地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (12): 2151-2162.doi: 10.12082/dqxxkx.2021.210063

• 地球信息科学理论与方法 • 上一篇    下一篇

基于城市园林树木景观三维模拟的绿视率估算方法

江锋1,2(), 唐丽玉1,2,*(), 林定1,2, 陈晓玲1,2, 冯先超1,2, 陈崇成1,2   

  1. 1.福州大学空间数据挖掘与信息共享教育部重点实验室,福州 350108
    2.福州大学地理空间信息技术国家地方联合工程研究中心,福州 350108
  • 收稿日期:2021-02-03 修回日期:2021-05-05 出版日期:2021-12-25 发布日期:2022-02-25
  • 通讯作者: *唐丽玉(1972— ),女,福建莆田人,博士,研究员,主要从事地学可视化与虚拟地理环境、虚拟植物研究。 E-mail: tangly@fzu.edu.cn
  • 作者简介:江 锋(1996— ),男,福建福州人,硕士生,主要从事地学可视化与虚拟地理环境、虚拟现实等相关研究。E-mail: 1310041602@qq.com
  • 基金资助:
    国家自然科学基金项目(41971344)

Green View Index Estimation Method based on Three-dimensional Simulation of Urban Tree Landscape

JIANG Feng1,2(), TANG Liyu1,2,*(), LIN Ding1,2, CHEN Xiaoling1,2, FENG Xianchao1,2, CHEN Chongcheng1,2   

  1. 1. Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350108, China
    2. National Engineering Research Center of Geospatial Information Technology, Fuzhou University, Fuzhou 350108, China
  • Received:2021-02-03 Revised:2021-05-05 Online:2021-12-25 Published:2022-02-25
  • Contact: TANG Liyu
  • Supported by:
    National Natural Science Foundation of China(41971344)

摘要:

城市生态景观功能主要是绿色植物对人的视觉作用。绿视率被认为是一种比较好的衡量绿色空间视觉感受的描述因子。目前绿视率的估算主要基于静态的图像或者街景数据,而绿视率是一种动态的量,不同视点有不同的值,且植物是生长变化的。因此,本文提出一种基于数据和模型综合驱动的园林树木三维模拟景观的绿视率计算方法,其利用虚拟地理环境、虚拟植物等技术,通过道路、建筑物等硬质景观数据和树木模型驱动,建立城市园林树木三维景观;根据视觉成像原理,构建虚拟相机,模拟不同视点园林景观的视觉图像,然后识别表征植被信息的像素,从而计算绿视率。本文研发了园林树木景观三维模拟及绿视率估算原型系统,并以城市道路树木景观为例,模拟分析了机动车道中车辆乘客可获得的绿视率,与街景图像提取的绿视率值相近。该方法和系统可用于包含时间变量的不同生长阶段园林树木景观的绿视率评估,支持交互设置不同的视点参数,估算城市任意位置和任意方向的绿视率,评价过去、现在和未来的园林景观绿化质量,以人的视觉感知角度为城市绿地规划提供参考。

关键词: 城市绿化, 绿视率, 视觉感受, 虚拟地理环境, 三维模拟, 城市道路树木景观, 虚拟相机, 虚拟植物

Abstract:

Urban ecological landscape has sensory functions, which describe the visual effect of green plants for human beings. Green view index is considered as a relatively good indicator for measuring the visibility of urban green space, which can reflect different levels of urban vegetation space directly. Green view index is usually calculated using static images or street view data. However, green view index is a variable quantity since the variant of view point location results with very different visual effects and the phenological change of plants. What is more, plants, as organism with life characteristics, are the most important elements in the urban green space landscape, which can change their morphology with time factors constantly and affect the amount of visible green space. In the paper, a green view index calculation method was proposed based on the three-dimensional simulation landscape of garden trees driven by spatial information data of geographic entities and tree architecture and growth model. This method comprises three steps. Firstly, using virtual geographical environment, virtual plants, and other technologies, a three-dimensional urban vegetation landscape was generated according to hard landscape data (e.g. roads, building) and tree models. Secondly, based on visual mechanisms of seeing, virtual cameras were constructed to set observation points and generate the landscape visual images. Thirdly, the visibility analysis was conducted to identify vegetation information visible from each observation point at the pixel level, which can compute the value of green view index. A three-dimensional tree landscape simulation and green view index estimation prototype was developed. Taking urban road greenery scenes (e.g. Jinshan avenue in Fuzhou) as an example, the green view index was estimated and analyzed. The results are closed to those derived from street view images. Therefore, it can effectively reflect the visual feeling of vehicle passengers. It is useful for quantitatively evaluating the visual effects of urban forest states of past, present, or future at different growth stages. It is also suitable to simulate and calculate green view index dynamically by setting view points everywhere and in arbitrary directions. The method can be used as a potential tool to assess the simulation results of urban green space design schemes before they were carried out. It is also helpful for the rational planning of urban green space. It can provide references for the science and rationality of the future landscape of different engineering design schemes, thereby promoting the sustainable development of the city.

Key words: urban vegetation, green view index, visual perception, virtual geographic environments, three-dimensional simulation, urban road greenery scenes, virtual cameras, virtual plants