Figure 2.19 Auditing Reference Buildings to Create a Meta Diagram

of parcels or discrete pieces of land with their attendant buildings and end uses. This approach provides much greater precision and is preferred in dealing with existing stocks of buildings. Parcels are grouped into categories based on land use and demand profi le, (for example, prewar low-rise multiunit residential or recent strip mall commercial). Aggregating parcel information requires that experts visit and audit several typical parcels within each category and use these parcels to create a solid reference database. Reference parcels are then used to create proxy values for all the parcels within each category. The total (aggregate) fl ow for the meta diagram is calculated simply by multiplying the proxy fl ows by the population of parcels within each category. Using such shortcuts, it is possible to determine an accurate baseline fl ow quickly (+/− 10 percent). Figure 2.19 shows an example from Squamish, Canada, where a diverse collection of reference parcels was audited and used to create an energy meta diagram for the whole region.

Tools for aggregation

In the development of a reference database on existing stock, all data collection occurs at the level of an individual parcel. Flows are recorded in a predefi ned matrix that corresponds with the Sankey diagram structure. Thus, the fl ows for each node on the parcel are connected with nodes upstream or downstream to account for all sources and destinations. By cross-referencing fl ows in and out of each partition and node, the matrix functions as the numerical equivalent of the meta diagram. A matrix may be automatically generated either from empirical (fi eld) data collected on each archetypal parcel or from hypothetical data deduced from a theoretical parcel design.

Field data and hypothetical data for reference parcels need to be converted into fl ows of resources. The conversion is accomplished using standard models for predicting thermal

Figure 2.19 Auditing Reference Buildings to Create a Meta Diagram

Source: Author compilation (Sebastian Moffatt), adapted from Sheltair Group (2007). Note: Carefully selected reference buildings in Squamish, Canada, were visited, audited, and used as proxies for the various categories of building stock. With the use of these reference buildings, a complete energy meta diagram was generated for the region. The result reveals a simple energy mix, with almost no cascading or on-site generation. This condition is typical of an area, such as Squamish, in which energy prices are low. The large share of energy used for personal transportation is typical of a dormitory community; in Squamish, two-thirds of the working population is employed elsewhere.

loads, water demand, and so on. For example, a data collection form may keep track of primary data such as type of appliance and number of occupants, and these data may then be used to calculate the probable fl ows of water, energy, materials, and people for each purpose. Data collection forms need to accommodate a wide variety of lifestyles and building types. Table 2.2 shows excerpts from data collection forms developed for water fl ows. Similar forms may be used for energy and organic materials. The forms are fairly simple, but they require that connectivity be recorded. For example, the forms shown in the table record exactly where the roof drainage water is output: to the ground, cistern, street, garden, sewerage, storm drain, or some combination of such destinations.

The data collected on each parcel may be used to generate the inputs for a universal fl ow matrix automatically (fi gure 2.20). The matrix may then be used to produce fi les to generate meta diagrams with the aid of various diagramming tools.

A parcel may be any discrete surface area (for example, a park, a house on a private lot, a shopping mall, a sewage treatment plant, or a roadway). The single format for data structure allows for each parcel to demand fl ows and to serve other parcels as a supply (or service) node. Thus, the data structure allows for transformer parcels that evolve over the long term to become part of integrated and distributed infrastructure systems. For example, a singlefamily home may begin as a water or energy demand node in the regional system, but if the roof is retrofi tted to catch rainwater or solar energy, the database easily accommodates the changes. The use of this standardized data structure also helps visualize the process of stock aggregation. Designers may move from a Sankey at the parcel or building scale to a Sankey at other scales simply by stacking the database for each parcel within the larger area and adding the cells. The systems perspective is always maintained.

Effective Overlay Mapping

When a picture is worth a thousand words

The best way to communicate complex information to planners and designers is through pictures, including maps, photos, schematics, or a combination of these. The history of using maps quickly to convey complex relationships between the built and the natural environments begins with Design with Nature (McHarg 1969). Although Ian McHarg’s simple overlays of transparencies are still good tools, the options have evolved considerably with geographic information systems (GISs) on computers and the Web. GIS is now a mature, aff ordable, and widely used technology for mapping and spatial analysis that will soon be part of the standard practice in all cities in all countries. All large metropolitan areas now have GIS departments and routinely use GIS to assist in design and management.

In the context of building capacity for Eco2 projects, cities require GIS and related visualization technologies to support the interdisciplinary planning process. Initially, GIS applications need not be demanding or timeconsuming. All that is required is (1) the capacity to produce simple overlay maps that consolidate spatially referenced information and help planners recognize relationships and patterns on the landscape and (2) the capacity to calculate a few simple spatial indicators, such as density, diversity, and proximity (fi gure 2.21). Such capacities are absolutely essential in supporting charrettes, foresight workshops, and other integrated design exercises.

Unlike many GIS applications, the generation of overlay maps and the calculation of spatial indicators provide exceptional value in exchange for a small investment in time and human resources. Moreover, new technology is now allowing for visualization in a wider variety of formats that also contribute to decision making. For example, simple contour maps (also referred to as digital elevation models)