Using the Online What If? Scenario Planning Tool for City Planning

Transcription

1 Using the Online What If? Scenario Planning Tool for City Planning Chris Pettit Professor of Urban Science Associate Director City Futures Research Centre

2 City Futures Research Centre Our work aims to advance the understanding of Australia s cities, their people, the policies that manage their growth, and their impacts on our society and economy Established 2005, 5 program areas: City Analytics: urban data and analysis, modelling, visualisation City Housing: policy, markets and practice City Shaping: planning, urban renewal and high density living City Wellbeing: planning and public health

3 City Analytics

4 City Dashboard

5 / (Pettit et al, 2015)

6 AURIN Online Workbench (Pettit et al, 2015)

7 Spatial Decision Support Systems Definition: SDSS are explicitly designed to provide the user with a decision-making environment that enables the analysis of geographical information to be carries out in a flexible environment Spraque & Carlson (1982).

8 Planning Support Systems Planning Support Systems (PSS) are computer-based tools introduced a few decades ago with the aim to provide assistance to planning practitioners in completing planning tasks (Te Brömmelstroet 2010). PSS support those involved in planning to explore, represent, analyze, visualize, predict, prescribe, design, implement, monitor and discuss issues associated with the need to plan (Batty, 2005, p666).

9 Scenario Planning Approach Planners require data driven evidenced based decision support tools to assist city planning. Scenario Planning Approach is based on: Best available data Data analytics and modelling Data (geo)-visualisation.to explore an envelope of plausible What if? Future City Scenarios. (Pettit & Pullar, 2004)

10 Spatial Decision Support Tools Metropolitan What if? Map Table Municipality Envision Precinct Envision Scenario Planner

11 Interactive Map Table

12 Interactive Map Table

13 Envision Scenario Planning tool A co-design approach (Pettit et al, 2014)

14 Envision planning support tool

15 Online What if? GIS based collaborative planning support tool (Klosterman, 1999). Enables planning and decision-makers to explore alternative future scenarios (Pettit et al, 2013 & 2015)

16 How it Works Scenario-based Analysis: policy-oriented planning tool used to determine what would happen if the user s policy choices are made and their assumptions concerning the future are correct What if? does NOT attempt to predict the future exactly: it is not an optimization model.

17 Online What if? Tool Setup Module Land Suitability Analysis Multiple Criteria Evaluation. Land use Demand Population & employment driven. Land use Allocation Future land use simulations.

18 Perth to Peel Case Study Perth Australia s 4 th largest city Estimated population 1.65 m Projected population 2.2m (2031), 3.5m (2050) Significant environmental assets surround the city. Growth corridor North West region

19 Perth to Peel Case Study Western Australia Dept of Planning want to explore the following scenarios: 1. Maximising Employment from universities and the health sector; 2. Promoting the region as a coastal growth zone; 3. Maximising the region s potential to act as a food bowl for the region; and 4. Exploring making the region a hub for international sports events and recreational activities.

20 What if? Set up Module What if? Project Workspace

21 What if? Set up Module Setup Upload Shapefile

22 What if? Set up Module Setup Extract Current Land Use

23 What if? Set up Module Setup Select Suitability Factors

24 Land Suitability Module If then else, Where, r ij = 0 S i = 0 S i = å j w ij r ij S i is the land suitability score for land use type i; w ij is the relative importance (weight) of a factor (criterion j) considered to determine the relative suitability of different locations for land use type i r ij is the rating or relative performance value of the factor j contributing to the suitability score of a land use type i Multiple Criteria Evaluation

25 Land Suitability Module Assign Weightings of importance

26 Land Suitability Module Suitability Results Low Density

27 Land Suitability Module Suitability Results Medium Density

28 Land Suitability Module Suitability Results High Density

29 Land Suitability Module Suitability Results Industrial

30 Land Suitability Module Suitability Results Commercial

31 Land Suitability Module Suitability Results Education

32 Demand Module High Growth expected Perth-Peel Directions 2031 Report Joondalup 2022 Plan Up to 12,000 new dwellings An increased focus on local employment Automatic Trend identifies mostly shrinking employment market High growth scenario reflects the desired growth pattern of Joondalup (Dept of planning) Growth Projections

33 Demand Module Current Residential Statistics

34 Land Demand Module Employment Sectors

35 Land Demand Module Current Employment

36 Land Demand Module RLD future = i å ( ) b i 1- IR i éæ TotalPopulation ê future ç ê ëè (1-VR i ) AvgHousehold future h i ö ù - HouseCount i ú current ø ú û Where: i is a particular type of residential housing b i future percentage breakdown by housing types (value between 0 and 1 specified by user) h i breakdown of future housing density by type (specified by user) IR i (Infill Rate) is the infill percentage of new housing units that is assumed to be allocated as infill to areas that are already devoted to residential uses (e.g. new residential units created on current vacant residential lots) VR i is the proportion of the housing units which is vacant and available for sale (surplus) Growth Projections - Residential

37 Land Demand Module ED j = i å (pne i - cne i ) Area j (1- IR i ) cne i Where: j is the land use class (that holds Employment Sectors i ) i is the Employment Sector (i.g. commercial, industrial, etc) ED j is an average value of area required by employment sector, for each land use type. pne projected Number of Employment cne current Number of Employment IR i is the infill rate of the employment sector i in certain land use class n i number of employment sectors (count) n i Growth Projections Employment

38 Land Demand Module Growth Projections - Residential

39 Land Demand Module Growth Projections - Employment

40 Demand Scenarios Land Demand Module Outputs generated from the demand process can be revised or via manual input

41 Land Allocation Module Land allocated across suitability layers Land sorted by: Growth Pattern Size Control Scenarios (utility Infrastructure, transport plans) Land is allocated until demand is met

42 Land Allocation Module

43 Land Allocation Module Allocation Results

44 Land Allocation Module Allocation Results

45 Perth to Peel Case Study Study Area: Perth Peel Estimated population 1.65 m Projected population 2.2m (2031), 3.5m (2050) Spatial Data and Aggregation level : Land Use Data: Cadastral Level (760,430 polygons) DoP Structure Plan Population and Employment forecast: LGA level (DoP) PSMA: street level road network DoP Infrastructure Footprint: proposed transportation network Baseline Year 2011: due to most recent LU data availability.

46 Department of Planning - 5 Scenarios 1 Peri-urban growth scenario 2 All Infill (compact city) 3 Likely City 4 Transit City 5 Activity Centre City

47 Scenario 3 Likely City Urban expansion in line with Directions 2031 (15 dwellings /hectare) Followed by infill to accommodate any surplus Areas suitable for Urban Expansion: Urban; Urban deferred; Urban expansion/investigation Avoid Environmentally Sensitive Areas Infill along public transport and activity centres

48 Residential Land Land for residential expansion = 32,716.5 ha (passed the total available land constraint ) At 15 dwellings/hectare: Land for residential growth will be exhausted by % of the total residential demand can be supplied on that amount of land(i.e. 490,747 dwellings) Infill required for an extra 283,515 dwellings (the remaining 37% of the house demand by 2050) NhousesBuilt (on available land) 490,746.9 Infill (number houses to Infill) 283,515

49 Residential Demand Year N_Houses Growth (in N.Houses) Residential Land Demand (ha) d=15houses/ha Residential Land Available(ha) ,159-32, , ,768 8,385 24, , ,932 6,995 17, ,064, ,072 7,005 10, ,175, ,373 7,358 2, ,291, ,630 7,775-4, ,361,241 69,308 4,621-9, ,442,547 81,306 5,420-14, ,503,421 60,874 4,058-18,901 Total 774,262 51, ,901

50 Online What If?

51 Summary City-wide land use scenarios can be generated in near real-time using What if? Scenarios can inform environmental assessment and strategic planning. Potential to explore scenarios under a changing climate including for example bush fire overlays

52 Next Steps Online What If? Development Release Open Source Code Foster International Community of Developer and Users Code, functionality extensions

53 Online Open Source code release Help documentation

54 User Metrics The number of registered users for what if? 112 Number of users who logged into the system : 52 Number of users who setup a project: 28 Users are international from countries including: Pakistan, Egypt, USA, UK, South Africa, Iran, Germany, Saudi Arabia, Colombia, Turkey, Australia.

55 REFERENCES Batty, M., Urban modeling in computer-graphic and geographic information system environments. Environment and Planning B: Planning and Design, 19, pp Klosterman, R.E. and Pettit, C. (2005) An update on Planning Support Systems, Environment and Planning B: Planning & Design, 32: Pettit, C.J. Klosterman, R.E., Delaney, P., Whitehead, A, L., Kujala, H.,. Bromage, A., Nino-Ruiz, M. (2015) The Online What if? Planning Support System: A Land Suitability Application in Western Australia, Applied Spatial Analysis and Policy. DOI: /s Pettit, C.J. Barton, J, Goldie, X, Sinnott, R. Stimson, R, Kvan, T. (2015) The Australian Urban Intelligence Network supporting Smart Cities, in Geertman S, Stillwell J, Ferreira J and Goodspeed J (eds) Planning Support Systems and Smart Cities, Lecture Notes in Geoinformation and Cartography, pp 243 Springer, pp Pettit, C.J. Klosterman, R.E. Nino-Ruiz, M. Widjaja, I., Tomko, M., Sinnott, R. (2013). The Online What if? Planning Support System in Planning Support Systems for Sustainable Urban Development, Eds Geertman, S and Stillwell, J. Springer Publishers, pp Pettit C.J., Russel A.B.M., Michael T., Aurambout J-P., Sharma, S., Williams, S., Hunter, D., Chan, P., Borda, A., Bishop, I.D., Abramson, D. (2013) Realising an escience platform to support climate change adaptation in Victoria, Future Computer Generate Systems, Vol 29, Pettit, C. and Pullar, D. (2004) A way forward for land use planning to achieve policy goals using spatial modeling scenarios, Environment and Planning B: Planning and Design, 31: Te Brömmelstroet, M., Equip the Warrior instead of Manning the Equipment: Land Use and Transport Planning Support in the Netherlands. University of Amsterdam. Available at:

56 Acknowledgements Get involved