Applying 3D City Models23/02/2006 |
| Intervisibility, LBS, Sunlight/shadow Analysis, Air and Noise Pollution |
| Planning, designing and managing the urban environment require appropriate decision-making. Here the availability and use of three-dimensional (3D) geo-information in the form of 3D city models is crucial. The authors give examples of how 3D city models can be used for applications including determination of intervisibility between objects, Location Based Services (LBS), sunlight/shadow analysis, and air and noise pollution. |
| Chaokui Li and Jun Wu, Department of Engineering and Technology, Old Dominion University, USA |
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Three-dimensional city models include Digital Elevation Models (DEM) of ground surface and 3D models (geometry and attributes) of buildings and other objects. Applications such as analysis of sunlight and shadow of buildings in densely populated areas require, in addition to 3D city models, appropriate mathematical methods, usually in addition to other types of information. Such mathematical methods include geo-statistical analysis, time-series analysis and analysis of moving platforms (dynamic analysis). The focus here is on examples of the use of 3D city models, without comprehensive treatment of the mathematical methods used to compute the results.
Air Pollution Air pollution is affected by the following factors:
Calculation of the pollution index of an area requires knowledge, in addition to how much pollution emitted by individual sources, of height of objects between gas layer and the ground. This information can be extracted from 3D city models. Noise Pollution Noise affects the health of human beings and is becoming a major source of environmental pollution. In modern cities noise comes mainly from traffic/transportation, industry and public activity. It spreads in certain directions and is emitted at a certain strength that weakens with increasing distance from the source. The presence of obstacles also influences direction and strength of noise at a certain location. Measurement of sound intensity at a certain location, the noise pollution index, is determined by many factors, including terrain relief, presence of sound walls, vegetation and buildings and their surface structure, and the height of bridges, streets and railways. Terrain relief will be evident in the 3D city-model in the form of a DEM, along with heights of obstacles and the height of bridges, streets and railways. Measures should be taken if the noise pollution index exceeds a given index. Sunlight and Shadow The presence of sunlight has a great effect on human wellbeing. The number of daily sunlight hours depends upon length of day as related to position on earth and season, terrain relief, and position, height, size and shape of buildings and other objects that generate shadow. Planning location, size and shape of residential buildings, office buildings and recreational facilities therefore greatly relies on analysis of the daylight hours of sunlight and shadow. More specifically, sunlight analysis facilitates determination of the distance between two buildings, facing direction of buildings, layout orientation, width of streets and distri- bution of blocks. Analysis of sunlight and shadow requires display of various shadows, calculation of sunlight time and computation of sunlight interval: the time between sunrise and sunset without shadow. Computation of the area covered by a shadow is done by projecting the 3D building surfaces onto a 2D plane on the ground along the direction of a ray of sunlight. Figure 3 visualises the result of computing the extent of shadow created by a building. The extent of the shadows of surrounding buildings can be superimposed on the designed building to determine sunlight hours and sunlight interval. Acknowledgements Thanks are due to the Chinese State Bureau of Surveying and Mapping, Dr Zhu Qing of LIESMARS, China, and Dr Zhilin Li of the Polytechnic University of Hong Kong, China. Further Reading
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| Biography of the Author(s) Dr Chaokui Li and Dr Jun Wu are, respectively, visiting faculty and postdoctoral at Old Dominion University, USA, involved in an USA NSF project. Chaokui Li holds a PhD in Geodesy and Surveying Engineering from Central South University, China. Jun Wu holds a PhD in Photogrammetry and Remote Sensing from Wuhan University, China. |
| References |
| http://www.ncgia.ucsb.edu/giscc/units/u127/ |
| http://www.lsgi.polyu.edu.hk/ISPRS_workshop_SADM2003 |
| http://www.ifp.uni-stuttgart.de |
| http://www.casa.ucl.ac.uk/publications/learning_spaces/ |
| http://www.esri.com/base/common/userconf/proc96/TO300/PAP260/P260.HM |


