• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.343-351
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• 2014

The correlation between regional Walkability Index and their physical socio-economic characteristics has evaluated by the spatial statistical analysis to understand the urban pedestrian environments, where has been emerging the significance, recently. Following to the study, the Walkability Indexes were calculated quantitatively from two administrative districts of Busan and measured Global Local spatial autocorrelation indices. Additionally, the Geographically Weighted Regression model was applied to define the correlation between Walkability Indexes and urban environmental variables. The spatial autocorrelation values and clusters on the Walkability Indexes were derived in statistically significant level. Furthermore, the Geographically Weighted Regression model has been derived more improved inference than the OLS regression model, so as the influence of local level pedestrian environment was identified. The results of this study suggest that the spatial statistical approach can be effective on quantitative assessing the pedestrian environment and navigating their associated factors.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1245-1246
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• 2022

Walkability is an indicator of how much pedestrians are willing to walk and how well a walking environment is created. As walking can promote pedestrians' mental and physical health, there has been increasing focus on improving walkability in different ways. Thus, plenty of research has been undertaken to measure walkability. When measuring walkability, there are many objective and subjective variables. Subjective variables include a feeling of safety, pleasure, or comfort, which can significantly affect perceived walkability. However, these subjective factors are difficult to measure by making the walkability index more reliant on objective and physical factors. Because many subjective variables are associated with human emotional states, understanding pedestrians' emotional states provides an opportunity to measure the subjective walkability variables more quantitatively. Pedestrians' emotions can be examined through surveys, but there are social and economic difficulties involved when conducting surveys. Recently, an increasing number of studies have employed physiological data to measure pedestrians' stress responses when navigating unpleasant environmental barriers on their walking paths. However, studies investigating the emotional states of pedestrians in the walking environment, including assessing their positive emotions felt, such as pleasure, have rarely been conducted. Using wearable devices, this study examined the various emotional states of pedestrians affected by the walking environment. Specifically, this study aimed to demonstrate the feasibility of monitoring biometric data, such as electrodermal activity (EDA) and heart rate variability (HRV), using wearable devices as an indicator of pedestrians' emotional states-both pleasant-unpleasant and aroused-relaxed states. To this end, various walking environments with different characteristics were set up to collect and analyze the pedestrians' biometric data. Subsequently, the subjects wearing the wearable devices were allowed to walk on the experimental paths as usual. After the experiment, the valence (i.e., pleasant or unpleasant) and arousal (i.e., activated or relaxed) scale of the pedestrians was identified through a bipolar dimension survey. The survey results were compared with many potentially relevant EDA and HRV signal features. The research results revealed the potential for physiological responses to indicate the pedestrians' emotional states, but further investigation is warranted. The research results were expected to provide a method to measure the subjective factors of walkability by measuring emotions and monitoring pedestrians' positive or negative feelings when walking to improve the walking environment. However, due to the lack of samples and other internal and external factors influencing emotions (which need to be studied further), it cannot be comprehensively concluded that the pedestrians' emotional states were affected by the walking environment.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.119-126
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• 2019

The active living of the elderly leads to improve their lives and enhance social networks. In the view of the active living, the walkability is an essential factor for the elderly's daily life. To support the active living, making age-friendly environment is important. Considering that the elderly mainly carry out activities through walking, making the age-friendly walking environment is a preliminary action. The existing studies applied various methods such as surveys by experts. In spite of the benefits in theirs, there is still a limitation that current walkability measurement methods did not incorporate the actual elderly's walking activity. Thus, the purposes of this study is to measure the elderly's walking quantitatively using a wearable sensor, and to investigate the feasibility of comparing several walking environments based on the data collected from the actual elderly's walking. To do this, experiment was conducted in four types environments with 22 senior subjects. The walkability was measured by walking stability represented quantitatively as Maximum Lyapunov Exponent (MaxLE). Through the experiment results, it was confirmed that the stability of the elderly walking was different according to the walking environment, which also meant that bodily responses (walking stability) is highly related to walkability. The results will provide an opportunity for the continuous diagnosis of walking environments, thereby enhancing the active living of the elderly.

• Journal of Preventive Medicine and Public Health
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• v.52 no.6
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• pp.405-415
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• 2019

Objectives: The aim of this study was to evaluate the associations of frailty with perceived neighborhood walkability and environmental pollution among community-dwelling older adults in rural areas. Methods: The participants were 808 community-dwelling men and women aged 65 years and older in 2 rural towns. Comprehensive information, including demographics, socioeconomic status, grip strength, polypharmacy, perceived neighborhood environment (specifically, walkability and environmental pollution), and frailty, was collected from participants using face-to-face interviews conducted between June and August 2018. Perceived neighborhood walkability was measured using 20 items that were selected and revised from the Neighborhood Environment Walkability Scale, the Neighborhood Walkability Checklist from the National Heart Foundation of Australia, and the Physical Activity Neighborhood Environment Survey. The Kaigo-Yobo Checklist was used to assess participants' frailty. Results: The overall prevalence of frailty in this community-dwelling population was 35.5%. Sex, age, cohabitation status, educational attainment, employment status, grip strength, and polypharmacy were significantly associated with frailty. In the logistic regression analysis, frailty was associated with low perceived neighborhood walkability (adjusted odds ratio [aOR], 0.881; 95% confidence interval [CI], 0.833 to 0.932; p<0.001) and severe perceived neighborhood environmental pollution (aOR, 1.052; 95% CI, 1.017 to 1.087; p=0.003) after adjusting for sex, age, cohabitation status, educational attainment, employment status, monthly income, grip strength, and polypharmacy. Conclusions: More studies are warranted to establish causal relationships between walkability and environmental pollution and frailty.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.62-70
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• 2016

Ensuring walkability in a city where pedestrians and vehicles coexist is an issue of critical importance. The relative relationship between vehicle transit and walkability improvements complicates the evaluation of walkability, which thus necessitates the formation of a quantitative standard by which a methodological measurement of walkability can be achieved inside the pedestrian network. Therefore, a model is determined whereby quantitative indices such as, but not limited to, experiences of accessibility, mobility, and convenience within the network are estimated. This research proposes the integration of space syntax theory and the logit path choice model in the evaluation of walkability. Space syntax theory assesses adequacy of the constructed pedestrian network through calculation of the link integration value, while the logit model estimates its safety, mobility, and accessibility using probability. The advantage of the integrated model hence lies in its ability to sufficiently reflect such evaluation measures as the integration value, mobility convenience, accessibility potential, and safety experienced by the demand in a quantitative manner through probability computation. In this research, the Dial Algorithm is used to arrive at a solution to the logit model. This process requires that the physical distance of the pedestrian network and the perceptive distance of space syntax theory be made equivalent. In this, the research makes use of network expansion to reflect wait times. The evaluation index calculated through the integrated model is reviewed and using the results of this sample network, the applicability of the model is assessed.

• Current Research on Agriculture and Life Sciences
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• v.27
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• pp.59-67
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• 2009

The purpose of this study is to propose the methodology for introducing green infrastructure that can improve the health of citizens by promoting walkability. The methodology is composed of the following three phases: classification of the types of green spaces, selection of core green spaces with two separate analyses, and introduction of the framework of green infrastructure to promote walkability. In the first phase, the classification of the types of green spaces was carried out in order to understand existing distribution pattern of green spaces in study site. In the second phase, walkable blocks were selected by such methods as walkability value. Through these two analyses, all the blocks were divided into three groups according to the ranking figured up the second analyses' results. The blocks in the first group, the group involved in the top 30% and having the greatest ranking, were defined as walkable blocks. In the last phase, a basic frame of the green infrastructure in study site was introduced by connecting the walkable blocks with using other blocks and the green spaces over 1ha. In case study, 28 important green spaces and 35 walkable blocks were selected through the two analysis process. Then, the basic framework of green infrastructure based on the selected 28 important green spaces and 35 walkable blocks was introduced. The methodology applied to this study can be used to get the best selections of the proper green infrastructure in accordance with the purpose of the ecological and recreational local development. In particular, this study will suggest a specific analysis model to use for the ecological and walkable urban planning with green spaces existing in the city.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.288-297
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• 2018

Walking plays an important role in promoting peoples' health and reducing the increasing pressure of traffic congestion. However, for cities in developing countries located in areas with unfavorable weather, such as hot and humid weather, there is not much research on walking. Therefore, this study focuses on the walkability and the effect of the built environment on walking in the center district of Ho Chi Minh City, Vietnam. The correlation between the built environment and walking frequency of people was analyzed. Besides common elements that have been used in previous studies, other specific factors of the built environment were determined to estimate the walkability index. The results were then compared with the amount of walking obtained from surveys of local people. The result shows that people tend to walk more in the areas with a higher walkability index.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.1-10
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• 2022

Attempts to interpret human perspectives using computer vision have been developed in various fields. In this paper, we propose a method for evaluating the walking environment through semantic segmentation results of images from road images. First, the Kakao Map API was used to collect road images, and four-way images were collected from about 50,000 points in JeonJu. 20% of the collected images build datasets through crowdsourcing-based paired comparisons, and train various regression models using paired comparison data. In order to derive the walkability score of the image data, the ranking score is calculated using the Trueskill algorithm, which is a ranking algorithm, and the walkability and analysis using various regression models are performed using the constructed data. Through this study, it is shown that the walkability of Jeonju can be evaluated and scores can be derived through the correlation between pixel distribution classification information rather than human vision.

• Transportation Technology and Policy
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• v.12 no.3
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• pp.58-65
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• 2015

• Journal of Preventive Medicine and Public Health
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• v.51 no.5
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• pp.227-233
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• 2018

Objectives: Chronic diseases, including back pain, result in significant patient morbidity and societal burden. Overall improvement in physical fitness is recommended for prevention and treatment. Walking is a convenient modality for achieving initial gains. Our objective was to determine whether neighbourhood walkability, acting as a surrogate measure of physical fitness, was associated with the presence of chronic disease. Methods: We conducted a cross-sectional study of prospectively collected data from a prior randomized cohort study of 227 patients referred for tertiary assessment of chronic back pain in Ottawa, ON, Canada. The Charlson Comorbidity Index (CCI) was calculated from patient-completed questionnaires and medical record review. Using patients' postal codes, neighbourhood walkability was determined using the Walk Score, which awards points based on the distance to the closest amenities, yielding a score from 0 to 100 (0-50: car-dependent; 50-100: walkable). Results: Based on the Walk Score, 134 patients lived in car-dependent neighborhoods and 93 lived in walkable neighborhoods. A multivariate logistic regression model, adjusted for age, gender, rural postal code, body mass index, smoking, median household income, percent employment, pain, and disability, demonstrated an adjusted odds ratio of 2.75 (95% confidence interval, 1.16 to 6.53) times higher prevalence for having a chronic disease for patients living in a car-dependent neighborhood. There was also a significant dose-related association (p=0.01; Mantel-Haenszel chi-square=6.4) between living in car-dependent neighbourhoods and more severe CCI scores. Conclusions: Our findings suggest that advocating for improved neighbourhood planning to permit greater walkability may help offset the burden of chronic disease.