3 research outputs found
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Creating Livable Neighborhoods in Old Hill and Six Corners, Springfield, Massachusetts
This report documents the work of the Graduate Urban Design Studio in Springfield’s Old Hill and Six Corners neighborhoods with 12,000 inhabitants. Both neighborhoods are challenged by a very low average household income, housing foreclosures, lot vacancies, lack of substantial home ownership, high traffic volumes and poor quality of open space. The primary goal of the project was to develop a vision to renew Old Hill and Six Corners to improve livability for their residents and create new opportunities for housing, recreation, working and commercial activities. Crucial keys to attaining this goal will be creating a stronger sense of place throughout the neighborhood and improved connectivity to the existing public open spaces like the Watershops Pond and the proposed recreational trail “Arc of Recreation”. Four physical design objectives were explored: Creating a vision for livable streets - a more livable streetscape improves walkability, urban ecology, commercial activities and provides an enriching sensual experience. Creating a better physical environment for commercial and business activities – attractive streets create a new identity and support existing businesses. Creating and improving a pedestrian and bicycle oriented circulation and coherent public open space system. Exploring new housing opportunities - new sites for housing integrate the student population in the neighborhoods.
We are proud that our proposals were recognized after a tornado hit Springfield in June 2011. REBUILDSPRINGFIELD targeted the tornado-impacted neighborhoods in a collaborative effort with engaged citizens and community groups. Our plans created a valuable planning and design framework to rebuild the City
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Inside and Outside the Lines: The Socio-Ecological Differences of Landscape Conservation Partnerships and Their Surrounding Regions
This study examines the socio-ecological criteria forming physical boundaries of regional conservation partnerships and the differences between outside and inside the boundaries. The purpose of this study is to first of all know more about the existing condition of regional partnerships\u27 boundaries, and to seek a method to maximize the efficiency of regional partnership goals to conserve more land. Using a patch-and-corridor matrix ecological model to proves to allow for stronger conservation plans than the existing more opportunity-driven approach currently taken by RCPs
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Applications of Machine Learning Methods in Macroscopic Crash Analysis for Transportation Safety Management
Transportation Safety Planning (TSP) is a statewide-scale tool and combines transportation planning processes with safety aims to increase safety and reduce transportation fatalities and injuries. Traffic safety, which continues to remain a critical issue worldwide, has led to a myriad of modeling techniques to improve analytical capabilities with respect to crash modeling and prediction. State and metropolitan transportation planning processes must be consistent with Strategic Highway Safety Plans. This research aims to identify models and methods to improve the ability to capture variables that have the most significant impact on traffic safety through crash prediction modeling. In order to achieve this research goal, the research objectives are as follows: Identify important variables in TSP. Investigate different areal unit such as traffic analysis zones (TAZs) and traffic analysis districts (TADs). Explore the modifiable areal unit problem (MAUP), which addresses crashes on the boundaries and autocorrelation in macro-level crash modeling. Analysis of before and after crashes and testing Poisson distribution
This research explores the application of parametric and nonparametric approaches to use different models for prediction and inference, with the aim of minimizing the reducible error.
Since a macro-level analysis involves aggregating crashes per spatial unit, a spatial dependence or autocorrelation may arise if a variable of a geographic region is affected by the same variable of the neighboring regions. So, this study also will explore the effect of spatial autocorrelation in modeling crashes in TAZs and TADs