• Survey Research
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• v.12 no.3
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• pp.63-94
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• 2011

Growing worldwide interests in walking are increasing and walking surveys and measuring walking projects are becoming more popular. By the way, we do not have the general survey method on walking yet. The lacks of pedestrian walking features lead to underestimate walking population and the social importance of walking. To solve this problem, Walk21 and Pedestrian Quality Needs projects have tried to build the international standardization in methodology of measuring walking. This study suggests indicator system of the measuring walking and models on the measuring walking proposed by the international measuring walking projects. In addition, we reviewed global governance of those projects and several cases related to the measuring walking. This paper will contribute to domestic walking surveys for participating actively in the ongoing international standardization methodology of walking.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.1
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• pp.19-28
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• 2019

The purpose of this study is to evaluate the walking behavior analysis methodology used in the previous studies, paying attention to the demand for empirical data collecting for urban and neighborhood planning. The preceding researches are divided into (1)Recording, (2) Surveys, (3)Statistical data, (4)Global positioning system (GPS) devices, and (5)Mobile Big Data analysis. Next, we analyze the precedent research and identify the changes of the walkability research. (1)being required empirical data on the actual walking and moving patterns of people, (2)beginning to be measured micro-walking behaviors such as actual route, walking facilities, detour, walking area. In addition, according to the trend of research, it is analyzed that the use of GPS device and the mobile big data are newly emerged. Finally, we analyze pedestrian data based on mobile big data in terms of 'application' and distinguishing it from existing survey methodology. We present the possibility of mobile big data. (1)Improvement of human, temporal and spatial constraints of data collection, (2)Improvement of inaccuracy of collected data, (3)Improvement of subjective intervention in data collection and preprocessing, (4)Expandability of walking environment research.