Matching Items (3)

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Hierarchy and Innovation: Patent Classes in the Urban Hierarchy of the United States

Description

For nearly a century Walter Christaller's Central Place Theory has served as a guiding framework in studies in economic geography. What began as a means for analyzing the disbursement of

For nearly a century Walter Christaller's Central Place Theory has served as a guiding framework in studies in economic geography. What began as a means for analyzing the disbursement of goods and services has grown into a methodology that encompasses a wide variety of phenomena including industrial location, spatial arrangement and innovative capacity. The aim of this paper is to use this conception on "central places" as a means of exploring the geographic alignment of patent classes, as they function within the existing urban hierarchy of the U.S. Revealing the relative ubiquity of patent classes as they relate to the size of the urban center in which they are developed helps to show the continue role that urban scale has in the development of new technologies. By analyzing the minimum threshold sizes for individual patent classes in urban areas by the overall frequency of the same patent classes we illustrate how the least ubiquitous patent classes are disproportionately found in the largest urban areas and the disbursement of patent types are distributed in a hierarchical fashion. This means the patent classes present in an urban area are also found in urban centers of equal or larger size.

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Date Created
  • 2015-05

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Determinants of bicycle and pedestrian crash severity in San Francisco, CA

Description

Bicyclist and pedestrian safety is a growing concern in San Francisco, CA,

especially given the increasing numbers of residents choosing to bike and walk. Sharing

the roads with automobiles, these alternative road

Bicyclist and pedestrian safety is a growing concern in San Francisco, CA,

especially given the increasing numbers of residents choosing to bike and walk. Sharing

the roads with automobiles, these alternative road users are particularly vulnerable to

sustain serious injuries. With this in mind, it is important to identify the factors that

influence the severity of bicyclist and pedestrian injuries in automobile collisions. This

study uses traffic collision data gathered from California Highway Patrol’s Statewide

Integrated Traffic Records System (SWITRS) to predict the most important

determinants of injury severity, given that a collision has occurred. Multivariate binomial

logistic regression models were created for both pedestrian and bicyclist collisions, with

bicyclist/pedestrian/driver characteristics and built environment characteristics used as

the independent variables. Results suggest that bicycle infrastructure is not an important

predictor of bicyclist injury severity, but instead bicyclist age, race, sobriety, and speed

played significant roles. Pedestrian injuries were influenced by pedestrian and driver age

and sobriety, crosswalk use, speed limit, and the type of vehicle at fault in the collision.

Understanding these key determinants that lead to severe and fatal injuries can help

local communities implement appropriate safety measures for their most susceptible

road users.

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Created

Date Created
  • 2016

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A Novel Transportation Modeling Framework for Use in a Post-Disaster Landscape: Incorporating Whole-Landscape Features

Description

Many coastal cities around the world are becoming increasingly vulnerable to natural disasters, particularly flooding driven by tropical storm and hurricane storm surge – typically the most destructive feature of

Many coastal cities around the world are becoming increasingly vulnerable to natural disasters, particularly flooding driven by tropical storm and hurricane storm surge – typically the most destructive feature of these storms, generating significant economic damage and loss of life. This increase in vulnerability is driven by the interactions between a wide number of complex social and climatic factors, including population growth, irresponsible urban development, a decrease in essential service provision, sea level rise, and changing storm regimes. These issues are exacerbated by the short-term strategic planning that dominates political action and economic decision-making, resulting in many vulnerable coastal communities being particularly unprepared for large, infrequent storm surge events. This lack of preparedness manifests in several ways, but one of the most visible is the lack of comprehensive evacuation and rescue operation plans for use after major storm surge flooding occurs. Typical evacuation or rescue plans are built using a model of a region’s intact road network. While useful for pre-disaster purposes, the immediate aftermath of large floods sees enormous swaths of a given region’s road system flooded, rendering most of these plans largely useless. Post-storm evacuation and rescue requires large amounts of atypical travel through a region (i.e., across non-road surfaces). Traditional road network models (such as those that are used to generate evacuation routes) are unable to conceptualize this type of transportation, and so are of limited utility during post-disaster scenarios. To solve these problems, this dissertation introduces an alternative network conceptualization that preserves important on-network information but also accounts for the possibility of off-network travel during a disaster. Providing this in situ context is necessary to adequately model transportation through a post-storm landscape, one in which evacuees and rescuers are regularly departing from roads and one in which many roads are completely interdicted by flooding. This modeling approach is used to automatically generate routes through a flooded coastal urban area, as well as to identify potentially critical road segments in advance of an actual storm. These tools may help both emergency managers better prepare for large storms, and urban planners in their efforts to mitigate flood damage.

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Created

Date Created
  • 2019