GIS as a tool for selection of sample areas in a travel behaviour survey |
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| Institution: | 1. NewRail, School of Mechanical and Systems Engineering, Newcastle University, Stephenson Building, Claremont Road, Newcastle upon Tyne NE1 7RU, United Kingdom;2. Institute of Transport and Logistics Studies (ITLS), University of Sydney Business School, The University of Sydney, Room 313, Newtown Campus (Located at 144 Burren Street) C37, NSW 2006, Australia;1. School of Construction and Environmental Engineering, Shenzhen Polytechnic, Shenzhen, 518055, China;2. College of Public Administration, Huazhong University of Science and Technology, Wuhan, 430074, China;3. School of Economics and Management, Beijing Forestry University, Room 924, No.35, Tsinghua East Road, Haidian District, Beijing, 100083, China;4. Collage of Public Administration, Central China Normal University, Wuhan, 430079, China;5. National Academy for Mayors of China, Huixin West Street, Chaoyang District, Beijing, 100029, China;1. Faculty of Natural Resources, University of Tehran, Iran;2. College of Agriculture, Shiraz University, Iran;3. Aerospace Research Institute (ARI), Iran;1. Department of Biochemistry, College of Natural Sciences, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon-si, Gangwon-do, 24341, South Korea;2. Advanced Nano Surface Research Group, Korea Basic Science Institute, 169-148 Gwahak-ro, Daejeon, 305-333, South Korea;1. Grupo de Investigación en Agentes y Sistemas Inteligentes (GINAySI), Fac. de Cs. de la Adm., Universidad Nacional de Entre Ríos (UNER), Monseñor Tavella 1424, (3200) Concordia, Entre Ríos, Argentina;2. Artificial Intelligence Research Institute (IIIA-CSIC), Campus UAB – 08193 Bellaterra, Barcelona, Spain;3. Dept. of Computer Science and Engineering, Universidad Nacional del Sur (UNS) and Institute for Computer Science and Engineering (ICIC UNS-CONICET), San Andrés 800, (8000) Bahía Blanca, Buenos Aires, Argentina;4. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Av. Rivadavia 1917, (C1033AAJ) Ciudad Autónoma de Buenos Aires, Argentina |
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| Abstract: | Whilst Geographical Information Systems (GIS) are now used more commonly in transport research and modelling, GIS techniques were used in this study to select similar sample areas (in terms of geography and census attributes) for data collection. For this purpose, a GIS mapping system for Tyne and Wear, UK, was built. The system included topographic maps of the area, boundary maps of Lower Super Output Areas (LSOA), and aggregated census statistics datasets for LSOAs. Criteria relating to census attributes and the nature of transport were employed to identify ‘hotspots’ by GIS enquiry to provide suitably matching areas, which then formed the basis of the sampling frame.The research project was concerned with commuters’ travel choices and so the study needed to identify commuters. In this case-study context, it is not possible to select fully homogeneous areas, so the GIS ‘hotspots’ approach allowed the identification of areas where there were a high concentration of commuters with multiple alternatives for travel to work. A pilot study showed that the GIS origin-based approach was good in collecting a balanced sample, as compared to an employment-based destination survey. This paper explores the benefits and costs of these origin- and destination-based approaches. In the origin-based home sample, households with paper-based surveys were targeted after identification by GIS. This origin approach requires more data preparation compared to the alternative of an employer-based, destination-based sample that could use online survey methodologies.The paper concludes by identifying GIS as an important tool in selecting a sample area for data collection using multiple criteria, but argues that plans for data collection need to be flexibly constructed to overcome unexpected challenges. Although this paper focuses on a transport research case study, the methodology presented can be applied to survey design and selection of sample areas in other disciplines. |
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| Keywords: | GIS Sample selection Methodology Census |
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