Travel Matrix Decomposition for Understanding Spatial Long-Distance Travel Structure

Mobile phone location data enable us to obtain accurate and temporally detailed long-distance travel distribution. However, the traditional distribution model cannot normally handle this temporal information. This study proposes an approach for handling information of Considering approach, origin-destination matrix decomposes into two variables (indicators): destination amenity cost. They can be interpreted as composite indicators several that are treated in travel-destination choice multinomial logit model. Because they calculated only from origin destination, we discuss their variations. In study, time changes amenities costs interprefectural Japan confirm value approach. These have succeeded describing pattern domestic Japan. quantified facilitated understanding national land structure. useful outcome measures policy-making. Moreover, these explain applicability Specifically, results a large seasonal variation. indicates parameters (i.e., coefficients variables) not seasonally stable. Therefore, must considered when dealing with travel.