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The Green Window View Index: Automated Multi-Source Visibility Analysis for a Multi-Scale Assessment of Green Window Views

Landscape Ecology(2024)SCI 2区

University of Bonn

Cited 3|Views15
Abstract
Context Providing accessible urban green spaces is crucial for planning and ensuring healthy, resilient, and sustainable cities. The importance of visually accessible urban green spaces increases due to inner urban development processes. Objectives This article proposes a new index, the Green Window View Index (GWVI) for analyzing and assessing visible vegetation, that promotes an integrated planning of urban green spaces and buildings at different scales and levels. It is defined as the proportion of visible vegetation area in a field of view when looking out of a specific window with a defined distance to the window. Methods The method for estimating GWVI consists of three steps: (a) the modeling of the three-dimensional environment, (b) the simulation of the two-dimensional window views using modern rendering engines for three-dimensional graphics, (c) the computation of the GWVI . The method is proposed and tested through a case study of the urban area of Bonn, Germany, using a Digital Terrain Model (DTM), CityGML-based semantic 3D City Model at level of detail (LoD) 2, airborne Light Detection and Ranging (LiDAR) data, and 2D land use data from the official German property cadaster information system (ALKIS). Results With an average processing time of 0.05 s per window view, an average GWVI of 26.00% could be calculated for the entire study area and visualized in both 2D and 3D. Conclusion The proposed engine generates multi-scale visibility values for various vegetation shapes. These values are intended for use in participatory citizenship and decision-making processes for analysis by architects, real-estate appraisers, investors, and urban as well as landscape planners.
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Visibility analysis,Urban green,Open source data,CityGML,LiDAR,ALKIS
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要点】:本文提出了一种新的指数——绿色窗口视野指数(GWVI),用于分析和评估可见植被,旨在推动城市绿色空间和建筑在不同尺度和层面的综合规划。

方法】:估算GWVI的方法包括三个步骤:三维环境的建模、使用现代三维图形渲染引擎模拟二维窗口视野、计算GWVI。

实验】:通过德国波恩市区的案例研究测试该方法,使用数字高程模型(DTM)、基于CityGML的详细程度为2的语义三维城市模型、机载激光雷达(LiDAR)数据和德国官方地产地籍信息系统(ALKIS)的2D土地利用数据,得到整个研究区域的平均GWVI为26.00%,并以0.05秒/窗口视野的平均处理时间在二维和三维中进行了可视化。