Potential of Citizen Science for Enhancing Infrastructure Monitoring Data and Decision-Support Models for Local Communities.

Citizen science is a process by which volunteer members of the public, who commonly lack advanced training in science, engage in scientific activities (e.g., data collection) that might otherwise be beyond the reach of professional researchers or practitioners. The purpose of this article is to discuss how citizen-science projects coordinated by interdisciplinary teams of engineers and social scientists can potentially enhance infrastructure monitoring data and decision-support models for local communities. The article provides an interdisciplinary definition of infrastructure data quality that extends beyond accuracy to include currency, timeliness, completeness, and equitability. We argue that with this expanded definition of data quality, citizen science can be a viable method for enhancing the quality of infrastructure monitoring data, and ultimately the credibility of risk analysis and decision-support models that use these data. The article concludes with a set of questions to aid in producing high-quality infrastructure monitoring data by volunteer citizen scientists.

Evaluating drivers of housing vacancy: a longitudinal analysis of large U.S. cities from 1960 to 2010.

Housing vacancies have become a major issue in depopulating, or shrinking, cities. All urban areas, however, are subject to some degree of vacant housing. A small percentage is necessary to allow mobility and sufficient space for growth, and is an indicator of healthy urbanization. Conversely, widespread housing vacancies may indicate structural crisis due to property abandonment. Land area and population changes, shifts in employment, demographic trends, development intensity, and economic conditions are primary drivers of housing vacancies. The degree to which these interrelated factors contribute can fluctuate by city. This paper explores relationships between factors contributing to housing vacancies over time to identify changes in underlying factors. The research examines U.S. cities of over 100,000 population over the period of 1960-2010, conducting multivariate regression analyses in 10-year periods and performing longitudinal panel analyses. The regressions examine changes in urban housing vacancy factors over time while the panel models assess which factors have remained consistent. The panel model results indicate that population change, percent nonwhite populations, unemployment and density are consistent, significant predictors of housing vacancies, The incremental regression models suggest that unemployment and regional location have also been strong indicators of housing vacancies. These results, while somewhat exploratory, provide insight into long-term data that cities should track over time to determine the optimal policy approaches to offset housing vacancies.

Using neighborhood characteristics to predict vacancy types: Comparing multi-scale conditions surrounding existing vacant lots.

Vacant and abandoned land can be public eyesores that can potentially result in neighborhood distress in the long term. In some cases, the contextual conditions of a neighborhood have been shown to have more of a negative effect on communities than the vacant property itself. Maximum opportunities to actually reuse vacant and abandoned land is known to primarily exist in cases where the surrounding area has locational benefits or when local economic conditions are hopeful. This study examines and compares neighborhood socioeconomic characteristics around vacant lots in Minneapolis, Minnesota, USA, to identify spatial heterogeneity within vacancy types and neighborhood characteristics. Specifically, we examine 1) if the socioeconomic characteristics of a neighborhood can predict existing vacant lots and 2) what neighborhood characteristics are associated with certain vacant lot types. Three logistic regressions were tested with different buffers around each vacant lot, and a total of eighteen regressions were performed to capture the effects on six vacancy types. Results suggest that there are various types of vacancies interacting differently at the neighborhood scale, and that a large-scale neighborhood context matters when predicting vacancy types. The results also indicate three salient points. First, minority populations are a strong predictor of residential and commercial vacancies. Second, high-income areas tend to predict vacancies with potential investment opportunities or vacancies as a part of an existing park or recreational system. Third, vacant properties designated for institutional land uses tend to be found in lower-income areas, yet, not necessarily in areas with high minority populations. Managing and repurposing vacant and abandoned land should be handled more progressively with a better understanding of the socioeconomic characteristics of neighborhoods. Further, examining vacancy types by community can be a way to diagnose potential neighborhood risks associated with vacant and abandoned land.

The Projected Impact of a Neighborhood-scaled Green Infrastructure Retrofit.

Climate change and its related factors are increasing the frequency of hurricanes, coastal storms, and urban flooding. Recovery from disasters can be slow, with jurisdictions failing to build back better, wasting time and money without improving resilience to the next disaster. To help attenuate floods and mitigate their impacts, Low Impact Development (LID) and the incorporation of green infrastructure (GI) is gaining in popularity. LID installs more natural methods of absorbing, redirecting, retaining, and filtering water, through GI installations such as rain gardens, detention ponds, and the reduction of impervious surfaces. LID is, however, primarily implemented and evaluated only on a local scale; few studies have assessed the broader impacts of GI on a larger scale. In fact, most performance calculators that evaluate the effects of GI are only useful at the site scale. Further, most advocates of GI propose its use in new developments, without much attention to retrofitting existing, suburban development. This article seeks to determine what the potential effects of retrofitting an existing, suburban neighborhood with GI for flood protection at a larger scale could be, using Sugar Land, Texas, USA as a case site. First, low-impact facilities are proposed and schematically designed at a site scale for a typical single-family lot. The volume of rainfall that can be retained on site, due to each incorporated feature, is then derived using the Green Values National Storm Water Management Calculator. Using this data, the total volume of rainfall that could be retained if all residential sites in Sugar Land incorporate similar facilities is then projected. The result show that Sugar Land has the capacity to capture 56 billion liters of stormwater water annually if all residential properties use LID. Additional benefits of the use of GI include reduced heat (37%), improved aesthetics and property values (20%), increased recreational opportunities (18%), improved water quality (12%), improved air quality (5%), increased green collar jobs (4%), reduced damage from harmful gas emissions (3%), and increased energy savings (1%), thereby surpassing conventional storm water management techniques [1].

The development of a participatory assessment technique for infrastructure: Neighborhood-level monitoring towards sustainable infrastructure systems.

Climate change and increasing natural disasters coupled with years of deferred maintenance have added pressure to infrastructure in urban areas. Thus, monitoring for failure of these systems is crucial to prevent future impacts to life and property. Participatory assessment technique for infrastructure provides a community-based approach to assess the capacity and physical condition of infrastructure. Furthermore, a participatory assessment technique for infrastructure can encourage grassroots activism that engages residents, researchers, and planners in the identification of sustainable development concerns and solutions. As climate change impacts disproportionately affect historically disenfranchised communities, assessment data can further inform planning, aiming to balance the distribution of public resources towards sustainability and justice. This paper explains the development of the participatory assessment technique for infrastructure that can provide empirical data about the condition of infrastructure at the neighborhood-level, using stormwater systems in a vulnerable neighborhood in Houston, Texas as a case study. This paper argues for the opportunity of participatory methods to address needs in infrastructure assessment and describes the ongoing project testing the best use of these methods.

Participatory Action Research: Tools for Disaster Resilience Education.

PURPOSE: Participatory action research can improve scientific knowledge and community capacity to address disaster resilience and environmental justice. Evidence from the literature suggests that resident participation enhances assessment of environmental risks, raises awareness, and empowers residents to fight for equitable distribution of hazard and climate risk adaptations. Yet, risk assessment and urban planning processes still frequently operate within expertise-driven groups without significant community engagement. Such fragmentation results in part from a lack of appreciation for community expertise in built environment adaptations and educational tools to support resident involvement in the often technical built environment planning processes. APPROACH: A participatory research and place-based education project was developed that enhanced co-learning between residents and researchers while collecting and analyzing local data on flood resilience in the built environment. Five research activities constitute the curriculum of resilience education on stormwater infrastructure: 1) establishment of partnership agreement/MOU, 2) participatory GIS to identify flooding issues, 3) water quality testing and health survey, 4) stormwater infrastructure assessment, and 5) urban/landscape design. Partners included high school and college students, residents, and environmental justice organizations. FINDINGS: Outcomes include a stakeholder approved infrastructure assessment smartphone application, neighborhood maps of drainage issues, a report of water containments, and neighborhood-scaled green infrastructure provisions and growth plans. Findings indicate that participatory research positively contributed to resilience knowledge of participants. VALUE: This paper outlines an interdisciplinary pedagogical strategy for resilience planning that engages residents to assess and monitor the performance of stormwater infrastructure and create resilience plans. The paper also discusses challenges and opportunities for similar participatory projects.