| Project/Area Number |
14208042
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
社会システム工学
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| Research Institution | Keio University |
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Principal Investigator |
KAJI Hideki Keio University, Faculty of Policy Management, Professor, 総合政策学部, 教授 (00016560)
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| Co-Investigator(Kenkyū-buntansha) |
ISHIBASHI Kenichi Keio University, Faculty of Policy Management, Assistant Professor, 総合政策学部, 専任講師 (00333039)
KANEGAE Hidehiko Ritsumeikan University, College of Policy Science, Associate Professor, 政策科学部, 助教授 (90302976)
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| Project Period (FY) |
2002 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥27,560,000 (Direct Cost: ¥21,200,000、Indirect Cost: ¥6,360,000)
Fiscal Year 2004: ¥9,230,000 (Direct Cost: ¥7,100,000、Indirect Cost: ¥2,130,000)
Fiscal Year 2003: ¥8,190,000 (Direct Cost: ¥6,300,000、Indirect Cost: ¥1,890,000)
Fiscal Year 2002: ¥10,140,000 (Direct Cost: ¥7,800,000、Indirect Cost: ¥2,340,000)
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| Keywords | Cellular Automata / Participatory Planning / The Internet / 都市開発 / ガバナンス / セル・オートマトン / 3次元地図 / シミュレーション / LIDARデータ |
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| Research Abstract |
In 2004, we developed the web-based participatory planning support system which has two components, one is the simulation software to predict the number, distribution pattern and each size and shape of houses and buildings in the future, the other is web-based participatory planning support system.
First outcome is the simulation software, the extended model of "Predicting the land use pattern using a cellular automata model" developed in 2003. This model was able to forecast the land use pattern for each cell. Moreover we developed the extended cellular automata (CA) model to predict the shape of a house and building. A CA model is using to predict the diffusion process of cell's attribute which mechanism is as follows. One cell with an attribute is in the defining space (two dimensional), which attribute is diffusion to neighborhood cells with probability (determined by distance, attractiveness and etc.). Traditional CA is handling with a cell, however our model is aims to deal with each housing lots or building lots. Because of this limitation of CA model, we had to develop an extended CA model. In our model, we develop the new algorithm to predict the diffusion process for each housing lot and building lot that is able to forecast the number, distribution pattern and each size of houses and buildings. By this model we have been trying to forecast the each pattern for Endo district in Fujisawa city, Kanagawa in Japan.
The other outcome is construction of the web-based participatory planning support system which includes 3D CG model for future image. That model is combined with aerial photo and simulation software outputs. Combining two components with www system, every residents that can connect to the internet, is able to browse the future image (twenty years later) of the city under the development program.
We completed the development of the web-based participatory planning support system.
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