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Poster Session Q
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Integrated utilization of Remote Sensing and GIS in Shashi's urban general planning
GIS-Based Urban Quantitive analysis
- Urban Environmental Quality Accessment
Urban Environmental Quality Accessmentand environmental pollution accessment as well as the relevant synthetic accessment were carried out. Firstly, the geographic units were taken as the evaluation units, and nine factors were taken into account as showed in Fig. 1. Data of building vocerage density, floor area ratio, green coverage and population density came directly from the remote sensing survey. The digitized air pollution source points and monitoring points were used as the reference points or starting points of mathematical interpolation or simulation in order to derive SO2, Nox, Dust, C12 and T.S.P. for each evaluation unit.
Fig.1 urban environmental quality accessment based on CIS
Fuzzy weighting method was used for multifactor synthetic accessment. Suppose k factors be selected. with their weights w1, w2,.... wk, p ranks are classified for each factor. Let x1, x2,.... xk be the values of a given evaluation unit, the subordiance degree of xi to the jth rank of the ith factor is defined as:
xijl,x iju are respectively the low limit and upper limit of the jth rank of the ith factor. In this way, fuzzy subordinace degree matrix R was created for k factors and p ranks,
and the fuzzy set of class St was determined as follows:
The evaluation unit in consideration was assigned to the class corresponding to the maximum of s1, S2,..., Sp.
- Urban Traffic volume Forecast and Planning
On the basic of traffic survey and geographic analysis, the planning area was divided into 42 traffic zones.
The existing traffic volume was firstly analyzed to obtain O-D distribution, time variation of traffic volume for certain road segments, traffic generation between basic traffic zones in different mode (by bicycle, by vehicle or on foot). Then the so-called "four-steps" pattern was used to forecast the trip and goods volume in the planned years.
As far as the trip volume forecast is concerned, the total trip volume and the volumes for different trip purposes were calculated according to the average trip volume per person and the future population. The generated and attracted trip volume were simulated by EVANS model,
Tij=KiLjOiDjf(dij) ------------------(3)
where Tij is the volume between the ith and jth traffic zones
dij is the distance between the ith and jth traffic zones.
Oi is the traffic volume generated by the ith traffic zone.
Dj is the traffice volume attracted by the jth traffic zone:
f(dij)=dij
Then the traffic volume was classified into different mode (by bicycle, by vehicle or on foot), and the relevant traffic volume was assigned to the temporary road network using shortest path algorithm.
Goods volume forecast was related to the non-agricultural, existing and planned urban landuse, category of enterprises etc. Similarly, the EVANS model was used for forecasting the generated and attracted goods volume of each traffic zone. The resulted traffic volume was assigned to the temporary road network. The diagnosis, evaluation and adjustment were then followed to optimize the road network and its relevant plan.
- Urban Socio-economic Development Forecast
An optimal equilibrium model was used for forecasting the industrial structure and industrial output values of Shashi in 1995, 2000 and 2010. The objective selected was to maximize the final social product and minimize the quantity of wasted water, gas and solid waste. Energy resources and raw materials. Labor resources etc were selected, after a detailed study, as the other constraints in the model. And the urban population production was carried out according to the discrete differential model.
Conclusion
The integrated utilization of remote sensing and GIS technology in Shashi urban general planning made it possible to provide with urban authority and urban planners, in a rather short time more complete, accurate and reliable basic data and to perform more comprehensive and efficient quantitative analysis, simulation and optimization.
Reference
- Chen Jun et al. the Build up and application of spatial urban information System city planning review no 1988.
- Chen Jun et al urban general planning information engineering based on remote sensing and GIS paper presented at the 2nd Beijing international workshop of GIS 1990.
- Sun Yuguo et al computer Aided Urban traffic planning of Xian fan city journal of Wuhan technical university of surveying and mapping No 1 1990.
- sun Yugao grey Fuzzy linear programming Model and its application paper presented the shangai international symposium models of geography
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