Resource Ecology & Management
Non Technical Summary
A fundamental challenge to urban sustainability is how best to incorporate and balance multipleenvironmental, social, and economic considerations into planning processes. Land use decisions and transformations are often narrowly driven by a one particular interest or benefit. This project will help develop the science necessary for effective spatial planning by developing an approach to urban forest green infrastructure expansion that is truly inclusive and interdisciplinary. Although this project is focused on Detroit, the approach will be applicable for other urban regions considering how best to restore and expand urban forest ecosystems, as well as urban agriculture and greening "gray" infrastructure such as alleyways. Through the use of Google Earth, this project will provide unprecedented level of spatial detail on urban forests and how they change over time. In terms of broader impact, hundreds of millions of dollars is being poured into redevelopment of Detroit, with green infrastructure expansion as a major centerpiece. Decisions about where and how to expand urban forest ecosystems will have ramifications for decades to come. This project, therefore, has the potential to significantly shape this expansion in a manner that includes matters of environmental and social justice, in addition to more traditional environmental benefits, such as stormwater abatement and carbon sequestration. By incorporating community partners in the urban forest criteria selection and weighting process, the project helps ensure that the results generated are used by those who have the power to beneficially shape outcomes on the ground. Finally, the GIS data layers and approach developed by this project will serve as a foundation for larger research projects that focus on urban sustainability in the Detroit region and beyond.
Animal Health Component
Research Effort Categories
Goals / Objectives
The city of Detroit has approximately twenty square miles of vacant residential, commercial, and industrial property and has ambitious plans to demolish some of these properties and shrink the city by concentrating stabilization efforts in key target neighborhoods (Detroit Future City, 2013). This project responds to an urgent and timely opportunity to this transform vacant, neglected, and underutilized land into a matrix of green infrastructure for the city's residents and ecology. The overall objective is to advance the science necessary to make sound decisions about how to expand urban forest ecosystems as part of a broader green infrastructure strategy.
To complete the project objectives, the research methods are divided into three phases. The proposed work builds on an existing body of research and data analyses by the PI.1. Use Google Earth Pro, ArcGIS, and fieldwork to map and analyze changes in forest cover (1999-2013)We will map forest cover change for the entire city of Detroit using two time periods (1999 and 2013). The PI will develop a methodological guide and research manual that includes a detailed forest classification scheme, step-by-step instructions for the digitizing process, and field validation of this process. Using the Google Earth Pro polygon drawing tool, all urban forests will be digitized on a flat plan at an elevation of ~600 feet and eye altitude of 700-850 feet. Forest polygons will be color-coded based on forest type on a parcel-by-parcel basis in both aerial and street views, assisted by reference images and indicators that will be generated based on site visits to selected urban forest sites. To improve accuracy, student researchers will be trained in classification procedures and their work will be cross-validated periodically. To further validate the accuracy of the digitizing process, we will conduct physical audits in Spring 2015, selecting specific polygons to verify through random stratified sampling. The KML-file forest polygon layers will then be exported to ArcGIS, where maps will be created and changes in forest cover quantified and analyzed. This spatial analysis will draw on a wide range of spatial data sets that have already been collected (see below).2. Develop a science of spatial multi-criteria sustainability analysis to identify optimal sites for expanding urban forestsIn collaboration with an interdisciplinary group of SNRE faculty and community collaborators, we will identify and weight the ecological and socio-economic criteria used to identify future optimal parcels for planting urban forests. Potential SNRE faculty include: Ibanez (forests and climate change), Nassauer (urban landscapes), Moore (ecosystem services), Grese (ecological restoration), Taylor (environmental justice and food access), Mohai (urban exposure to toxic pollutants), and Burton (urban stormwater and water quality). Potential community partners the PI has engaged include SEMCOG (Amy Mangus), Data Driven Detroit (Gregory Parish), Detroit Future City (Erin Kelly), Greening of Detroit (Dean Hay), and Detroiters Working for Environmental Justice (Kimberly Hill Knott)The GIS forest cover map generated in Phase 1 provides the baseline data for this effort. As a test case, the PI has used this spatial multi-criteria analysis approach to identify prospective new urban agricultural sites in Detroit's lower east side. The following criteria (equally weighted) were used: proximity to existing urban gardens, parks, schools, and food stores; suitability of soils; and prevalence of flooding. The PI will organize a half-day interdisciplinary workshop at SNRE to identify and weight the urban forest criteria. Potential additional indicators include: park poverty; proximity to brownfields; historical forest cover (pre-1950); and climate adaptation risk zones. The criteria will be proposed to the faculty and community partners and finalized prior to the workshop. Although the overall spatial scale of analysis will be the city of Detroit, we will deploy these criteria at multiple spatial scales (e.g. census block, NSP target areas, and zip code level) to see how the results and priority areas shift accordingly.3. Identify suitable tree species for potential pilot sitesGoogle Street View allows for identification of species of individual trees at the sub-parcel scale. For this final phase, we will select 3-5 parcel sites identified in Phase 2, and draw upon the knowledge of SNRE faculty (e.g. Ibanez) to suggest appropriate tree species for these locations. This initial effort will serve as a foundation for future research and the PI will engage collaborating community partners and students to explore its potential as a future student Master's Project.