水害に対するコミュニティレジリエンス評価のための地理空間指標

国立大学法人長岡技術科学大

A Decision-Making Tool for Urban Planners: A Framework to Model the Interdependency among Land Use, Accessibility, Density, and Surface Runoff in Urban Areas

The purpose of this study was to evaluate the four-dimensional relationship between land use, accessibility, density, and surface runoff in urban areas. In contemporary literature, a series of studies have been conducted that extensively discuss the natural components associated with the surface runoff in urban areas. However, the dynamic and complex dimensions of the urban form, such as land use, accessibility, and density, are yet to be fully understood. In this study, a 4D diagram was utilized to identify relationships between dimensions, in addition to decision tree analysis, to explore the structural flow between selected variables. Furthermore, a structural equation modeling (SEM) approach was employed with the purpose of investigating the direct, indirect, and moderating effects on the targeted dependent variable, surface runoff. The results of the analysis reported a strong correlation between land use, accessibility, density, and surface runoff, with an R-squared value of 0.802, which indicates an acceptable model accuracy by the international standard. A positive relationship between the four dimensions was indicated by the higher accessibility; the higher density in terms of a higher floor space index (FSI), ground space index (GSI), and open space; the building height of the adjacent buildings; the higher diversity of the land use; and the higher surface runoff. Accordingly, the findings of the study offer policy implications in the fields of land use planning, zoning regulations and overall urban development planning towards achieving climate resilient cities

An Urban Density-Based Runoff Simulation Framework to Envisage Flood Resilience of Cities

Assessing the influence of urban density on surface runoff volume is vital for guiding the built-form expansions toward flood-resilient cities. This paper attempts to develop a spatial simulation framework to assess the impact of urban density on the level of surface runoff (SR), at the scale of the micro-watershed. This paper proposes a spatial simulation framework that comprehensively captures the influence of urban density dynamics over surface runoff. The simulation model consists of 13 proxies of urban density that are identified through a systematic literature review. The model is formulated through three case applications in Colombo, Sri Lanka; and validated statistically and empirically with reference to flooding events that occurred in 2021–2022. The possible planning interventions for reducing urban flooding are analyzed through an AI-based application of Decision Tree Analysis. The model results indicated that impervious coverage, open space ratio, and road density have the most significant impact on surface runoff volumes in selected micro-watersheds. The decision-making process for planning the built environment for reducing urban flooding is demonstrated by three possible density control options with a prediction accuracy of 98.7%, 94.8%, and 93.5% respectively. This contributes a novel framework to capture the density dynamics of built form in surface runoff simulations by three density areas (3Ds): density, diversity, and design; and to demonstrate the decision-making process for controlling the density of built form in reducing urban flooding

A Decision-Making Tool for Urban Planners: A Framework to Model the Interdependency among Land Use, Accessibility, Density, and Surface Runoff in Urban Areas

The purpose of this study was to evaluate the four-dimensional relationship between land use, accessibility, density, and surface runoff in urban areas. In contemporary literature, a series of studies have been conducted that extensively discuss the natural components associated with the surface runoff in urban areas. However, the dynamic and complex dimensions of the urban form, such as land use, accessibility, and density, are yet to be fully understood. In this study, a 4D diagram was utilized to identify relationships between dimensions, in addition to decision tree analysis, to explore the structural flow between selected variables. Furthermore, a structural equation modeling (SEM) approach was employed with the purpose of investigating the direct, indirect, and moderating effects on the targeted dependent variable, surface runoff. The results of the analysis reported a strong correlation between land use, accessibility, density, and surface runoff, with an R-squared value of 0.802, which indicates an acceptable model accuracy by the international standard. A positive relationship between the four dimensions was indicated by the higher accessibility; the higher density in terms of a higher floor space index (FSI), ground space index (GSI), and open space; the building height of the adjacent buildings; the higher diversity of the land use; and the higher surface runoff. Accordingly, the findings of the study offer policy implications in the fields of land use planning, zoning regulations and overall urban development planning towards achieving climate resilient cities