Volume XLI-B2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 709-713, 2016
https://doi.org/10.5194/isprs-archives-XLI-B2-709-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 709-713, 2016
https://doi.org/10.5194/isprs-archives-XLI-B2-709-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  08 Jun 2016

08 Jun 2016

ESTIMATION OF HOUSING VACANCY DISTRIBUTIONS: BASIC BAYESIAN APPROACH USING UTILITY DATA

K. Kumagai1, Y. Matsuda2, and Y. Ono2 K. Kumagai et al.
  • 1Dept. of Civil & Environmental Engineering, Setsunan University, 17-8 Ikeda-Nakamachi, Neyagawa, Osaka 572-8508 Japan
  • 2Division of Social Development Engineering, Graduate school of Science and Engineering, Setsunan University, 17-8 Ikeda- Nakamachi, Neyagawa, Osaka 572-8508 Japan

Keywords: Housing vacancy distributions, Utility data, Spatial analysis, Urban planning

Abstract. In this study, we analyze the quality of water hydrant data for estimating housing vacancies based on their spatial relationships with the other geographical data that we consider are correlated with such vacancies. We compare with in-situ vacant house data in several small districts, thus verifying the applicability of the water hydrant data to the detection of vacant houses. Through applying Bayesian approach, we apply the water hydrant data and other geographical data to repeatedly Bayesian updating for the classification of vacant / no vacant houses. We discuss the results of this classification using the temporal intervals associated with turning off metering, fluctuations in local population density, the densities of water hydrants as indicators of vacancies and several other geographical data. We also conduct the feasibility study on visualisation for the estimation results of housing vacancy distributions derived from the fine spatial resolution data.