Research on the Impact of Panoramic Green View Index of Virtual Reality Environments on Individuals’ Pleasure Level Based on EEG Experiment

Green View Index (GVI) is a core indicator to measure urban quality. Identifying proper ranges of GVI has become a significant proposition in Landscape Architecture to design environments that can increase individuals’ pleasure level. However, quantitative research on the pleasure level impacted by varied GVIs is still inadequate. This research explores the changes of pleasure level through EEG data collection and questionnaire survey under panoramic scenarios with different panoramic GVIs, which can represent more environmental elements than two-dimensional images. By adding shrubs and trees gradually, this experiment precisely set five scenarios with the GVI changing from 0 to 30%, 60%, 90%, and 0. Research results show that 1) individuals’ pleasure level dropped to the lowest when they first enter the scenario with a panoramic GVI of 0, but when panoramic GVI increased from 0 to 30% and to 60%, the pleasure level increased and finally researched the highest; 2) in an environment with a panoramic GVI of 90%, individuals’ pleasure level significantly reduced, while some participants self-reported the sense of fear and oppression; and 3) when shifting panoramic GVI from 90% to 0, the bright and open space increased participants’ pleasure level. All these findings reveal that individuals’ pleasure level reached the highest under the scenario with 60% panoramic GVI; extremely high panoramic GVI may lead to negative emotions; and landscape with carefully designed panoramic GVIs can improve one’s pleasure level. Future research may probe into the relationship between GVI and individuals’ pleasure level from more perspectives to provide reference for the design, optimization, and evaluation of outdoor urban greening.     

Research on the Influencing Factors of Users’ Perception of the Inclusiveness of Urban Parks Based on the Grounded Theory

The improvement of the inclusiveness of urban parks can guarantee the recreational opportunities and experience of different user groups, especially the vulnerable ones, and is also an important way to promote the justice of urban green landscape. The research explores the influencing factors to park users’ perception and evaluation on the inclusiveness of urban parks. Through the three-level data coding and analysis, a model consisting of eight main categories (i.e. site conditions, site usage, independent mobility, supply-demand matching capacity of space and facilities, interference and limitation of recreational activities, positive emotional experience, broad social participation, and place identity) which cover 30 influencing factors to individuals’ perception of the inclusiveness of urban parks is established. The model shows that park users evaluate the inclusiveness of urban parks upon their observation of site conditions and usage, and their own recreational experience; while the latter is affected by both physical and psychological factors related to passive exclusion and active exclusion, according to the concept of design exclusion. The disparity of the physical environmental quality of urban parks would lead to users’ different emotions and feelings about recreational activities. The model helps clarify the path and key factors of inclusiveness evaluation and provides a theoretical reference for future research and practice of landscape justice.     

SLOWING DOWN FAST CITIES WITH DESIGNED EXPERIENCES

To challenge the stupefying homogeneities produced by dense and fast urban environments, designers should offer a range of experiences to create a “slowing city,” which first relies on the understanding of the character and range of “slow experiences,” then requires an empiricallydriven approach to attain it. Phenomenologically, slow experiences can be social or solitary; both are discussed. The former comes from “event” experiences that facilitate meaningful interactions among people, while the latter promotes a shift into “being mode” which can help replenish human’s attention. Using findings in psychology and neurocognition, this article suggests that architects, landscape designers, and urbanists adopt a scientifically-grounded phenomenological approach to designing healthy urban environments where people can flourish. More attention is required to investigate people’s experience of surfaces and textures, and of compositions with varying levels of patterned complexity, as well as the changeability of design features and approaches to combat habituation.     

Influencing Mechanism of Ecological Aesthetic Preference on Urban River Ecological Restoration: A Case Study of Kunshan,Jiangsu Province

To balance the ecological–aesthetic relationship in urban river ecological restoration, the research analyzed the ecological aesthetics performance of related practice. By defining „ecological aesthetic preference” and establishing a triple framework of ecological aesthetic preference on urban riverfronts, the research summarized three major factors that impact ecological aesthetic preference. With the Urban River Survey method, 24 typical river section samples in Kunshan, Jiangsu Province were selected. Through correlation analysis and optimal scaling regression model, relevant characteristics and influencing mechanisms were analyzed. The results include that: 1) Individuals’ ecological awareness and knowledge level has the most significant impact, followed by ecological factor characteristics of riverfronts and individuals’ social–cultural characteristics; 2) The respondents having higher cognition on ecosystem services show a stronger aesthetic preference for urban riverfronts; and 3) Vegetation characteristics impact ecological aesthetic preference more than material and physical habitat characteristics, and different combinations would lead to various overall benefits of urban riverfronts. Therefore, urban river ecological restoration should better integrate ecological values and aesthetic values by flexibly combining spatial elements, meanwhile fully consider social demands for urban riverfronts, to promote people’s ecological awareness and knowledge level and provide them with better landscape perception of ecosystem services.     

Built Environment Supported by Cognitive Sciences: From Aesthetic Judgment to Intelligent Management

The knowledge integration of Cognitive Sciences and other related fields supports the rethinking of environmental aesthetic experience. Compared with the explicit logical reasoning, aesthetic judgment is an implicit way for the brain to process information based on personal instincts or experiences. As a rapid information processing of the environment, the experiencing of beauty facilitates individuals’ cognition of environmental information and their prompt making of beneficial behaviors for survival. Compared with human’s instinctive love to the nature (or biophilia), our attitude and preference towards natural landscapes is more complicated. Seemingly complex environmental perceptions can be simplified and measured promoting corresponding research and designs. Meanwhile, the multidisciplinary integration provides insights for technologies including Artificial Intelligence and helps people obtain external information through different input channels. In this issue, LA Frontiers attempts to encourage researchers to explore a more profound understanding of environmental perception. The combination of scientific knowledge and technology can contribute to the creation of intelligent built environment that can actively respond to people’s needs.     

Placemaking Based on Site Experience—Landscape Design of Parkhill Commons in Shenzhen

Placemaking of public open spaces, such as community parks and streetscapes that are foundational to residents’ daily social and recreational life, can significantly influence their site experience. Scholars have explored the influence of such kind of experience on users’ behavioral, physical, and mental conditions from multiple perspectives including attention restoration and stress reduction. However, the findings are seldom applied in practice to convey certain design concepts. This article introduces the landscape design project of Parkhill Commons in Shenzhen. The project team reviewed relevant research findings, and characterized the health-promoting restorative environment and social-capital-friendly communities. Accordingly, strategies for activity zones, planting design, service facilities, and slow-traffic neighborhoods were proposed to enhance site experience and serve nearby residents by creating vital and pleasant community-level public open spaces, and to maximize the social benefits and reinforce community cohesion. After completion, the project team has investigated the site usage and the public’s evaluation, in order to stimulate reflections on design strategies. Results from the questionnaire survey and field observation show the effect of placemaking strategies on users’ site experience. This article provides references for placemaking practice of community-level public open spaces and is expected to help bridge the gap between theoretical research and design practice.     

Machine learning-based automatic control of tunneling posture of shield machine

For a tunnel driven by a shield machine, the posture of the driving machine is essential to the construction quality and environmental impact. However, the machine posture is controlled by the experienced driver of shield machine by setting hundreds of tunneling parameters empirically. Machine learning(ML) algorithm is an alternative method that can let the computer to learn from the driver’s operation and try to model the relationship between parameters automatically. Thus, in this paper, three...     

建筑系馆体验性--以内蒙古工业大学建筑系馆为例

建筑教育重视对学生体验及认知能力的培养。建筑系馆是建筑学子专属的体验学习场所,具有体验性。建筑系馆体验性会激发学生对系馆的体验学习,引导学生通过建筑体验提升自身专业认知和设计能力。本文以内蒙古工业大学建筑系馆为例,从工业改造、功能空间、生活场所、设计进程四方面分析建筑系馆体验性对系馆内学生建筑体验及学习的作用。体验性在今后建筑系馆的营造中应得到充分显现。     

Designing Attention—Research on Landscape Experience Through Eye Tracking in Nanjing Road Pedestrian Mall (Street) in Shanghai

To understand the attention distribution and visual cognition in streets, this study conducted an experiment on Nanjing Road Pedestrian Mall (Street) using Head-mounted eye-trackers. Participants’ attention distribution were analyzed via Area Of Interest (AOI) during real-life walking scenarios, combining with several experiment tasks (i.e., destination selection, point-of-interest photography, and in-depth interviews), to capture participants’ naturalistic decision-making. The study combined automatic semantic segmentation with manual audit to code participants’ attention fixation duration and proportion by AOIs. A new indicator „information density,” which is the ratio of the attention percentage to the exposure percentage of a given environmental element, was introduced to describe the efficiency of environmental elements on attracting attentions. Findings revealed information density varies across environmental elements: higher information density was found in sign, building entrance, brand name, and poster; the lower was found in building, sky, and ground; while tree and person fell in between. Findings hence suggest environmental elements of higher information density (such as business signs) should be systematically designed to enhance desired experiences. Findings also indicated that personalized experiences are more likely to induce positive associations about environment which eventually lead to place attachment.     

A measure of restorative quality in environments

Restorative environments help renew psychological resources depleted in environments that do not fully support intended functions. The design of restorative environments can be aided and underlying theory elaborated with a means for measuring psychological factors thought to work in restorative experiences. This paper reports on four studies carried out to develop such a measure, the Perceived Restorativeness Scale (PRS). Each study employed several strategies for assessing reliability and validity. Factor analysis was used to examine the stability of the measure's factor structure across different sites and studies. To assess criterion, convergent, and discriminant validities, measures of emotional states and other environmental qualities were also completed for each site. The sites selected for evaluation differed on theoretically relevant dimensions (natural‐urban; outdoor‐indoor), enabling checks on the PRS's sensitivity to meaningful differences among environments. The results were consistent across the studies, which also involved different subject populations (American, Swedish, Finnish) and presentation modes (on‐site, video, photographic slides). Although the factor analytic results introduce some interpretive qualifications, substantial validity coefficients and sensitivity to meaningful differences between sites speak to the utility of the measure.     

探寻场地的场所精神——基于感官之上的场所体验

该文从创作主体的角度出发,探寻了场地特征和场所精神对于场地设计的重要意义,并从使用者的角度即以人的场所体验和视觉、听觉、触觉、嗅觉、味觉五大感官反应出发,通过对典型场地设计作品的解读,重新审视场地场所精神的意义。从而得出结论:知觉体验触发体验者领会场所精神,同时也揭示了场地设计的新角度,即将人类知觉体验的五要素纳入场地设计,使场地设计更具有人文性与地域性,进而完善和塑造场地的场所精神,提高场地设计作品的感染力。     

度假酒店中的感官体验设计

体验经济的到来,使人们越来越注重从不同的生活体验中获取有价值意义的感受。本文通过对度假酒店中顾客消费需求的研究,阐述建筑设计中需要重视感官刺激带来的体验的论点,分析了感官体验设计在度假酒店中的成因和要点,结合实例从视觉、听觉、嗅觉和触觉四个角度来论证感官体验作为一种最直接、最朴素的体验形式,如何能生动地呈现在建筑空间和形态中,做到与酒店主题的有机契合。     

人因视角融入的景观认知研究进展及展望

人的景观认知对于城市绿色空间优化具有重要价值,然而目前此类研究仍由主观认知经验主导,缺少客观测度方法支撑。引入人因工程学视角,界定人因耦合系统下的景观认知对象,总结人因场景构建及测度技术方法,梳理人因耦合的景观认知相关研究,归纳出三大类研究内容：1）景观认知产生机制;2）景观认知主体评价;3）景观认知行为效应。从城市-社区-场地三重维度解析人因视角融合下的景观认知研究发展趋势,阐明开展此类研究的重要价值。     

基于自注意力的隧道视频火灾识别技术研究

针对公路隧道火灾样本量少、深度学习效果不理想的问题，研究一种小样本学习技术，以提高对隧道火灾样本的利用率，并在此基础上利用成熟的机器学习方法，提出一种基于自注意力的隧道视频火灾识别技术。该技术采用自注意力机制结合SVM分类器搭建火焰识别模型，该模型针对各项特征对火焰识别的重要性分配不同的注意力权重，形成注意力矩阵，并将权重矩阵与特征向量的值相加权，通过SVM的Hinge Loss进行线性支持向量机分类，对公路隧道火灾进行识别和预警。在火灾识别训练过程中，通过对火焰疑似区域进行检测，并利用数据增强技术达到样本扩增的目的，随后采用多通道融合的特征提取方式构建特征向量，输入设计的自注意力火焰识别模型中，通过梯度下降优化器进行小批量模型训练，降低迭代次数，最终获得最优特征权重参数，得到最佳识别模型。试验结果表明，该方法在模型训练时收敛较快，在火焰识别时相比未使用小样本学习的传统SVM算法，准确率提高了5%，因此能在小样本环境下有效提高火灾识别的准确度。     

Cognition and Design of Complex Landscapes: The Function,Logic, and Mechanism of Mapping

Being rich in form and obscure in content, mapping brings not only new opportunities, but also confusion and doubts to the research and practice of contemporary complex landscapes. Therefore, deep exploration of mapping’s function, logic, and mechanism in inspiring design is needed to help recognize the value of Mapping and promote its understanding and application. Through literature review, case studies, and the authors’ practice and teaching, this article attempts to answer three questions: Which function does Mapping emphasize, representation or exploration? What is the logic of mapping in arranging information? And what is the mechanism of mapping in inspiring design? The main conclusions of this article include: 1) Rather than viewer-oriented representation, mapping more often serves the cartographers themselves in their exploration activities, in which they develop new understandings and create new possibilities while constructing the complex relationship of existing information; 2) Despite the various forms, media, and methods, mapping’s logical structures in organizing information would converge into five types: sequence, matrix, parallel, network, and deconstruction reflecting to various degrees the logic of complex landscapes themselves; And 3) through collecting and connecting information and ideas with certain logical frameworks, mapping helps with bottom-up generation of cognition and design of the site, which provides a visual operation carrier that reflects the site’s structures and evolutionary processes. Applying mapping in teaching and practice can promote designers’ cognition on structures and processes of complex landscapes and get rid of the dogma of following standardized workflows or imposed cultural symbols.     

Application of Intelligent-Interaction-Based La ndscape Experience Augmentation

Since the mid- to late 1990s, both Artificial Intelligence and wearable interaction techniques have dramatically changed the way how humans interact with the exterior environment, as such influence will be greater and greater over time. Wearable devices and mobile terminals have enhanced humans’ experience on spatial environment by improving their perception, understanding, and ability of control towards certain places. This paper centers on the advanced efforts of the augmentation technologies in intelligent sensing, cognition, and feedback, by introducing several innovative applications, including 1) the live-audio augmented project for the Washington Monument; 2) the CityScope project, developed by the MIT City Science Lab, which provides intelligent decision-making aid for non-professional users; and 3) Nature-X, an augmented reality application that creates nature community scenes based on Location Based Service. All these studied cases of spatial and environmental planning and design look into the future opportunities and challenges in the context of intelligent interaction.     

Effects of Pictures With Waterscapes of Varied Visual Perception of Naturalness on Individual Cognition

Natural environments can provide individual cognitive benefits, and naturalness is often regarded as a valued property of environment. This research focuses on the visual perception of naturalness and investigates the impact of waterscapes of varied naturalness levels on people’s cognition, by proposing and verifying two hypotheses: 1) subjective restoration varies across waterscapes of varied naturalness levels; and 2) waterscapes of varied naturalness levels affect people’s working memory accordingly. Through a between-subjects experiment, participants in this research were randomized into three experiment groups (waterscapes of high, medium, and low naturalness level) and the control group, and the Perceived Restorative Scale and the Restoration Outcome Scale are introduced to measure the subjective restoration of the environment. The running memory accuracy, shifting cost, and Stroop task indicators are used to measure an individual’s working memory. According to the characteristics of waterscapes of varied naturalness levels summarized upon the research and the findings on the corresponding cognitive benefits, suggestions are concluded for optimizing resource allocation and investments in landscape design practice, as well as guiding visitors’ usage of waterscapes: 1) waterscapes are recommended in spatial creation for their productive cognitive benefits, if financial and ecological conditions permit; 2) in terms of cognitive benefits, waterscapes of high naturalness level are conducive to high subjective restoration and enhanced inhibition function of central executive system; 3) waterscapes of medium naturalness level can lead to a relatively high subjective restoration and improved updating function of central executive system; and 4) waterscapes of low naturalness level can bring about a better attention restoration and better performance on shifting function of central executive system.     

基于支持向量机的砂土液化预测模型

分析了砂土液化的主要影响因素,建立了砂土液化的支持向量机预测模型。该模型能通过有限经验数据的学习,建立砂土液化类型与其影响因素之间的非线性关系。运用所建立的模型对具体的砂土液化类型进行了评判,评判结果表明,基于线性核的支持向量机分类器不能有效地建立液化类型与影响因素之间的非线性映射,而基于多项式核及径向基核函数的分类器能正确判定砂土是否液化。     

SVM的信息粒化时序回归预测城市用水量

利用基于信息粒化的支持向量机预测模型对某市11个月的时用水量数据进行模拟训练,对下一个月的每日最高时用水量进行预测.首先提取每日的最高时用水量,再将每7个数据变换为一个三角型模糊粒子,该模糊粒子中的三个参数Low、R和Up分别代表一周内最高时用水量变化的最小值、平均值和最大值,然后利用SVM对最高时用水量及Low、R和Up进行预测.针对SVM在预测时调整自身相关参数困难的问题,提出了运用网格法对模型中的参数进行优化选择.实例分析结果表明,该模型建模速度快,预测精度高,且实用性强.     

Automating the interpretation of PM2.5 time-resolved measurements using a data-driven approach

The rapid development of automated measurement equipment enables researchers to collect greater quantities of time-resolved data from indoor and outdoor environments. While significant, the interpretation of the resulting data can be a time-consuming effort. This paper introduces an automated process of interpreting PM_2.5 time-resolved data and differentiating PM_2.5 emissions resulting from indoor and outdoor sources. We use Random Forest (RF), a machine learning approach, to study a dataset of 836 indoor emission events that occurred over a 2-week period in 18 apartments in California. In this paper, we show model development and evaluate its performance as the sample size and source vary. We discuss the characteristics of the dataset that tended to help the source identification and why. For example, we show that data from many events and from different apartments are essential for the model to be suitable for analyzing a new separate dataset. We also show that longitudinal data appear to be more helpful than the time frequency of measurements within a given apartment. We use the resulting RF model to analyze PM_2.5 data of an entirely separate dataset collected from 65 new homes in California. The RF model identifies 442 indoor emission events, with only a few misidentifications.