive quadtree index reconstruction algorithm for massive 3D city models

An adaptive quadtree index reconstruction algorithm for massive 3D city models

UD‐SV: Urban data services and visualization framework for sharing multidisciplinary research

Py3dtilers: An Open Source Toolkit for Creating and Managing 2d/3d Geospatial Data

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