バーチャル・アーバニズム：都市アイデンティティの抽出と可用化のための計算フレームワーク
実施中
中居 楓子
This research develops Virtual Urbanism (VU) — a computational framework for extracting and operationalizing urban identity at the neighborhood scale using multimodal geospatial data. Urban identity is formalized through the Zones of Identity (ZoI) framework, a multi-indicator spatial model computing six indicator groups over a 450 m grid: functional semantic distinctiveness, daily activity centrality, destination pull intensity, landmark prominence, morphological coherence, and visual coherence. Real population flow data is required for two of these groups. Daily activity centrality quantifies behavioral concentration patterns — where urban life actually occurs — complementing structural network metrics derived from street graph analysis. Destination pull intensity measures which spatial units attract visitors from outside the immediate area, a signal that cannot be reliably estimated from static datasets (street maps, imagery) alone. Together these two groups capture the dynamic, movement-based dimension of urban identity that distinguishes lived urban space from its physical configuration. The pilot study covers Setagaya Ward, Tokyo (348 grid cells, 58 km²), selected as a well-documented residential district. The ZoI framework is designed to generalize to approximately 18 Japanese towns for comparative analysis. This work is supported by JST SPRING, Grant Number JPMJSP2108. Outputs include spatially explicit identity scores per cell, contributing to peer-reviewed research in computational urban design and Japanese urban planning.
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グリーンスカヤ マリア / 東京大学 工学系研究科 建築学専攻 川添研究室
豊田啓介 / 東京大学生産技術研究所
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【別途書類手続き。通常より審査期間が長くなります】実人流データ（東京都、2025年5月）
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