Download PDF by Hui Lin, Jun Zhu, Bingli Xu, Wenshi Lin, Ya Hu (auth.),: 3D Geo-Information Sciences

By Hui Lin, Jun Zhu, Bingli Xu, Wenshi Lin, Ya Hu (auth.), Jiyeong Lee, Sisi Zlatanova (eds.)

ISBN-10: 3540873945

ISBN-13: 9783540873945

ISBN-10: 3540873953

ISBN-13: 9783540873952

In fresh years 3D geo-information has turn into an incredible examine zone as a result of the elevated complexity of projects in lots of geo-scientific purposes, equivalent to sustainable city making plans and improvement, civil engineering, chance and catastrophe administration and environmental tracking. in addition, a paradigm of cross-application merging and integrating of 3D facts is saw. the issues and demanding situations dealing with today’s 3D software program, usually application-oriented, concentration virtually solely on 3D information transportability concerns – the power to take advantage of info initially built in a single modelling/visualisation process in different and vice versa. instruments for elaborated 3D research, simulation and prediction are both lacking or, whilst on hand, devoted to particular projects. so one can reply to this elevated call for, a brand new form of method needs to be built. a completely built 3D geo-information process could be capable of deal with 3D geometry and topology, to combine 3D geometry and thematic details, to research either spatial and topological relationships, and to provide the knowledge in an appropriate shape. as well as the easy geometry varieties like element line and polygon, a wide number of parametric representations, freeform curves and surfaces or sweep shapes must be supported. methods for seamless conversion among 3D raster and 3D vector representations could be to be had, they need to enable research of a illustration best suited for a particular application.

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Extra info for 3D Geo-Information Sciences

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However, in practical applications it is often necessary to store and exchange extra attributes or even 3D objects which do not belong to any of the predefined classes. For these cases, CityGML generally provides two different ways of extension. The first is the usage of generic city objects and generic attributes, both defined within the module ‘generics’ (Fig. 2). Any CityObject may have an arbitrary number of additional generic attributes. For each generic attribute of an object the name, type, and value has to be given within the CityGML dataset.

5 Acknowledgments The authors wish to thank the directors and researchers in the five core research projects and research coordination project. Sincere thanks should go to the Ministry of Land, Transport and Maritime Affairs and to the Korea Institute of Construction and Transportation Technology Evaluation and Planning, both of which initiated the program and have provided the government’s full support. References 1. Korean Land Spatialization Group: Research Plan for Korean Land Spatialization Program.

For each generic attribute of an object the name, type, and value has to be given within the CityGML dataset. Supported data types are string, integer, real, date, and URI. GenericCityObjects may be assigned arbitrary geometries or ImplicitGeometries for each LOD. As they are derived from CityObject they may also be assigned generic attributes. The second concept for extending CityGML are the so-called Application Domain Extensions (ADE). An ADE specifies systematic extensions of the CityGML data model, see Fig.

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3D Geo-Information Sciences by Hui Lin, Jun Zhu, Bingli Xu, Wenshi Lin, Ya Hu (auth.), Jiyeong Lee, Sisi Zlatanova (eds.)

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