UrbanFootprint’s urban planning analytics modules are built to answer complex problems in simple terms: How can our city reduce carbon emissions to 80 percent of 1990 levels by 2050? How will land use patterns impact conservation, carbon, energy, and public health? How might three different TOD scenarios impact household costs?
UrbanFootprint’s urban planning analytics modules distill vast, complex datasets into clear, scenario-based reporting. With access to efficient and comprehensive impact analysis at the outset of the planning process, UrbanFootprint helps planners, designers, and project stakeholders put people and planet first.
Want to learn more about how each urban planning analytics module works? Dig into the details below.
The Emissions module estimates annual emissions associated with energy use (including electricity and natural gas), water use, and transportation. The module is loaded with baseline emission rates for a list of modeled sources, including GHG and the following pollutant emissions: NOx, PM10, PM2.5, SOx, CO, and VOCs. UrbanFootprint users can replace the default rates with localized data*, if available, for a more accurate assessment. The Emissions urban planning analytics module is designed to help planners and stakeholders easily compare and contrast how various scenarios will impact emissions in their communities.
The Land Consumption urban planning analytics module measures land consumed, in total and by type. Land Consumption can include up to five land use categories: greenfield, infill, redevelopment, agriculture, and woodlands. Conserve your community’s natural resources with comprehensive analytics and informed scenario planning.
The Water Use urban planning analytics module estimates indoor and outdoor water consumption for both residential and commercial building types. Indoor water use is modeled on a per-capita or per-employee basis by building type or employment category. Outdoor water use is based on irrigated area at the parcel scale using location-specific evapotranspiration values. UrbanFootprint users can customize water use calculations with local usage factors, where available. Reduce wasteful water consumption with advanced use analysis.
The Energy Use urban planning analytics module estimates electricity and natural gas use for residential and commercial buildings based on building type and climate zone. Energy use is reported as totals, as well as averages per capita, per household, and per employee. The module is loaded with baseline usage rates derived from U.S. Energy Information Administration (EIA) survey data on energy consumption. UrbanFootprint users can customize energy use calculations with local factors, where available. Plan for smarter energy use with easy access to advanced scenario modeling and analysis.
The Transportation urban planning analytics module incorporates a comprehensive ”sketch” model that interacts with regional travel network data to produce estimates of vehicle miles traveled for land use and transportation scenarios. In turn, VMT estimates are used to calculate transportation-related costs, greenhouse gas (GHG) emissions, and pollutant emissions. UrbanFootprint’s core travel engine is adapted from the Mixed-Use Trip Generation (MXD) model developed by Fehr & Peers for the U.S. Environmental Protection Agency(EPA). Reduce greenhouse gas emissions by building with a data-driven approach to lowering vehicle miles traveled.
The Household Cost module estimates annual expenses associated with residential energy, water, and transportation use. This calculation is based on the modeling outputs of the Energy Use, Water Use, and Transportation modules. The Household Cost urban planning analytics module is preloaded with baseline costs for utilities and transportation use. UrbanFootprint users can replace the default rates with localized data for enhanced precision. Quickly assess fiscal impacts with the Household Costs module.
The Walk Accessibility module calculates the amount of time (minutes) it takes to reach the nearest destination of interest. This includes schools, parks, restaurants, and more. These metrics are generated with OpenStreetMap’s walk, bike, and drive path data, and then combined with relevant datasets for the selected mode of analysis. Plan for walkable, human-scaled communities with UrbanFootprint’s Walk Accessibility urban planning analytics module.
The Transit Accessibility module also calculates the amount of time (minutes) it takes to reach the nearest destination of interest by transit. Commute time along transit networks, if available in the specific location, is gathered from morning peak hours on a standard weekday. The module incorporates regional General Transit Feed Specification (GTFS) data from all operators in the region that provide data in this format.
The Conservation module measures and projects the impact of proposed policy and development across for four key elements: Water quality, habitat preservation, agricultural factors, and carbon sequestration and storage. By standardizing land cover types, reference data, and calculated model inputs, we built a program to compare and contrast future growth scenarios and their resulting impact on the environment.
The Risk and Resilience module helps planners and communities better prepare for the projected impacts of sea level rise, flood inundation, fire hazard, and more. Planners and community stakeholders are now armed with the tools they need to quantify and illustrate the impacts of climate change on populations, job centers, infrastructure, and beyond. Increase your ability to hold data-driven conversations and accelerate the adoption of essential community resilience plans.
The Public Health module measures the impact of land use patterns and urban form on a range of health-related indicators, including physical activity-related weight and disease incidences, pedestrian safety measures, and respiratory impacts. In all cases, costs are applied to health impacts to highlight the fiscal implications of comparative land use and transportation scenarios.
The Fiscal Impacts module calculates three metrics that reflect the fiscal impacts of new residential growth on local jurisdictions: capital infrastructure costs, operations and maintenance (O&M) costs, and revenues. Empirical data from local, regional, state, and utility sources are used to derive the cost and revenue factors which vary by housing unit type, land development category, and land condition.
Interested in fine-tuning an analytics module for a specific location? Please check out Product Services for details.