Urban Studies & Planning Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1609

Browse

Now showing 1 - 10 of 10

A Smart, Connected, and Sustainable Campus Community: Using the Internet of Things (IoT) and low-cost sensors to improve stormwater management at UMD/Greater College Park
(2024) Hendricks, Marccus D.; Si, Qianyao; Alves, Priscila B. R.; Pavao-Zuckerman, Mitchell A.; Davis, Allen P.; Burke, Tara; Bonsignore, Elizabeth M.; Baer, Jason; Peterson, Kaitlyn; Cotting, Jennifer; Gaunaurd, Pierre; Clegg, Tamara; Loshin, David; Fellow, Andrew; Keen, Taylor; Knaap, Gerrit-Jan
This dataset is part of the research project titled “A Smart, Connected, and Sustainable Campus Community: Using the Internet of Things (IoT) and low-cost sensors to improve stormwater management at UMD/Greater College Park”. We use an Internet of Things (IoT) framework along with low-cost sensors to monitor and improve stormwater management on the University of Maryland Campus. This project provides real-time data that can inform both short term responses and longer-term adaptations to stormwater surface runoff. New buildings, the Purple Line, and other developments on the UMD campus will potentially increase the amount of impervious cover and thus increases the amount of surface runoff. Furthermore, as a result of climate change, the region is expected to experience more frequent and intense rainfall events over shorter periods of time. These two factors have implications for higher quantities of water on campus, pooling water, and potential localized flooding. Stormwater issues can affect the movement of people, goods and services, campus infrastructure, and students as they walk across campus exposing their belongings, and particularly their feet to wetter conditions. As part of more sustainable development, communities and campuses across the world, are beginning to plan for adaptations within the built campus environment to mitigate both larger scale stormwater issues as well as more practical everyday concerns, including wet pathways, and to meet and evaluate the effectiveness of stormwater permitting requirements. The research objectives for this project are fourfold: (1) Install low-cost stormwater sensors that measure water levels at a number of locations across campus that include high pedestrian traffic areas and major campus arterials; (2) Develop an online database for campus water levels; (3) Train students to install and read the stormwater sensors, manage the data platform, interpret the data (4) Use the data to write adaptation plans and designs to better manage stormwater on campus and, perhaps subsequently, downstream from campus. The dataset contains clean stormwater quality and quantity measurements collected from three different sites, along with processed data that describe runoff behavior during selected rainfall events and corresponding catchment characteristics (imperviousness, slope). The spatial data files provide location information for the outfall locations and the corresponding catchment boundaries. The R code provided includes data processing, statistical analysis, and visualization steps.
Should We Leave? Attitudes towards Relocation in Response to Sea Level Rise
(MDPI, 2017-12-04) Song, Jie; Peng, Binbin
The participation of individuals contributes significantly to the success of sea level rise adaptation. This study therefore addresses what influences people’s likelihood of relocating away from low-lying areas in response to rising sea levels. The analysis was based on a survey conducted in the City of Panama Beach in Florida (USA). Survey items relate to people’s risk perception, hazard experience, threat appraisal, and coping appraisal, whose theoretical background is Protection Motivation Theory. Descriptive and correlation analysis was first performed to highlight critical factors which were then examined by a multinomial Logit model. Results show that sea level rise awareness is the major explanatory variable. Coping appraisal is qualitatively viewed as a strong predictor for action, while threat appraisal is statistically significant in driving relocation intention. These factors should be integrated in current risk communication regarding sea level rise.
Spatiotemporal Prediction of Theft Risk with Deep Inception-Residual Networks
(MDPI, 2021-01-29) Ye, Xinyue; Duan, Lian; Peng, Qiong
Spatiotemporal prediction of crime is crucial for public safety and smart cities operation. As crime incidents are distributed sparsely across space and time, existing deep-learning methods constrained by coarse spatial scale offer only limited values in prediction of crime density. This paper proposes the use of deep inception-residual networks (DIRNet) to conduct fine-grained, theft-related crime prediction based on non-emergency service request data (311 events). Specifically, it outlines the employment of inception units comprising asymmetrical convolution layers to draw low-level spatiotemporal dependencies hidden in crime events and complaint records in the 311 dataset. Afterward, this paper details how residual units can be applied to capture high-level spatiotemporal features from low-level spatiotemporal dependencies for the final prediction. The effectiveness of the proposed DIRNet is evaluated based on theft-related crime data and 311 data in New York City from 2010 to 2015. The results confirm that the DIRNet obtains an average F1 of 71%, which is better than other prediction models.
Bicycle Accessibility GIS Analysis for Bike Master Planning with a Consideration of Level of Traffic Stress (LTS) and Energy Consumption
(MDPI, 2022-12-20) McNally, Devin; Tillinghast, Rachel; Iseki, Hiroyuki
Measuring the impact of bicycle infrastructure and other mobility improvements has been a challenge in the practice of transportation planning. Transportation planners are increasingly required to conduct complex analyses to provide supporting evidence for proposed plans and communicate well with both decision makers and the public. Cyclists experience two important factors on roads: (a) travel stress related to the built environment along with the traffic conditions and (b) changes in physical burden due to topography. This study develops a method that integrates an energy consumption calculation and “bicycling stress” score to take into account external conditions that influence cyclists substantially. In this method, the level of traffic stress (LTS) is used to select street segments appropriate for different comfort levels among cyclists and is combined with biking energy consumption, in addition to distance, which is used as travel impedance to consider the effects of slopes and street intersections. The integrated Geographic Information System (GIS) analysis methods are used to evaluate bicycle infrastructure improvements in the coming years in Montgomery County, MD, USA. The analysis results demonstrated that the infrastructure improvements in the county’s bike master plan are well-targeted to improve bicycling accessibility. Furthermore, the use of energy as opposed to distance to generate bikeshed areas results in smaller bikesheds compared to distance-generated bikesheds. The method presented herein allows planners to characterize and quantify the impact of bicycle infrastructure and prioritize locations for improvements.
Come hybrid or high water: Making the case for a Green–Gray approach toward resilient urban stormwater management
(Wiley, 2023-02-07) Hendricks, Marccus D.; Dowtin, Asia L.
120 years or more of unsustainable urban development has damaged the natural environment and disrupted essential ways to stabilize water body overflow and even mitigate pluvial flooding. In light of catastrophic flooding that has occurred globally, a renewed commitment to transforming built surfaces and incorporating more green infrastructures (GIs) has emerged. In fact, one could argue that an overcommitment to GI is being touted in the literature, but largely disconnected from more real-world possibilities, considering all things. In this commentary, we make the case that as cities transition from development patterns of the past and even considering climate-induced storm characteristics of the future, a hybridized solution (e.g., Green–Gray) should be considered. Smaller approaches to urban greening have been implemented in areas that need larger-scale restorations, thus proving to be insufficient. Likewise, the uncertainty surrounding rainfall and storm events has forced us to be more strategically balanced in our efforts to achieve resilience in our stormwater infrastructure. Hybridized solutions that include a diverse set of systems, anchored in local conditions, position us best for effective urban stormwater management. In the absence of such solutions, runoff volumes will continue to rise, flooding will prevail, and disenfranchised communities will remain disproportionately impacted by these impacts of urbanization.
Recent intra-metropolitan patterns of spatial mismatch: Implications for black suburbanization and the changing geography of mismatch
(Wiley, 2022-09-01) Eom, Hyunjoo
Kain's spatial mismatch hypothesis (SMH) (1968) highlights the segregation of Black population in the inner city as well as the decentralization of jobs, both of which played a role in the poor labor market outcomes for Black residents in the inner city. Demographic and economic changes in U.S. metropolitan areas since the late 20th century have transformed the urban spatial structure. This paper aims to revisit the SMH and investigate whether the spatial pattern of mismatch has changed as a result of geographic shifts in the Black population. This paper specifically examines how the suburbanization of the Black population has affected the geographic patterns of mismatch and whether the mismatch is disappearing in the major U.S. metropolitan areas. Using spatial measures of mismatch, this paper presents intra-metropolitan spatial mismatch patterns that capture the clustering of jobs and the Black population based on their relative distributions, showing that the overall level of spatial mismatch declined in major U.S. metropolitan areas between 2000 and 2015. However, geographical evidence reveals that the spatial mismatch has shifted to the outer suburbs, replicating city-suburb spatial inequality, implying that although mismatch may have declined in the inner city due to Black suburbanization, spatial mismatch continue to persist in U.S. metropolitan areas in Black suburbs. The findings also demonstrate that although spatial mismatch generally declined in the inner city, it increased in cities with high inner city polarization, particularly New York, Chicago, San Francisco, and Seattle.
Moving Up the Ladder in Rising Waters: Community Science in Infrastructure and Hazard Mitigation Planning as a Pathway to Community Control and Flood Disaster Resilience
(Ubiquity Press: Open Access, 2022-05-19) Hendricks, Marccus D.; Meyer, Michelle A.; Wilson, Sacoby M.
Public participation is the democratic gateway to more just, inclusive, and resilient communities. However, infrastructure and hazard mitigation planning tends toward top-down, expert-driven processes that fail to meaningfully include communities most at risk of disasters. In this article, we critically examine the potential of citizen science in infrastructure and hazard mitigation planning with a focus on stormwater infrastructure and extreme wet-weather events, as floods are the most common disaster in the US. We review literature on various citizen science approaches, from crowdsourcing to community science, and offer a framework that situates them within Sherry Arnstein’s foundational piece on public participation, a “Ladder of Citizen Participation.” We discuss the opportunities different participatory methods offer for meaningful public involvement, knowledge generation, and ultimately community control and ownership of stormwater and flood infrastructure. We provide case study examples across the US of how public works departments, emergency management, and related organizations have engaged communities around hazard risks and flooding challenges, and offer recommendations for how these programs can be improved. We conclude that in order to produce data needed to mitigate flood disasters and increase trust and public interest in infrastructure needs, civic participation should be grounded in community science, utilizing a multimedia and technological platform. The methods applied and data generated can be leveraged toward public safety, and provide voice, agency, and power particularly to disenfranchised communities most at risk from current hazards and looming climate change impacts.
Increasing Bus Transit Ridership: Dynamics of Density, Land Use, and Population
(California Department of Transportation, Division of Research and Innovation, 2004) Banerjee, Tridib; Myers, Dowell; Irazabal, Clara; Bahl, Deepak
The study explores the possibilities of revitalizing existing urban communities, increasing transit ridership, decreasing jobs-housing imbalance, and mitigating the impacts of sprawl from transit corridor development or TCD, a variant of the more general class of TOD or transit-oriented development. We present findings of a study that focuses on the relationship between transit ridership and density and mixed land use developments along major arterial corridors in Los Angeles. Our research focuses on Ventura Boulevard and Vermont Avenue as a comparative study of two heavily subscribed transit corridors. Our analysis suggests that the predominant land use around these corridors is low-density automobile-oriented development which remains transit –unfriendly. However, the City’s policy environment has undergone favorable changes with the introduction new zoning ordinances. In light of these changes, we develop and recommend spatial and urban design strategies that productively utilize surplus and marginal space along transit corridors to accommodate future population growth. It is our expectation that the densification of the underutilized commercial corridors will create vibrant local economies, increase opportunities for market and affordable housing, revitalize retail, and lead to a fuller use of transit lines and increased ridership, a trend that we have already observed in higher density bus station areas
A Case Study of Preliminary Cost-Benefit Analysis of Building Levees to Mitigate the Joint Effects of Sea Level Rise and Storm Surge
(MDPI, 2018-02-08) Peng, Binbin; Song, Jie
Sea-level rise (SLR) will magnify the impacts of storm surge; the resulting severe flooding and inundation can cause huge damage to coastal communities. Community leaders are considering implementing adaptation strategies, typically hard engineering projects, to protect coastal assets and resources. It is important to understand the costs and benefits of the proposed project before any decision is made. To mitigate the flooding impact of joint effects of storm surge and SLR, building levee segments is chosen to be a corresponding adaptation strategy to protect the real estate assets in the study area—the City of Miami, FL, USA. This paper uses the classic Cost-Benefit Analysis (CBA) to assess the cost efficiency and proposes corresponding improvements in the benefit estimation, by estimating the avoided damages of implementing levee projects. Results show that the city will benefit from implementing levee projects along the Miami River in both a one-time 10 year storm event with SLR and cumulative long-term damage scenarios. This study also suggests that conducting CBA is a critical process before making coastal adaptation planning investment. A more meaningful result of cost effectiveness is estimated by accounting for the appreciation and time value. In addition, a sensitivity analysis is conducted to verify how the choice of discount rate influences the result. Uncertain factors including the rate of SLR, storm intensification, land use changes, and real estate appreciation are further analyzed.
Constraints in household relocation: Modeling land-use/transport interactions that respect time and monetary budgets
(2017) Moeckel, Rolf
Traditionally, integrated land-use/transportation models intend to represent all opportunities of travel and household location, maximize utilities and find an equilibrium in which no person or household could improve their satisfaction any further. Energy scarcity, higher transportation costs, and an increasing share of low-income households, on the other hand, demand special attention to represent constraints that households face, rather than opportunities for utility maximization. The integrated land-use model SILO explicitly represents various constraints, including the price of a dwelling, the travel time to work, and the monetary transportation budget. SILO ensures that no household makes choices that violate these constraints. Implementing such constraints helps SILO to generate more realistic results under scenarios that put current conditions under a stress test, such as a serious increase in transportation costs or severely increased congestion.

Browse

Recent Submissions