Booth Pieter N, Law Sheryl A, Ma Jane, Buonagurio John, Boyd James, Turnley Jessica
Ramboll Environ, Seattle, Washington, USA.
Contact through Pieter N Booth.
Integr Environ Assess Manag. 2017 Sep;13(5):926-938. doi: 10.1002/ieam.1944. Epub 2017 Jul 12.
This paper reviews literature on aesthetics and describes the development of vista and landscape aesthetics models. Spatially explicit variables were chosen to represent physical characteristics of natural landscapes that are important to aesthetic preferences. A vista aesthetics model evaluates the aesthetics of natural landscapes viewed from distances of more than 1000 m, and a landscape aesthetics model evaluates the aesthetic value of wetlands and forests within 1000 m from the viewer. Each of the model variables is quantified using spatially explicit metrics on a pixel-specific basis within EcoAIM™, a geographic information system (GIS)-based ecosystem services (ES) decision analysis support tool. Pixel values are "binned" into ranked categories, and weights are assigned to select variables to represent stakeholder preferences. The final aesthetic score is the weighted sum of all variables and is assigned ranked values from 1 to 10. Ranked aesthetic values are displayed on maps by patch type and integrated within EcoAIM. The response of the aesthetic scoring in the models was tested by comparing current conditions in a discrete area of the facility with a Development scenario in the same area. The Development scenario consisted of two 6-story buildings and a trail replacing natural areas. The results of the vista aesthetic model indicate that the viewshed area variable had the greatest effect on the aesthetics overall score. Results from the landscape aesthetics model indicate a 10% increase in overall aesthetics value, attributed to the increase in landscape diversity. The models are sensitive to the weights assigned to certain variables by the user, and these weights should be set to reflect regional landscape characteristics as well as stakeholder preferences. This demonstration project shows that natural landscape aesthetics can be evaluated as part of a nonmonetary assessment of ES, and a scenario-building exercise provides end users with a tradeoff analysis in support of natural resource management decisions. Integr Environ Assess Manag 2017;13:926-938. © 2017 SETAC.
本文回顾了美学方面的文献,并描述了远景和景观美学模型的发展。选择了空间明确的变量来代表对审美偏好很重要的自然景观的物理特征。远景美学模型评估从超过1000米远处观看的自然景观的美学,而景观美学模型评估观众1000米范围内湿地和森林的美学价值。每个模型变量都在EcoAIM™(一种基于地理信息系统(GIS)的生态系统服务(ES)决策分析支持工具)中,基于像素特定的基础上使用空间明确的指标进行量化。像素值被“分类”为排名类别,并为选定变量分配权重以代表利益相关者的偏好。最终的美学分数是所有变量的加权总和,并被赋予1到10的排名值。排名美学值按斑块类型显示在地图上,并集成在EcoAIM中。通过将设施离散区域的当前状况与同一区域的开发情景进行比较,测试了模型中美学评分的响应。开发情景包括两座6层建筑和一条取代自然区域的步道。远景美学模型的结果表明,视域面积变量对美学总分的影响最大。景观美学模型的结果表明,整体美学价值增加了10%,这归因于景观多样性的增加。这些模型对用户分配给某些变量的权重很敏感,这些权重应设置为反映区域景观特征以及利益相关者的偏好。这个示范项目表明,自然景观美学可以作为生态系统服务非货币评估的一部分进行评估,情景构建练习为最终用户提供了权衡分析,以支持自然资源管理决策。《综合环境评估与管理》2017年;13:926 - 938。©2017 SETAC。