A multiple representation data structure for dynamic visualisation of generalised 3D city models

Mao, Bo; Ban, Yifang; Harrie, Lars

doi:10.1016/j.isprsjprs.2010.08.001

Cited by 52 publications

(41 citation statements)

References 17 publications

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“…The visualisation involved the use of maps or 3-D displays to represent physical space. So, the multiple interactively linked view providing different perspectives into the data has become kind of standard in geovisualisation (Mao et al, 2011). There has been paradigm shift in creating, viewing and utilizing geospatial data for planning, navigation and traffic management of urban areas.…”

Section: Geospatial Informationmentioning

confidence: 99%

Geospatial Information From Satellite Imagery for Geovisualisation of Smart Cities in India

Mohan¹

2016

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

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ABSTRACT:In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

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Section: Geospatial Informationmentioning

confidence: 99%

Geospatial Information From Satellite Imagery for Geovisualisation of Smart Cities in India

Mohan¹

2016

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

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“…Glander and Döllner [37] proposed cell-base generalization by maintaining a hierarchy of landmarks, which are preserved. In the work of Mao et al [38], buildings are divided into clusters by the road network and grouped with their close neighbors in each cluster. Chang et al [39] presented a large scale simplification approach based on "urban legibility" intended for better preserving understandability for complex urban spaces at all levels of simplification.…”

Section: -P3mentioning

confidence: 99%

“…Therefore, further generalization is needed especially at city scale. Since a major problem of 3D city models is the huge amount of composing objects, we believe the divide-and-conquer strategy can be adopted, and road network can be regarded as a natural partition of a city [37,38].…”

Section: City Scale Generalizationmentioning

confidence: 99%

All range and heterogeneous multi-scale 3D city models

He¹,

Besuievsky²,

Tourre³

et al. 2012

Usage, Usability, and Utility of 3D City Models – European COST Action TU0801

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Abstract. 3D City Models (3DCM) are key features into decision making of several urban related problems. Therefore 3DCM are needed by several applications, but the required level-of-detail (LoD) of the model depends on the application. Our goal is to propose a multi-scale 3DCM production and use method. Our approach consists of merging, procedural modeling, graph rewriting techniques, and a generalization technique to handle all different kinds of LoD of a 3DCM. In this way, it allows to handle various heterogeneous LoDs of a complete urban city model. We test our proposal with the 3DCM of the City of Nantes for a rendering application. Our results can also be applied to other LoDs criteria to match other 3DCM-based needs.

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“…In the past decade, many researchers have concentrated on the generation of LoDs from the finest 3D building models [4][5][6][7][8]. Generally, most methods derive coarse LoD models by employing the operators of simplification and aggregation on a fine-scale 3D building model [5,7] or on the 2D ground plans [4,6,9].…”

Section: Introductionmentioning

confidence: 99%

“…After the CityGML (OGC City Geography Markup Language) standard was published [1], many studies focused on deriving coarse models from a fine-scale 3D model according to the framework of CityGML. Mao et al generated CityGML models by simplification and aggregation, and then transformed the generated CityGML models to a CityTree for realizing dynamic zoom functionality in real time [6]. Fan and Meng proposed a three-step approach to simplify and aggregate 2D ground plans and generalize roof structures [4].…”

Section: Introductionmentioning

confidence: 99%

Automated Reconstruction of Building LoDs from Airborne LiDAR Point Clouds Using an Improved Morphological Scale Space

Wang

Huang

et al. 2016

Remote Sensing

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Abstract:Reconstructing building models at different levels of detail (LoDs) from airborne laser scanning point clouds is urgently needed for wide application as this method can balance between the user's requirements and economic costs. The previous methods reconstruct building LoDs from the finest 3D building models rather than from point clouds, resulting in heavy costs and inflexible adaptivity. The scale space is a sound theory for multi-scale representation of an object from a coarser level to a finer level. Therefore, this paper proposes a novel method to reconstruct buildings at different LoDs from airborne Light Detection and Ranging (LiDAR) point clouds based on an improved morphological scale space. The proposed method first extracts building candidate regions following the separation of ground and non-ground points. For each building candidate region, the proposed method generates a scale space by iteratively using the improved morphological reconstruction with the increase of scale, and constructs the corresponding topological relationship graphs (TRGs) across scales. Secondly, the proposed method robustly extracts building points by using features based on the TRG. Finally, the proposed method reconstructs each building at different LoDs according to the TRG. The experiments demonstrate that the proposed method robustly extracts the buildings with details (e.g., door eaves and roof furniture) and illustrate good performance in distinguishing buildings from vegetation or other objects, while automatically reconstructing building LoDs from the finest building points.

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A multiple representation data structure for dynamic visualisation of generalised 3D city models

Cited by 52 publications

References 17 publications

Geospatial Information From Satellite Imagery for Geovisualisation of Smart Cities in India

Geospatial Information From Satellite Imagery for Geovisualisation of Smart Cities in India

All range and heterogeneous multi-scale 3D city models

Automated Reconstruction of Building LoDs from Airborne LiDAR Point Clouds Using an Improved Morphological Scale Space

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