Abstract
This study aimed to develop a new method for estimating the spatial distribution of vacant houses using municipal public big data and sample field surveys instead of a field survey of the whole municipal area. This can help reduce the cost, time, and labor involved in conducting vacant house surveys. For this purpose, we developed a vacant house database to integrate various public big data with field survey results for different parts of Japanese municipalities (Kagoshima and Asakura). With our newly developed method, we could estimate the spatial distribution of vacant houses with high reliability utilizing crosstab tables developed from the database. The results help to realize a method for conducting surveys of vacant house distribution in broad areas in a quick, inexpensive, and continuous manner, which has not yet been achieved by previous studies.
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Acknowledgements
This study received tremendous cooperation from the cities of Kagoshima and Asakura in Japan. We would like to thank them and all those people without whose cooperation this study would not have been realized. In addition, we would like to thank Editage (www.editage.jp) for English language editing.
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Akiyama, Y. et al. (2020). Estimating the Spatial Distribution of Vacant Houses Using Public Municipal Data. In: Kyriakidis, P., Hadjimitsis, D., Skarlatos, D., Mansourian, A. (eds) Geospatial Technologies for Local and Regional Development. AGILE 2019. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-030-14745-7_10
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DOI: https://doi.org/10.1007/978-3-030-14745-7_10
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