广州地区花园式屋顶绿化植物调查分析

通过对广州市花园式屋顶绿化植物调查分析,共记录维管植物85科167属220种,其中,蕨类植物3科3属4种,裸子植物5科6属7种,被子植物77科158属209种。通过对优势科和适生种分析,总结出花园式屋顶绿化植物的选取标准;通过对花园式屋顶绿化植物优势种的分析对比,总结出花园式屋顶绿化选择标准,并初步选取海南龙血树等36种植物品种适合应用于花园式屋顶绿化。     

浅析杭州既有建筑屋顶绿化实施情况和存在问题

根据当前杭州市屋顶绿化现状,分析本市屋顶绿化目前存在的问题并提出改进意见。     

关于屋顶绿化微环境的调查研究

以杭州市隽维中心屋顶绿化为对象,分别对温度、湿度、CO2浓度、空气负离子浓度进行对比观测,结果表明,不同的植物配置模式会影响到建筑周围的微环境,从优至劣排序:乔灌草复层式绿地草坪绿地廊架硬质园路。此排序在夏冬两季差异尤其明显。     

成都市屋顶绿化植物评价及其应用

通过对成都市屋顶绿化植物种类及其生长情况进行实地调查,采用5分制评价法对成都市屋顶绿化植物的适应性进行综合评价。结果表明:在成都市屋顶绿化应用的169种植物中,生长良好与较好的植物有141种植物,占总数的83%;而在这141种中,可用的观花植物有76种,芳香植物11种,藤本植物14种,彩叶植物9种。最后探讨了成都市屋顶绿化存在的问题,并提出了发展建议。     

屋顶绿化的植物配置探析

随着城市绿化建设的不断发展,屋顶进行绿化对提高城区绿地率也越来越重要,但在建设过程中会遇到一系列的问题。其中有关于屋顶绿化的植物的配置则是这些问题中最主要的问题之一。本文将以屋顶绿化的简况与原则为基础,对住宅建筑的屋顶绿化的植物配置进行分析,并探析住宅建筑生态改造过程中适宜推广的几种绿化的植物配置,希望能为更好的建设屋顶花园,提高城市绿化率,改善城市生态环境有所帮助。     

浅谈屋顶绿化植物的养护与管理

屋顶绿化是增加城市园林绿化面积的重要途径之一。本文从屋顶绿化植物在生存中面临的问题入手,介绍了屋顶绿化在植物选择、工程施工方面的一些建议,并从水肥管理、整形修剪、病虫害防治、自然灾害预防、养护管理队伍建设等方面,详细阐述了如何养护屋顶绿化植物,以期为屋顶绿化植物健康生长提供借鉴。     

北京地区屋顶绿化植物材料选择研究

从屋顶绿化的分类、植物材料的选择、植物景观营造等方面总结了北京地区屋顶绿化的情况,并列出了常用的屋顶绿化植物材料,为其他地区屋顶绿化材料的选择与应用提供参考。     

屋顶绿化植物的选择原则及配置方式研究

本文从屋顶绿化植物的生长特性和屋顶绿化植物对环境的适应性两个方面研究了屋顶绿化植物的选择原则及配置方式,简要阐述了多种屋顶绿化植物在屋顶环境适应中的重要作用,以期为城市绿化提供一定的参考。     

影响居住建筑屋顶绿化植物造景因素浅析

屋顶绿化作为一种绿化形式,其理论与技术应用的研究已经取得重大进展,但还不够完善。从人为因素、自然环境因素以及植物自身因素3方面对居住建筑屋顶绿化植物选择进行分析与讨论,希望对屋顶绿化的研究提供参考价值。     

郑州市屋顶绿化现状及分析

屋顶绿化在城市绿化美化中占有重要作用,拥有巨大的市场潜力。通过对郑州市现有及施工中屋顶花园的调查勘测,从屋顶绿化的设计和工程两大部分进行研究分析,并对比两种屋顶绿化的建造形式(简单式屋顶绿化和花园式屋顶绿化)。总结郑州市屋顶绿化规划中存在的问题与不足,并针对这些问题和不足提出改进措施和规划意见。     

杭州市城区主干道路绿地现状调查与分析

通过对杭州市城区主干道路绿地进行调查,从道路绿地结构、绿化树种和群落结构类型等方面对杭州主干道路绿地进行分析。结果表明:杭州市道路绿地主要应用的树种有66科、112属、144种,常绿树与落叶树的数量比为1.31∶1.00。为进一步优化道路绿地景观,应提高植物多样性水平,充分发挥路侧绿地的生态功能,并注重道路绿地建设的文化特色。最后讨论了杭州市在道路绿地建设中存在的问题并提出改进意见。     

Assessing the potential of strategic green roof implementation for green infrastructure: Insights from Sumida ward,Tokyo

Urban green spaces, and green infrastructure more generally, provide multiple benefits that can enhance urban livability and sustainability. These range from the mitigation of air pollution and urban heat island (UHI) effect, to multi-dimensional benefits to human wellbeing and biodiversity. However, the expansion of urban green spaces is not always feasible in many cities. In such urban contexts, there have been proposals to utilize rooftops as green roofs in order to gain some of these benefits. This study spatially identifies areas where roofs have the potential to provide different types of benefits associated with urban green spaces if they are retrofitted with green roofs. Through a GIS-based approach we catalogue available roof space in Sumida ward in Tokyo for green roof implementation, and subsequenlty evaluate the potential of each roof patch to offer four types of benefits if retrofitted with a green roof, namely UHI effect mitigation, air pollution mitigation, and benefits to subjective wellbeing and biodiversity. Approximately 25% of the total roof surface in Sumida ward can potentially be used for green roof implementation. Furthermore, about 5.2% and 59% of this area has a respectively high and moderate potential to provide all four benefits if retrofitted with green roofs. This could increase the extent of green spaces by 10% and 120% respectively across the Sumida ward. In this sense, green roofs can become a major element of green infrastructure with ripple positive effects for urban livability and sustainability through the provision of UHI effect and air pollution mitigation, and benefits to subjective wellbeing and biodiversity.     

浅析屋顶花园的生态功能

以屋顶绿化为研究对象,探讨屋顶绿化的生态功能。屋顶绿化具有降低能源消耗、缓解"热岛"效应、雨水收集、改善屋顶的物理性能、降温降燥、增加CO2固化效果、保护生物多样性等生态功能。屋顶绿化生态效益明显,顺应可持续发展的潮流,将会成为本世纪的重要产业之一。     

屋顶绿化降温效果研究

随着屋顶绿化的发展,研究屋顶绿化作为改善城市生态环境的策略之一越来越受到人们的重视。为了研究屋顶绿化对建筑内、外表面的降温效果,选取屋顶绿化实地测量,通过对测量数据的量化分析,结合国内外相关的研究方法和长沙市独特的气候背景,论证屋顶绿化后建筑温度的变化及对于城市热环境的改善。     

A GIS-based mapping methodology of urban green roof ecosystem services applied to a Central European city

Green roofs provide a number of different urban ecosystem services (UESS), e.g. regulation of microclimate, support of air quality improvement, or stormwater retention. To estimate the spatial variation of green roof UESS across an urban area, a GIS-based mapping and spatial analysis methodology was established and applied to the city of Braunschweig, Germany. Based on the analysis of available geodata, in a first step, a quantity of 14,138 rooftops in the study area (14% of all buildings) was found to be generally suitable for greening. This resulted in a green roof area of 3 km². Based on criteria such as roof slope and minimum roof size, nearly two-thirds of these buildings (8596 buildings, 8.6% of total number of buildings) were categorised ‘appropriate’ for greening and subject to green roof UESS analysis.The spatial distribution of green roof UESS was estimated based on the categories thermal urban climate, air quality, stormwater retention and biodiversity. Due to their potential benefits in the four UESS categories an overall assessment resulted in a number of 867 roofs (0.9% of total number of buildings) categorised as ‘high benefit’ from rooftop greening. Another 3550 buildings (3.5%) and 4179 buildings (4.2%) were defined as ‘moderate benefit’ and ‘low benefit’, respectively. The inner city area of Braunschweig appears as a hot-spot of green roof UESS, i.e. higher percentage of ‘high benefit’ green roofs in comparison to residential areas. The proposed method is a simple but straightforward approach to analyse urban green roof UESS and their spatial distribution across a city but it is sensitive to the quality of the available input geodata.     

Can green roofs help with stormwater floods? A geospatial planning approach

Increasing urbanization, impervious space, and the impact of climate change are threatening the future of cities. Nature-based solutions, specifically urban green infrastructures, are seen as a sustainable strategy to increase resilience against extreme weather events, including the escalating occurrence of stormwater runoff flooding. Consequently, urban planners and decision-makers have pushed their efforts toward implementing green infrastructure solutions to reduce the impact of stormwater floods. Among others, green roofs help store water and decrease stormwater runoff impacts on a local scale. This research aims to investigate the effect of surface permeability and green roof implementation on reducing stormwater flooding and subsequently provide urban planners with evidence-based geospatial planning recommendations to improve urban resilience in Helsinki. First, we modeled the current impact of stormwater flooding using the Arc-Malstrom model in Helsinki. The model was used to identify districts under high stormwater flood risk. Then, we zoomed in to a focus area and tested a combination of scenarios representing four levels of green roof implementation, two levels of green roof infiltration rates under 40-, 60-, 80-, 100 mm precipitation events on the available rooftops. We utilized open geographic data and geospatial data science principles implemented in the GIS environment to conduct this study. Our results showed that low-level implementation of green roofs with low retention rates reduces the average flood depth by only 1 %. In contrast, the maximum green roof scenario decreased most of the average flood depth (13 %) and reduced the number of vulnerable sites. The proposed methodology can be used for other cities to develop evidence-based plans for green roof implementations.     

Importance of different components of green roof substrate on plant growth and physiological performance

Green roof substrate is arguably the most important element of a green roof, providing water, nutrients and physical support to plants. Despite this there has been a lack of research into the role that different substrate components have on green roof plant growth and physiological performance.To address this, we assessed the importance of three green roof substrate components (organic matter type, brick particle size and water absorbent additive) for plant growth and plant physiological performance. Lolium perenne (Ryegrass) was grown in eight substrates in a controlled greenhouse environment with a factorial design in composition of (i) small or large brick, (ii) conifer bark or green waste compost organic matter, and (iii) presence/absence of polyacrylamide water absorbent gel (‘SwellGel?’).We found that large brick substrates had a lower water holding capacity than small brick (?35%), which led to decreased shoot growth (?17%) and increased root:shoot ratio (+16%). Green waste compost increased shoot and root growth (+32% and +13%) shoot nitrogen concentration and chlorophyll content (20% and 57%), and decreased root:shoot ratio (?15%) compared to bark. The addition of swell gel increased substrate water holding capacity (+24%), which increased shoot growth (+8%). Total evapotranspiration (a proxy for potential cooling) was increased by greater shoot biomass and substrate water holding capacity. Overall, this study provides one of the first quantitative assessments of the relative importance of commonly used green roof substrate components. It is clear that substrate composition should be considered carefully when designing green roofs, and substrate composition can be tailored for green roof service provision.     

Using superpixel- or pixel-based segmentation for efficient green roof digital image classification and rapid estimation of plant species cover

Green roofs are “nature-based solutions” that provide numerous ecosystem services in the context of urban green infrastructures. Plant species diversity and the associated vegetation communities, in strong interactions with green roof substrate, play a central role in the green infrastructure functioning. In order to better understand the influence of vegetation in relation with the co-benefits provided by green roofs as well as to select suitable species for these usually harsh environments, it is essential to be able to achieve accurate and long-term monitoring of plant communities. In this short communication, two free plugins recently developed for the open-source image analysis software Fiji (a distribution of the freely available ImageJ platform, initially dedicated to biological image analysis) were investigated for their capacity to rapidly and efficiently perform supervised machine-learning for the classification of green roof vegetation photographs, with the aim of estimating individual plant species abundance. Two simple methods are thus described using the Trainable Weka Pixel Segmentation (Arganda-Carreras et al., 2017) or the Trainable Superpixel Segmentation (Salinas Colina et al., 2018), which allowed for rapid, efficient and reproducible classification and estimation of multispecies colonized green roof regardless the color or shape similarities among species or ground cover materials. Finally, recommendations are made for the use of the Trainable Superpixel Segmentation which is particularly convenient for quick and efficient green roof image analysis.     

An initial experimental assessment of the influence of substrate depth on floral assemblage for extensive green roofs

Extensive green roofs have the potential to be used as mitigation tools to compensate for urban habitat loss, but there is little information about how closely these systems emulate ground-based habitats. This study investigated the effect of limited substrate depth on plant assemblages in the initial phase of growth in extensive green roof substrates. Five replicate mesocosms (1 m²) for each of three design treatments: (A) 10 cm aggregate depth with green roof drainage and solid floor, (B) 15 cm aggregate depth with green roof drainage and solid floor, and (C) 15 cm aggregate depth on top of bare earth; were positioned at ground level. Each mesocosm had an identical growth substrate and was seeded with the same seed mix. Plant assemblages were analysed using point-quadrat methods. Significant differences in species composition were observed between treatments that seemed to be related to water availability. Even the deep (15 cm) solid floor green roof treatment showed many significant differences in floral assemblage compared to the identical treatment (C) where plants had access to water in the soil profile. Therefore, it is not possible to exactly recreate most ground-based urban habitats on roofs by simply copying the soil characteristics and floral composition found on the ground. Like for mitigation for habitat loss using extensive green roofs requires the careful manipulation of design elements in order to counteract the limited water availability on green roofs.     

Green roofs in temperate climate cities in Europe – An analysis of key decision factors

This paper aims to identify and assess the main decision factors that are relevant for the diffusion of green roof technology in cities of temperate climate in Europe. A mixed design method was applied to identify relevant factors and to structure these along a Strengths, Weaknesses, Opportunities and Threats framework. The factors were subsequently assessed by a sample of green roof experts, using an Analytical Hierarchy Process. The results indicate that prospects for green roofs are in general rather bright, and that dissemination potential is substantial. Green roofs are particularly likely to benefit from climate change and respective counter-strategies, as they are seen as an adaptation and mitigation measure. However, current barriers to adoption need to be carefully considered. Especially the dilemmatic incentive structures, in that building owners bear most of the risks and potential disadvantages, while the public collectively benefits from green roof advantages, could be a major implementation barrier. Without supportive policies, green roofs are thus unlikely to move from niche to regime level in the near future.