Service reviews by municipalities across Canada have been common over the past few years. Since 1990, the Municipal Reference Model has been stewarded by MISA Canada, as a consistent and common language that can be applied across jurisdictions. Integration and standardization across Canadian governments, with the provincial PSRM and federal GSRM, have been coordinated through a Service Mapping Subcommittee, since 2007. Since 2008, IBM has cooperated with MISA to explore technology platform support, codeveloping a Service Design Workbench. In an open source spirit, these models and tools could be included into university research projects as a way of aligning practices and theory.
In the systems sciences community, recent research has aimed to bridge the domains of services systems and natural systems. Two key directions have emerged: (i) extending the theory of the offering with the language action perspective; and (ii) appreciating regime shifts, ecological resilience and panarchy from the perspective of supply side sustainability. Collaboration between systems scientists (as the ISSS) and systems engineers (at INCOSE) has led to a re-examination of the meaning of systems and science.
DesignDEVS is a software application for developing and testing computer simulations. By combining the open source Lua programming language with the DEVS conventions for coupling models, DesignDEVS aims to help communities of researchers and practitioners collaborate effectively on simulation projects.
WISIR is developing two valuable tools for working in systems and developing social innovations. The first is “The Seven Steps Building Landscapes, Regimes and Transformative Pathways”. The second is the process for a Social Innovation Lab. A brief overview of both will be presented.
Aggregating form parcel data, and employing measures of parcel size, net population density, and housing types, it is possible to create typologies of neighbourhoods to understand the types of urban form created in the Toronto region since 1950. Such typologies can be intersected with other data sets such as energy use, travel patterns, socio-economic status, etc. to examine the relationship between urban form and urban function.
Project Dasher is a research prototype to visualize vast amounts of sensor data in the context of a Building Information Model (BIM). By integrating numerous sources of data in a virtual environment, Dasher aims to help people observe a building’s past performance, understand its present behavior, and improve its future energy efficiency. We present our research across different scales to discuss opportunities and challenges in deploying such technology at a building, community and urban scale.
A resilient city is a sustainable network of physical systems and human communities. Characteristics of resilient systems may include: redundancy, diversity, efficiency, autonomy, strength, interdependence, adaptability and collaboration. The presentation will briefly introduce an integrated resilience measure that combines economic, health, physical and social impacts of climate caused disasters. The measure is implemented through the development of an original ‘City Resilience Simulator’ – tool that integrates (i) system dynamics simulation for describing temporal dynamics and (ii) GIS for capturing spatial dynamics of the resilience measure.
A comprehensive, yet simple, model of the urban metabolism has been developed using approximately 25 closed form equations. The equations represent essential inter-relationships between the major components of metabolism – materials, water, nutrients, energy and
contaminants. The model expresses the role infrastructure in the urban metabolism through parameters such as per capita floor space and the density of transportation infrastructure, which as part of a city’s material stock
influence the flows of energy and or water flows through the city. The model includes some parameters, which while having more variation, are independent of climate, city size, population and other unique characteristics
of cities; these include: material intensities, per capita floor space, intensity of water use for cooling, leakage rates for water distribution systems, heating and cooling intensities of buildings, and utilization rates for transportation infrastructure.
Transportation planning often includes assumptions for mode splits based on case studies; but what, specifically, needs to be in place to replicate observed travel behavior? What mix of our complex physical, economic and social system’s attributes will provide desired results? How can we best communicate this to our clients in a comprehensible manner? We are actively fulfilling a niche to provide transportation advice for mobility hubs, station areas and site master plans.
The Integrated Mode Share Estimation Platform (IMSEP) assumes the role as an embedded tool in the planning workflow for expedited transportation ridership prediction and mode share analysis. The tool was created as an extension for ArcGIS 10.1 using Python Add-Ins. We take advantage of core GIS functions in our analysis and utilize geospatial databases for data storage; while the central analytical engine was built based on leading research on connections between observed travel behavior, land use and urban design. The tool takes into account the direct and derivative attribute or indicator values for any given catchment area around a transportation hub. These attribute and indicator values have been selected by consulting the knowledge and expertise in the academic sphere; while planning specialist observe and validate results returned by the tool. Through parameter and model adjustments, the IMSEP allows for the modifications to underlying attribute and indicator values, which subsequently produce alternative transit ridership and mode share estimations.
Preliminary development and testing has identified the complex nature of modeling transit ridership and mode share estimation; there is no single expert knowledge body to base this work upon. This tool provides a workflow that allows for quickly testing scenarios and supporting decision-maker preferences by connecting with academic and industry knowledge.
The concept of “urban metabolism” has been around for almost five decades (perhaps even longer) and has become a very common framework for describing the flows of the materials and energy within cities and across cities. When it comes to energy use, however, there are many empirical difficulties when trying to answer a set of seemingly straightforward but terribly important questions: what is the energy consumption of urban areas? what features of cities makes them more or less energy efficient? what is the relationship between energy consumption and the size and density of population? The recent availability of detailed data on CO2 emissions (for U.S. metropolitan areas) and Night Time lights (NTL) emissions data for the whole world presents new opportunities for building proxy measures of energy use in urban areas.