1. Beijing Land-use and Transportation Integrated Model Development and Application BJLUTI (v1.0) Beijing Municipal Institute of City Planning and Design 2012.09 Beijing Municipal Institute of City Planning and Design 2012.09

2. Contents 1. Research review 2. Development objective and usage 3. Model framework and flow chart 4. Land use Sub-model calibration and validation 5. Application 6. Main Conclusions 1. Research review 2. Development objective and usage 3. Model framework and flow chart 4. Land use Sub-model calibration and validation 5. Application 6. Main Conclusions

3. 1 、 Research Review

4. Basic Theory Von Thünen Wingo Alonso Mills Anas Spatial economic Gravity & entropy Hansen Lowry Wilson Input and output Leontief Discrete choice & Radom utility McFadden Research Theories Short path algorithmic Dijkstra BJLUTI is Based on many relative theories.

5. Model Classification ModelDRAM/EMPALTRANUS/MEPLANUrbanSim Basic TheoryInput-Output model Discrete choice Input-output Model Gravity and entropy Discrete choice Input-output Model Gravity and entropy Spatial economic Case Study Detroit 、 Houston 、 LA St Paul 、 Laister Nottingham Salt Lake City 、 Paris 、 Taipei

6. 2 Objective and Usage

7. Area (sq-km) Pop-2005 (thousands) City proper1,680018,000 Center city108810,000 The TAZ number: 178 That is an macro model.

8. Objective Residential location choice Firm location choice Travel type 1 、 Land use and transportation Plan scenarios appraisal 2 、 Evaluation the different importance infrastructure location choice 3 、 Transportation Strategy and policies appraisa l Relation between choice BJLUTI

9. Model output 1 、 Residential land scale and distribution appraisal

10. Model output 2 、 Forecasting the distribution of different household type

11. Model output 3 、 Forecasting the distribution of rent price 4 、 Forecasting the distribution of land price

12. Model output 5 、 Forecasting the accessibility

13. Model output 6 、 Forecasting the distribution of trips AM PH PCU DISTRIBUTION 5RR

14. Model output 7 、 Forecasting the traffic modal split AM PH Modal split result

15. Model output 8 、 Forecasting the traffic volume through assignment AM PH VC ratio of Planning Year

16. Model output 9 、 Balance between the labor demand and supply appraisal Labor demand ： 10 million Pop demand ： 18.6 million HH demand ： 7.2 million HH supply ： 7.6 million Balance

17. 3 、 model Framework

18. Model Description T sub-model LU sub-model Trip Gen Trip Dist Mode Choice Traffic Ass Location Choice Rent Model Develop Model Land Auction

19. Traffic Assg Mode Choice Trip Dist Trip Gen Land Model Development Model Residential Location Choice BJTLUI(V1.0) Flow Chart Scenario Land Use Plan Transport Sys Balance No Employment Distribution Labor Demand RE Planning Acc Rent Model Yes LU Model T Model Labor Market Balancing Check

20. 4 LU sub-model calibration and validation

21. Data collection NameBeijing HIS2005 Rent Price Data Land Price Data Social attribute (School Hospital Park) Transport system Source from Beijing Traffic Committee Index Institute of China & TsingHua University Index Institute of China BICP Information Department BMI Model Year2005 2002-2010 （ transfer to 2005 ） 2005 Sample820,000HH882407—— Model Application Residential Location choice model & Development model Rent Model & Development Model Land Price Model & Development Model Residential Location choice model & Land Price Model Residential Location choice model & Land Price Model

22. Purpose ： Simulate the residential location choice behaviors of different HH type. (Low Inc \ Mid Inc NCA\ Mid Inc CA\ High Inc NCA\ High Inc CA) Theory ： Bid-auction Methodology ： MNL Residential Location Choice Model Selected Factor

23. Factor A The Shortest Distance from each TAZ to nearest Top50 Primary school Residential Location Choice Model

24. Factor B The Shortest Distance from each TAZ to nearest Top50 Primary school Residential Location Choice Model

25. Factor C The Shortest Distance from each TAZ to nearest City Park Residential Location Choice Model

26. Factor D The Shortest Distance from each TAZ to nearest University Residential Location Choice Model

27. Factor E The Shortest Distance from each TAZ to nearest 3A hospital Residential Location Choice Model

28. Factor F Each TAZ’s commute Accessibility Residential Location Choice Model

29. The Formulation  The higher Income families pay more attention to education\hospital\ environment and accessibility.  The CA HH are less sensitive to the variables compare with the NCA HH at the same income level.  The willingness to pay is more strongly at the locations with better commute accessibility. Calibration Result Residential Location Choice Model HH Low Inc Mid Inc NCA Mid Inc CA Hig Inc NCA Hig Inc CA

30. Validation Residential Location Choice Model Obs HH Distribution Model HH Distribution

31. Function ： Price(i) is avg price of TAZi ， B(hvi) is the willing to pay. Rent Model Purpose ： Compute the Price with the willingness to pay of each HH. Theory ： Utility Max Methodology ： Hedonic

32. Get the TAZ’s average price from 626 samples. Rent Model TAZ Price from the RE price survey sample

33. Rent Model Bids from the Location choice model

34. Calibration result ： Rent Model The R square value is 0.684.

35. Model Validation Rent Model Obs RE Price Distribution Model RE Price Distribution

36. Land Price Model Purpose ： Estimate the land price using the relative variables Theory ： Land auction Methodology ： Hedonic model

37. Land Price Model YearSample Land Price （ RMB/SqM ） MinMaxAvgStd.e 20022274744293587.931189. 20032811339171344.511147. 20043233240601572.431138. 20053116964002189.291443. 200661189110152655.402276. 200756691137883578.192682. 200859707147513733.032635. 200976785298595874.255475. 201062682240667573.284939. total407113298594082.564048. Land Price of each year statistic Land Price from 2003-2010

38. Land Price Model The land price from 2002 to 2010 are transformed into the equivalent price of 2005 2005 Avg Land price of TAZ The sample distribution

39. Land Price Model PAR calibration result The final formulation Final selected factor

40. Land Price Model Model Validation Obs Model

41. Develop Model Purpose ： Simulate the developing behavior of the land developer Theory ： Profit Max Methodology ： MNL 。 Profit Max ：

42. 5 、 Develop Model The relationship between development scale and profit ： Profit (RMB/sq-m) Development Percent of each TAZ

43. 5 、 Develop Model Calibration and Validation Obs Model

44. Sub-model summary 1 、 The model calibrated include ：  Residential location choice  Rent model of Residential  Land Price model of Residential  Development model of Residential 2 、 Future need to calibrated ：  Enterprise location choice  Rent model of NR  Land Price model of NR  Development model of NR

45. 5 Application Case

46. 3A hospital site planning Assessment Concentrate Decentralization

47. RE Development change as the hospital decentralization 3A hospital site planning Assessment

48. However, the effect is not very obvious The distribution of HH change as the hospital decentralization 3A hospital site planning Assessment

49. 6 、 Conclusion

50. Why Choice Cube A Can make an integrated model using the flow chart. B The Cube Land can be used as the tool to develop the Land use Model C The support group of Cube can give an effective support. Especially -Francisco Martinez, which is the founder of Cube Land. D The Matrix can be used to statistic vary data. The Pilot can be used to evoke some mathematical analysis software like: R & Biogeme.

51. Main conclusion A This is a better beginning of BJLUTI, and it is necessary for a mega city. B The panel data for model calibration is vey hard to get. C The LUTI need the transportation model more detailed and better to change the four-step model to ABA model. D The model structure build and variables selection should consider to the data available both of the based and planning year E The model should be improved during more actual projects.

52. Thank you for attention