five

URBAN FOREST COMPONENTS INFLUENCING MICROCLIMATE AND COOLING POTENTIAL1

收藏
DataCite Commons2020-08-31 更新2024-07-25 收录
下载链接:
https://scielo.figshare.com/articles/URBAN_FOREST_COMPONENTS_INFLUENCING_MICROCLIMATE_AND_COOLING_POTENTIAL1/5719609/1
下载链接
链接失效反馈
官方服务:
资源简介:
ABSTRACT Planting areas with arboreal vegetation has been proposed as a way to improve the climatic conditions of cities. However, it is not yet known which components of urban forest provide more satisfactory effects. The main goal of this study was to determine which components of the landscape provide greater influence on the microclimate and the cooling potential of the urban forest. For this, areas of different types of urban forest were selected. Using the fixed points method, the microclimate of the areas was analyzed, and by means of mobile transects walking a route of 500 m in an adjacent street, it was possible to analyze the influence in the immediate environment, determining the potential of cooling. The results indicated that the number of individuals and the tree density of the areas showed a statistically strong correlation with the temperature and relative humidity values, as well as with the cooling potential. In addition, it was found that 70% of the influence that the urban forest provides on the immediate surroundings can be explained by the number of trees. It is concluded that the number and density of individuals were the components of urban forest typologies that exerted greater influence on the microclimate, as well as on the cooling effect.

摘要:栽植木本植被的城市区域被认为是改善城市气候环境的可行途径。然而目前尚不明确城市森林(urban forest)的哪些组成部分能带来更理想的调节效果。本研究的核心目标为明确城市景观中的哪些组分对微气候(microclimate)及城市森林降温潜力(cooling potential)具有更显著的影响。为此,研究选取了不同类型的城市林地区域作为研究对象。采用固定点监测法(fixed points method)对各区域的微气候进行分析,并通过在相邻街道开展500米步行移动样线(mobile transects)调查,对城市森林在周边邻近区域的气候影响进行分析,以此明确其降温潜力。结果显示,研究区域内的树木个体数量与树木密度,在统计学上与气温、相对湿度数值及降温潜力均存在显著强相关性。此外,研究发现城市森林对周边邻近区域的气候调节效应中,有70%可通过树木个体数量进行解释。综上可得,树木个体数量与密度是不同类型城市森林的组分中,对微气候及降温效果影响最为显著的要素。
提供机构:
SciELO journals
创建时间:
2017-12-20
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作