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100			_aUsui, Hiroyuki _946053
245			_aStatistical distribution of building lot depth: Theoretical and empirical investigation of downtown districts in Tokyo
260			_bSage, _c2019.
300			_aVol 46, Issue 8, 2019,( 1499-1516 .p)
520			_aA building lot represents one of the most important basic spatial objects of urban form because building lots are basically adjacent to road networks and combine to make an exact whole with no leftover space. Thus, it is important to understand the relationship between the sizes and shapes of building lots and the density of buildings and road networks at a district scale. While building lot sizes and frontages are known to follow a log-normal distribution, respectively, the probability density function that building lot depths follow remains uncertain. Therefore, the research objective is to answer the following research question: What types of statistical distribution of building lot depths are found if the values of building density (the number of buildings per unit area) and road network density (total lengths of road networks per unit area) are given at a district scale? Assuming that (A1) one building lot has one building; (A2) building lot depth is defined as the ratio of building lot size to frontage; and (A3) building lot frontages and depths are independently distributed, I derived the probability density function of rectangular building lot depths as a log-normal distribution. As the result of theoretical investigations, it was found that (1) the probability density function of building lot depths depends not on the building density but on road network density; and (2) it depends not only on road network density but also on the variation in building lot sizes and frontages. For the empirical study of 20 downtown districts of the Tokyo metropolitan region, I tested (A3) and the log-normality of building lot depths and applied the derived function. At a 5% significance level, it was found that the hypothesis of log-normality of building lot depths was accepted in 12 of the 20 selected districts. These findings imply that when we discuss the criteria of the variation in building lot sizes and frontages, we must take into consideration the variation in building lot depths and vice versa. I also derived the probability density function of building setbacks, whose parameters include road network density and building coverage ratio. These findings are expected to provide urban planners with a theoretical basis to not only reconsider the validity of the present road network density and building coverage ratio (form-based codes) but to additionally discuss the relationship between building-lot-scale and district-scale urban physical planning.
650			_aBuilding, _946054
650			_a lot, _946055
650			_adepth, _946056
650			_a log-normal distribution, _946057
650			_a density _946058
773	0		_011590 _915512 _dSage 2019. _t Environment and Planning B: Urban Analytics and City Science
856			_uhttps://doi.org/10.1177/2399808319840366
942			_2ddc _cART