scholarly journals Impact of the Built Environment Measured at Multiple Levels on Nonmotorized Travel Behavior: An Ecological Approach to a Florida Case Study

2020 ◽  
Vol 12 (21) ◽  
pp. 8837
Author(s):  
Jina Mahmoudi ◽  
Lei Zhang
Keyword(s):  
Built Environment ◽  
Travel Behavior ◽  
Urban Areas ◽  
Structural Equation Models ◽  
Spatial Scales ◽  
Regional Scale ◽  
Environment Factors ◽  
Physical Form ◽  
The Impact

Research continues to reveal the benefits of nonmotorized travel modes such as walking and bicycling. Therefore, identification of the factors that nurture these activities is essential in developing sustainable urban planning policies and designs. Among those factors are the built environment characteristics of the place of residence. To date, research on the role of the built environment in nonmotorized travel has focused on neighborhood-level factors. However, people do not stay within their neighborhoods; they live and work at a regional scale and travel to various destinations and distances each day. Nonetheless, little is known about the impact of built environment factors at larger spatial scales on nonmotorized travel behavior. Guided by the principles of the ecological model of behavior, this study investigates the role of the built environment at hierarchical spatial scales in nonmotorized travel behavior. Multilevel Structural Equation Models have been developed to comprehensively examine the complex links between the built environment and individuals’ nonmotorized travel. Findings indicate that built environment factors at multiple spatial scales can influence nonmotorized travel behavior. Thus, to promote walking and bicycling, more effective policies are those that include multilevel built environment and land use interventions and consider the overall physical form of urban areas.

scholarly journals The Role of Destination’s Built Environment on Nonmotorized Travel Behavior: A Case of Long Beach, California

2017 ◽  
Vol 38 (2) ◽  
pp. 152-166 ◽  
Author(s):  
Dohyung Kim ◽  
Jiyoung Park ◽  
Andy Hong
Keyword(s):  
Built Environment ◽  
Travel Behavior ◽  
Mode Choice ◽  
Long Beach ◽  
Environment Factors ◽  
Household Travel Survey ◽  
Future Policy ◽  
Household Travel ◽  
National Household Travel Survey

This study examines how built environment factors at trip destinations influence nonmotorized travel behavior in the City of Long Beach, California. Using 2008–2009 National Household Travel Survey with California Add-Ons, we found that nonmotorized users tend to choose more clustered destinations than motorized users, and that density, diversity, and design at destinations significantly affect mode choice decisions. Transportation networks and nonmotorized facilities at trip destinations are especially important factors for nonmotorized mode choice. Future policy and research need to consider built environment factors at trip destinations to effectively accommodate nonmotorized travel within a city.

The Impact of Zoning and Built Environment Characteristics on Transit, Biking, and Walking

2019 ◽  
Vol 11 (1) ◽  
pp. 108-129
Author(s):  
Andrew G. Mueller ◽  
Daniel J. Trujillo
Keyword(s):  
Land Use ◽  
Built Environment ◽  
Discrete Choice ◽  
Travel Behavior ◽  
Choice Model ◽  
Mode Choice ◽  
Land Use Regulation ◽  
Policy Action ◽  
Development Goals ◽  
The Impact

This study furthers existing research on the link between the built environment and travel behavior, particularly mode choice (auto, transit, biking, walking). While researchers have studied built environment characteristics and their impact on mode choice, none have attempted to measure the impact of zoning on travel behavior. By testing the impact of land use regulation in the form of zoning restrictions on travel behavior, this study expands the literature by incorporating an additional variable that can be changed through public policy action and may help cities promote sustainable real estate development goals. Using a unique, high-resolution travel survey dataset from Denver, Colorado, we develop a multinomial discrete choice model that addresses unobserved travel preferences by incorporating sociodemographic, built environment, and land use restriction variables. The results suggest that zoning can be tailored by cities to encourage reductions in auto usage, furthering sustainability goals in transportation.

Using Deep Learning to Understand Travel Demands in Different Urban Districts

2021 ◽  
pp. 036119812199458
Author(s):  
Shunhua Bai ◽  
Junfeng Jiao
Keyword(s):  
Built Environment ◽  
Travel Behavior ◽  
Prediction Accuracy ◽  
Travel Demand ◽  
Short Term Memory ◽  
Future Research ◽  
Demand Forecast ◽  
Time And Space ◽  
The University ◽  
The Impact

Travel demand forecast plays an important role in transportation planning. Classic models often predict people’s travel behavior based on the physical built environment in a linear fashion. Many scholars have tried to understand built environments’ predictive power on people’s travel behavior using big-data methods. However, few empirical studies have discussed how the impact might vary across time and space. To fill this research gap, this study used 2019 anonymous smartphone GPS data and built a long short-term memory (LSTM) recurrent neural network (RNN) to predict the daily travel demand to six destinations in Austin, Texas: downtown, the university, the airport, an inner-ring point-of-interest (POI) cluster, a suburban POI cluster, and an urban-fringe POI cluster. By comparing the prediction results, we found that: the model underestimated the traffic surge for the university in the fall semester and overestimated the demand for downtown on non-working days; the prediction accuracy for POI clusters was negatively related to their adjacency to downtown; and different POI clusters had cases of under- or overestimation on different occasions. This study reveals that the impact of destination attributes on people’s travel demand can vary across time and space because of their heterogeneous nature. Future research on travel behavior and built environment modeling should incorporate the temporal inconsistency to achieve better prediction accuracy.

scholarly journals Large but decreasing effect of ozone on the European carbon sink

2018 ◽  
Vol 15 (13) ◽  
pp. 4245-4269 ◽  
Author(s):  
Rebecca J. Oliver ◽  
Lina M. Mercado ◽  
Stephen Sitch ◽  
David Simpson ◽  
Belinda E. Medlyn ◽  
...  
Keyword(s):  
Carbon Storage ◽  
Primary Productivity ◽  
Carbon Sink ◽  
Spatial Scales ◽  
Stomatal Closure ◽  
Regional Scale ◽  
Surface Model ◽  
Background Concentrations ◽  
Tropospheric O3 ◽  
The Impact

Abstract. The capacity of the terrestrial biosphere to sequester carbon and mitigate climate change is governed by the ability of vegetation to remove emissions of CO2 through photosynthesis. Tropospheric O3, a globally abundant and potent greenhouse gas, is, however, known to damage plants, causing reductions in primary productivity. Despite emission control policies across Europe, background concentrations of tropospheric O3 have risen significantly over the last decades due to hemispheric-scale increases in O3 and its precursors. Therefore, plants are exposed to increasing background concentrations, at levels currently causing chronic damage. Studying the impact of O3 on European vegetation at the regional scale is important for gaining greater understanding of the impact of O3 on the land carbon sink at large spatial scales. In this work we take a regional approach and update the JULES land surface model using new measurements specifically for European vegetation. Given the importance of stomatal conductance in determining the flux of O3 into plants, we implement an alternative stomatal closure parameterisation and account for diurnal variations in O3 concentration in our simulations. We conduct our analysis specifically for the European region to quantify the impact of the interactive effects of tropospheric O3 and CO2 on gross primary productivity (GPP) and land carbon storage across Europe. A factorial set of model experiments showed that tropospheric O3 can suppress terrestrial carbon uptake across Europe over the period 1901 to 2050. By 2050, simulated GPP was reduced by 4 to 9 % due to plant O3 damage and land carbon storage was reduced by 3 to 7 %. The combined physiological effects of elevated future CO2 (acting to reduce stomatal opening) and reductions in O3 concentrations resulted in reduced O3 damage in the future. This alleviation of O3 damage by CO2-induced stomatal closure was around 1 to 2 % for both land carbon and GPP, depending on plant sensitivity to O3. Reduced land carbon storage resulted from diminished soil carbon stocks consistent with the reduction in GPP. Regional variations are identified with larger impacts shown for temperate Europe (GPP reduced by 10 to 20 %) compared to boreal regions (GPP reduced by 2 to 8 %). These results highlight that O3 damage needs to be considered when predicting GPP and land carbon, and that the effects of O3 on plant physiology need to be considered in regional land carbon cycle assessments.

Assessing the impact of the built environment on travel behavior: a case study of Buffalo, New York

2011 ◽  
Vol 38 (4) ◽  
pp. 663-678 ◽  
Author(s):  
Andrew J. Tracy ◽  
Peng Su ◽  
Adel W. Sadek ◽  
Qian Wang
Keyword(s):  
New York ◽  
Built Environment ◽  
Travel Behavior ◽  
The Impact

scholarly journals EARTHQUAKE RISK MITIGATION: THE IMPACT OF SEISMIC RETROFITTING STRATEGIES ON URBAN RESILIENCE

2016 ◽  
Vol 20 (3) ◽  
pp. 291-304 ◽  
Author(s):  
Tiago Miguel FERREIRA ◽  
Rui MAIO
Keyword(s):  
Built Environment ◽  
Urban Areas ◽  
Risk Mitigation ◽  
Seismic Retrofitting ◽  
Structural Safety ◽  
City Centre ◽  
Earthquake Risk ◽  
Masonry Building ◽  
Urban Resilience ◽  
The Impact

It is recognized that both community and urban resilience depends on the capacity of built environment to maintain acceptable structural safety levels during and after unforeseeable events, such as earthquakes, as well as to recover their original functionality. Investing in disaster risk mitigation policies is a great step towards promoting urban resilience and community preparedness, implicitly limiting damage to the built environment and subsequently reducing human, economic and environmental losses. Portugal is a moderate to high seismic prone area as the latest estimates indicate that within the next 50 years the country could be severely hit by a strong quake similar to the histori­cal 1755 event, which left a trail of destruction and death, mainly in densely populated areas, such as Lisbon. This manuscript aims to mitigate the impact of earthquake damage scenarios on social and economical terms, as well as evaluating the outcome of implementing traditional retrofitting strategies to existing masonry building stock located in urban areas of high seismic risk, using the old city centre of Horta, Faial island (Azores, Portugal), as a case study.

scholarly journals Understanding self-organization and formal institutions in peri-urban transformations: A case study from Beijing

2019 ◽  
Vol 47 (2) ◽  
pp. 287-303
Author(s):  
Shuhai Zhang ◽  
Gert de Roo ◽  
Ward Rauws
Keyword(s):  
Urban Areas ◽  
Institutional Environment ◽  
Self Organization ◽  
Current Debate ◽  
Formal Institutions ◽  
Rural Village ◽  
Urban Transformations ◽  
The Impact

This article explores the mechanisms of urban self-organization and the role of formal institutions in shaping peri-urban areas. A case study of Gaobeidian, a former rural village that is now part of Beijing, examines the mechanisms of change and the interdependent relations between institutions and bottom-up initiatives that drive peri-urban transformations. The paper presents two main contributions: (1) it identifies the differences between government-controlled planning, shared governance, self-governance and self-organization and how these intertwine in urban transformations; (2) it proposes three distinct roles played by institutions in relation to self-organization: triggering, constraining and enabling. The empirical study of this Chinese case will enrich the current debate on planning for self-organizing cities by revealing the impact of, and the various responses to, self-organization dynamics in a hierarchical institutional environment.

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