What is Sketch Planning?
In the broadest sense sketch plans are use to create a simplified picture of an otherwise complex scene, for the purpose of clearly communicating design concepts. The view of a sketch plan varies from a highly representative picture to an abstract diagram that describes the key components of the system are represented with some sacrifice of detail (Singh 1996). Traditionally sketch planning was a diagrammatic map making technique used by urban planners and designers to describe the key attributes of a place which words could not express succinctly.
With the advent of computers sketch planning has taken a new form, it allows for the visualisation of in a number of ways, the first being the visualisation complicated systems, to make things simple. Secondly; to use visualisation to explore unanticipated outcomes and to refine processes that interact in unanticipated ways. Thirdly to use visualisation to enable end-users with no prior understanding of the problem of the science but a deep understanding of the problem to engage in using models for prediction, prescription and control (Batty et al 2004). This can be accomplished with the translation of data into computable formats. Secondly it allows for scenario building aided by prepared menus and provides a means for their injection into analytic processes (Harris 2001).
Communication and visualisation is at the heart of the planning system. Sketch planning provides this medium; it allows different ways of looking at a subject, different ways of exploring a topic. It has the possibility of sketching things that have never been seen before in a certain combination (Harris 2001). Sketch planning like agent-based models are abstractions of reality, they allow the visualisation of how the system interacts with varying parameters, acting to provide a decision support tool and to foster discussion.
Why use sketch planning in the Urban Environment?
Sketch planning is part of the planning process, it allows different ways of looking at a subject, different ways of exploring a topic. This is especially important as visualisation is becoming increasingly important in spatial modelling and is now key to human interaction with computers. Sketch planning allows users and designers ways of exploring models and outcomes of models/scenarios which were not possible in the past. It provides tools allow to allow ‘what if?’ scenarios to be asked. “What if?” a metaphor popularised by electronic spreadsheets, by acknowledging that model results identify only “what” would happen “if” a scenario underlying assumptions are correct (Klosterman 2001). Sketch planning and planning in general, various scales interact with one another, each of these scales “has some kind of objects, occupiers, and interactions and thus urban functions at different scales could be modelled by skilfully primitive but universal computer capabilities (Harris 2001).” This one could consider has close similarities to ABM, where it is the interactions of the individuals at different scales that cause more aggregate patterns to emerge
Sketch planning, like models more generally are concerned with explorations of one or more essential aspects of an issue, a project, a plan to be. These explorations serve to be both encourage an atmosphere of imaginative improvisation in which means have precedence over ends, and to support later stages of planning, when ends become paramount (Harris 2001). By means of firstly specifying a set of interventions, a plan or part of a plan: secondly, to determine the probable consequences of the outcomes of this intervention; and thirdly, evaluate these outcomes with reference to the goals being pursued (Harris 2001).”
Ideally, one would use a single GIS to produce simplified pictures of reality but it has long been argued that “GIS alone cannot serve all the needs of planning because the current ‘general purpose’ systems cannot easily accommodate the particular informational, computational and display needs of planners (Brail & Klosterman 2001).” This realism has renewed planners’ interests in computer modelling and stimulated the development of Planning Support Systems (PSS), that combine GIS (and non GIS) data , computer based-based models, and advanced visualisation techniques into integrated systems to support core planning functions such a plan preparation and evaluation. (See for example, Finaly and Marples 1992; Holmberg 1994; Klosterman 1997, 2001).” Harris & Batty (1993) identified two principle requirements for planning that devolve onto any PSS. First, since optimization (which equates with the automatic generation of a plan) is impossible, the search for good plans must be by way of an informed process of trial and error, which generates alternatives and prepares them for testing. Second, planning and policy making need extensive tools for tracing out the consequences of alternatives, since otherwise there is no way to compare alternatives on the basis of their costs and benefits, and no way to look for means of improving or replacing alternatives.
Sketch planning and Planning Support Systems in general allow urban planners, policy makers and citizens a means to visualise alternative futures for their cities. “Harris (1960) has long argued for an approach to planning that combines sketch planning –rapid and partial description of alternatives –with state of the art modelling of the implications of these alternatives (cited in Hopkins 2001).” This according to Harris (2001) should be accomplished with the ease of entering proposals, a speedy turnaround in analysis and thirdly, clarity in presenting the outcomes and their relation to objects. The entering of proposals need to be automated, for example adding new roads, the rules need to be locational e.g. no selling of drugs within 200m of schools or do not permit industrial buildings on slopes greater than 8 degree. Secondly the results need to be automated therefore allowing the speedy turnaround of analysis, and as many of the results might be geographically distributed, one could use graphic displays with various types of maps. The evaluation of proposals means that unintended side effects can be seen, for example a model examining landuse, one plan may have low cost and low impact at one level but at a higher level the impact could be reversed. More specifically Batty (2004) writes that sketch planning type models are being developed for more practical needs, “where the exigencies if policy force for the development of models and tools which are closely adapted to local situations and can be developed quickly enough to give some fine tuning to the problem at hand (Batty 2004).
Examples of Sketch Planning
The von Thünen Model
Adapting GIS to Sketch Planning Needs, Singh (1996)
A second example of sketch planning is where it has been used as a decision support tool for urban planning (urban redevelopment). Singh (1996) argued that the built environment influences the cities ability to function therefore one needs to understand how buildings, roads, sidewalks, rail lines, topography etc, integrate to form a characteristic place. Singh explored ways in which a GIS database could be used to develop an understanding of the physical layout, infrastructure and patterns of activity within a city without field investigation of every part of it. By identifying key characteristics such as: nodes, paths, districts, edges and landmarks (based on the classification by Lynchs’ The Image of the City (1960)) as perceived by the city’s inhabitants to help with sketch planning. Singh developed a pattern finding tool within a GIS to identify these key characteristics of the city.
A GIS was used to integrate numerous data sources e.g. Land use data, Streets, Parcels of land, Building footprints, Census data, and Aerial photographs. Once all the data was added to the database, a pattern finding algorithm was used to find the key characteristics as mentioned above. (Arc Info Grid was used to find nodes based on an algorithm and Arc View 3.2 as the GIS interface for the pattern finding application.) Singh (1996) demonstrated the potential of GIS for sketch planning, first, that a GIS can include basic sketch planning functions that takes advantage of the ability of GIS to integrate numerous and disparate data sources. Secondly, building into the system a level of customization demanded by the professionals engaged in urban design.
Other examples of Sketch Planning
The examples above highlighted what can be achieved by small groups or individuals. The examples below are more complex examples of sketch planning tools which were designed as decision support tools.
The What if? Model
The “What if?” model does not attempt to predict future conditions exactly, instead, it is an explicitly policy-orientated planning tool that can be used to determine what would happen if clearly defined policy choices are made and assumptions concerning the future prove to be correct, for example alternative land use plans. The “What if?” model uses a combination of ESRI’s Map Objects and VB from Microsoft (Klosterman 2001).
More information can be seen at: http://www.whatifinc.biz/
CommunityViz: An Integrated Planning Support System.
CommunityViz (Kwartler and Bernard 2001) combines both sketch planning and ABM, which are used to examine land use change at the scale of 1000 to 25000m2. For the model to run, it combines both actual data from the census (such as information on individuals and households in the community) while other data which cant be gained from the census such as building information, land use parcels, zoning regulations, income, sales, property values are synthesised and used to provide agents individualistic characteristics.
Agents are used within the model as autonomous decision making entities that have individual goals and preferences, and which interacts with and creates –through their actions the environment in which they reside. The use of these ‘economic agents’ is a move away from the traditional computer models of urban systems that work from the top-down (aggregated data) which have limited use for local action. In this ABM, units of analysis (i.e. those units being modelled directly) are the specific individuals or households living in the environment. Agents are programmed to make decisions regarding their life autonomously, based upon their own individual characteristics. Each agent has different motivations and values.
The use of agents means the model is stochastic i.e. decisions that the agents make are not based on a deterministic model structure therefore different model runs have different results. This type of stochastic, ABM is a main experimental method in the field of complexity theory. ABM allows the user to trace back the causes of decisions and diagnose the decision making process as well as understand how the agents are modelled. It takes policy forecasting out of the “black box” and makes the process more transparent, unlike traditional urban simulations (Kwartler and Bernard 2001).
More information can be seen at: http://www.communityviz.com/
UrbanSim was designed as a decision support system for metropolitan planning (Weddel 2001). UrbanSim is a good example of a micro-simulation urban development model built from an object-orientated perspective. The software was designed and developed to make the system as flexible as possible by making it portable and modular as possible (i.e. reusable software architecture), with a long term intent of implementing the model and its user interface over the internet for distributed use and review. UrbanSim explores travel times by modes, residential size and value and retail size and value etc. Policy can be inserted by increasing transportation pricing or imposing environmental restrictions. UrbanSim allows areas to be affected by areas surrounding it (adjacent landuse effects) and data can be exported into ArcView or as ASCII tab delimited files.
What is interesting is that within this environment data can be directly imported from a GIS (2 and 3D) and displayed in this 3D artificial world, where others can interact with and discuss the built form. This approach also has the potential to create agent-based models within Second Life. Andy’s team has also been exploring the use of games engines such as Crysis and Oblivion. Within Crysis they are importing their Virtual London model and exploring the use of the Google 3D Warehouse. To see more of this work, tutorials, movies of current work etc, I recommend you to look at Andy’s excellent blog Digital Urban.
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Klosterman, R.E., 1997. Planning Support Systems: A New Perspective on Computer-aided Planning. Journal of Planning Education and Research. 16: 177-87.
Kwartler, M., and Bernard, R. N., 2001. CommunityViz: An Integrated Planning Support System. Paper 11 in Brail, R. K., and Klosterman, R. E., (eds) 2001. Planning Support Systems: Integrating Geographic information Systems, Models and Visualisation tools. ESEI Press,
Lynch, K., 1960. The Image of the City. MIT Press
North, M. J., and Macal, C. M. (2007) Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation,
Singh, R. P., 1996. Adapting Geographic Information Systems to Sketch Planning needs. Unpublished Master thesis from MIT. http://web.mit.edu/rajsingh/www/mcpsketch/
Weddel, P., 2001. Between Politics and Planning: UrbanSim as a Decision-Support System for Metropolitan Planning. Paper 8 Brail, R. K., and Klosterman, R. E., (eds) 2001. Planning Support Systems: Integrating Geographic information Systems, Models and Visualisation tools. ESEI Press,