The rapid expansion of cities brings in new challenges for the urban firefighting security, while the increasing fire frequency poses serious threats to the life, property, and safety of individuals living in cities. Firefighting in cities is a challenging task, and the optimal spatial arrangement of fire stations is critical to firefighting security. However, existing researches lack any consideration of the negative effects of the spatial randomness of fire outbreaks and delayed response time due to traffic jams upon the site selection. Based on the set cover location model integrated with the spatiotemporal big data, this paper combines the fire outbreak point with the traffic situation. The presented site selection strategy manages to ensure the arrival of the firefighting task force at random simulated fire outbreak points within the required time, under the constraints of the actual city planning and traffic situation. Taking Nanjing city as an example, this paper collects multi-source big data for the comprehensive analysis, including the full data of the fire outbreak history from June 2014 to June 2018, the traffic jam data based on the Amap, and the investigation data of the firefighting facilities in Nanjing. The regularity behind fire outbreaks is analyzed, the factors related to fire risks are identified, and the risk score is calculated. The previous fire outbreak points are put through the clustering analysis, the spatial distribution probability at points in each cluster is calculated according to the clustering score, and the random fire outbreak points are generated via the Monte Carlo simulation. Meanwhile, the objective emergency response time is set as five minutes. The average vehicle speed for each road in the urban area is calculated, and the actual traffic network model is built to compute the travel time from massive randomly-distributed simulated fire points. The problem is solved by making the travel time for all simulated demand points below five minutes. At last, the site selection result based on our model is adjusted and validated, according to the planned land use. The presented method incorporates the view of the spatiotemporal big data and provides a new idea and technical method for the modification and efficiency improvement of the fire station site selection model, contributing to a service cover ratio increase from 58% to 90%.

当代风景园林研究密切关注共性心理与景观环境的交互关系,景观关注度成为景观心理描述与环境绩效的重要评价指标。基于风景园林"环境-心理"耦合机制与脑电信号采集技术（EEG）研究进展,结合景观关注度研究相关成果,基于主成分分析法建立了一种景观关注度脑电数据回归模型。以玄武湖公园为例,通过主成分分析法对原始景观因子进行整合筛选,建立变量观测体系并对其景观心理评价要素进行脑电分析,通过算法设定与数据分析获取景观关注度主成分及其量化耦合关系。研究结果表明,玄武湖公园景观色彩丰富度、空间集成度、水体形态变化度3项评价指标对景观关注度起主要作用,景观关注度与景观因子种类呈正相关关系。研究结果为景观心理量化描述与算法分析提供了一种基于脑电数据的景观关注度分析技术,为相关研究纵深开展提供技术支持。

Rapid economic and social development has been accompanied by the occurrence of many major issues throughout the world. Specifically, there is an ever-increasing demand for emergent medical services among the public. In order to ensure timely responses to emergency demands, it is critical to reasonably configure the emergency stations. In general, emergency stations are mostly distributed according to the distribution of emergency demands and response time, which, however, fails to consider the negative impacts of randomly occurring emergency demands and traffic delays. In this study, first aid demands are combined with traffic states based on the spatiotemporal big data set covering model, which alleviates the negative impacts of randomly occurring first aid demands and traffic delay time on the planning of pre-hospital first aid stations. Moreover, the accuracy of the site selection model is improved, which meets the requirements that all randomly occurring simulated first aid demands can be approached within the target time under planning conditions and actual traffic constraints. Taking Nanjing City as an example, this study obtains multi-source big data, such as ambulance-carried GPS data from June 2018 to June 2019, Gaode Map-recorded traffic congestion data, and survey data of emergency rescue facilities. Basing on the processing and analysis of these data, it shows that first aid demands in Nanjing City are highly region-specific with high time delay. Various required factors are determined based on modeling and analysis, and the target time is agreed to be 8 min. The average vehicle speed on each road is calculated, accompanied by the establishment of an actual road network model. In this context, the transit time from the randomly distributed first aid stations to the hospital can be calculated, which are set to satisfy the model conditions so as to obtain the solution. Finally, such a solution is adjusted and verified according to the land-use situation. The results of this study, based on spatiotemporal big data, are expected to provide insights into improving the site selection model and enhancing efficiency while providing new technical methods.

Facing the existing digital image libraries on landscape, researchers need to urgently solve a challenging problem: how to realize rational management and accurate retrieval of landscape images that contain feature information like hierarchy, layout, color system, and color matching. For accurate organization and labeling of landscape Images, this paper presents a novel method for feature extraction and image retrieval of landscape images based on image processing. Firstly, a color quantization process was designed for landscape images, and used to analyze the color composition and color space pattern (CSP) of such images. Next, the existing methods, which are suitable for the extraction of color features from landscape Images, were briefly reviewed, and the basic flows of our improved algorithm and division method of landscape color blocks (LCBs) were explained. Finally, the retrieval performance of landscape images was improved by matching of weighted color blocks of regional landscape, based on the multi-dimensional color eigenvectors of landscape image. The experimental results demonstrate the effectiveness of our algorithm. The research results shed light on the feature extraction from other types of color images.

With the boom of digital landscape architecture, the evaluation of landscape efficacy has evolved from pictorial description to model analysis. Many scholars have explored the mathematical model behind traditional geometric laws. Structural equation modelling (SEM) provides a scientific measurement tool for landscape performance, thanks to its simple path, simultaneous equations, and in-depth variable measurement. Inspired by the theories of the SEM, this paper establishes a theoretical model for landscape efficacy based on five unobservable factors, namely, spatial density, vegetation coverage, recreational travel, scenic integration, and topological depth. Next, typical new Chinese style (NCS) commercial streets were selected as samples, and the initial data on the five factors were extracted and normalized by depthmapX, Grasshopper, and SPSS. With the aid of SPSS Amos, the path between each unobserved element and landscape efficacy was simulated, quantified, and fitted by our model. The fitting results were verified and analysed through multiple regression. A total of 200 typical NCS commercial streets were selected as samples to verify the established model. The results show that topological depth (path coefficient: 0.98) has the greatest impact on landscape efficacy, followed in turn by spatial density (0.86), vegetation coverage (0.65), scenic integration (0.59), and recreational travel (0.50). The empirical analysis proves that the SEM can effectively evaluate the landscape efficacy of the NCS commercial streets. The research results provide a good reference for the quantification of the coupling relationship between unobserved factors in built environment. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University.

基于低影响开发（LID）理念,采用建成环境径流系统科学组织与技术集成的研究视角,认为建筑表面与景观场地共同构成了建成环境地表系统,统筹建筑顶面、侧立面及景观下垫面的一体化径流系统设计是当代科创园区更新改造的重要内容,并对改善局部地段生态环境、集约利用水资源等方面具有重要意义。以中小型科创园区为研究对象,提出了全地表生态径流理念下"建筑-环境"协同改造的设计观念;以苏州金枫产业园改造设计为例,进行了包含建筑改造和园区景观更新的一体化地表生态径流协同设计。总结了地表生态径流设计方法在科创园区建筑及其景观设计中的应用策略与设计要点,探讨了后续研究的思路与方向,为充实当代低影响开发设计方法与技术模式提供相关依据与研究结论。

Considering that the standard genetic algorithm in the analysis of the quantization of landscape space still has some problems such as low precision and large error, a new Chinese style landscape space cognitive model based on operator optimization genetic algorithm is proposed in this paper. Based on the analysis of the cognitive characteristics involved in the new Chinese style landscape design, the model of landscape space features and landscape space cognitive elements is established. With the cognitive behavior as the standard, through feature matching, landscape space cognition is analyzed from similarity and cognition in detail. On this basis, combined with operator optimization genetic algorithm, a new Chinese style landscape space cognitive model is successfully constructed, and operator optimization heredity grade is used to determine the structure and the adjacent matrix of the genetic algorithm of the algorithm to get the landscape space cognition accurately, then provide the guidance for the new Chinese type landscape space design. At the end of this paper, the practicability and validity of the model is verified by examples.

In order to improve the spatial planning ability of island port landscape pattern, an image planning and design method based on block matching space reconstruction for island port landscape pattern spatial structure is proposed. Firstly, the information transmission model of the spatial structure image of the island port landscape pattern is constructed, and the sub-spatial structure block matching and the priority determination of the spatial planning of the island port landscape pattern are carried out. Then the multi-layer wavelet feature decomposition method is used to decompose and fuse the spatial distribution images of the island port landscape pattern, and the block matching space area reconstruction is carried out to realize the optimization planning and design of the island port landscape pattern spatial structure. The simulation results show that the restoration performance of the reconstruction modeling of the spatial structure image of the island port landscape pattern is better, the spatial integration degree of the island port landscape pattern is higher, and the peak signal-to-noise ratio is high. The rationality of the spatial planning and design of the island port landscape pattern has been improved, and it is more reasonable in the spatial planning and spatial structure optimization application of the island port landscape pattern.