刊首語

時空大數據(spatiotemporal big data)、大數據平臺(big data platform)、大數據分析(big data analysis)和大數據應用(big data application)是近年來引起各行各業普遍關注的重要領域，相關的研究成果涉及時空大數據內涵解析與發展機遇、大數據平臺構建與數據管理、大數據分析技術與數據挖掘、大數據應用探索與決策支持等多個方面。

在城鄉景觀規劃設計研究領域，時空大數據的應用也逐步受到重視，相關探索性研究既涉及大數據在城鄉規劃設計領域應用的技術與方法，也涉及大數據時代風景園林的發展和教育；研究范圍既有大中尺度的風景名勝區及新型城鎮化背景下的城市園林規劃設計，也有關注使用者活動方式的中小尺度的城市綠地系統規劃設計；特別是在將多種類型的時空大數據應用于景觀規劃設計的具體案例中，手機信令數據的應用、衛星定位導航(GNSS)數據的應用、社交網絡(SNS)大數據的應用、具有地理位置的景觀照片(geo-tagged photo)分析，以及基于社會感知大數據的人群行為模式(behavioral mode)分析等，均表現出全方位的時空大數據輔助景觀規劃設計的態勢。

時空大數據的出現為景觀規劃設計帶來了新的機遇和挑戰。機遇體現在時空大數據為我們開展景觀規劃設計提供了全面、系統、定量地分析與認識場地的機會，特別是認識人與場地的關系，因為時空大數據類型多樣、內容豐富、特征鮮明，與城鄉景觀規劃設計相關的時空大數據包括2個大類(靜態數據與動態數據)、12個中類(基礎空間數據、場地資源數據、場地設施數據、社會經濟數據、環境效益數據、人流統計數據、動態監測數據、定位通信數據、網絡媒體數據、社交網絡數據、刷卡消費數據、活動行為數據)、30多個小類；不僅如此，時空大數據具有6個方面的顯著特性，即客觀性、多源性、動態性、精細性、現勢性和人本性，這使得數字景觀規劃設計迎來新的發展契機。于是，業內不少學者開展了基于時空大數據的景觀規劃設計探討，涵蓋了基于移動通信大數據的城市公園游客構成及活動分析與規劃設計研究、基于定位導航大數據的歷史文化景區游客空間行為模式分析與規劃設計研究、基于社交網絡大數據的城市綠地系統分析與公園綠地規劃設計研究、基于環境感知大數據的城市生態系統變遷分析與規劃管理研究、基于數值模擬大數據的居住小區建筑布局與環境規劃設計研究，以及基于地理標記景觀照片大數據的街道尺度景觀規劃設計等。

在看到探索研究成果的同時，也要關注到景觀規劃設計領域時空大數據應用面臨的挑戰，主要體現在2個方面，其一是大數據的獲取途徑還比較有限，很多的景觀時空大數據存儲在事業或者企業服務器中，對于廣大景觀規劃設計從業者來說，并沒有真正的時空大數據可以隨時應用；其二是大數據的處理能力還比較有限，多數景觀規劃從業人員對于大數據分析和應用的技能還沒有達到預期水準，所以也無法在自己承擔的景觀規劃設計研究中嘗試應用大數據。然而，面向未來，上述挑戰將逐步予以解決，因為國家已經出臺了《促進大數據發展行動綱要》，城鄉景觀規劃設計領域已經呈現出以下5個方面的時空大數據應用發展趨勢：其一是大數據應用的生態環境逐步構建，其二是大數據應用的技術體系逐步形成，其三是大數據應用的人才力量逐步壯大，其四是大數據應用的多源集成創新發展，其五是大數據應用的人本主義特色體現?；跁r空大數據的景觀規劃設計必將體現人本主義特色，通過大數據輔助分析人的自然、社會、文化、情感等多維特性，然后通過規劃設計的手法，在空間、時間、設施、環境等多個維度滿足人的需求特性。

最后，感謝清華大學黨安榮教授對本期主題文章的貢獻。

Spatiotemporal big data, big data platform, big data analysis and big data application are important areas of interest that have drawn the attention of a wide range of industries in recent years. Relevant research results include many aspects such as the big data connotation analysis and development opportunity, the construction and data management of big data platform, big data analysis technology and data mining, big data application exploration and decision support.

In the field of urban and rural landscape planning and design, the application of spatiotemporal big data has also been gradually taken seriously. Relevant exploratory research involves both technologies and methods big data applied in urban and rural planning and design as well as the development and education of landscape architecture in the era of big data. The research range includes both large and medium-sized scenic areas and urban landscape planning and design under new urbanization, as well as small and medium sized urban green space system planning and design that focuses on user activities. Particularly in the cases of the application of multiple types of spatiotemporal big data to the landscape planning and design, the application of handset signaling data,GNSS data, SNS big data, geo-tagged photo analysis, and behavioral mode analysis based on social perception big data, show the situation of the full range spatiotemporal big data aiding landscape planning and design.

The advent of spatiotemporal big data brings new opportunities and challenges to landscape planning and design. The opportunities are reflected in the spatiotemporal big data providing a comprehensive, systematic and quantitative analysis and understanding of venues for our landscape planning and design, especially in understanding the relationship between people and venues, because the spatiotemporal big data are of diverse types,rich contents, and distinctive features, The spatiotemporal big data related to urban and rural landscape planning and design include two large categories (static data and dynamic data), 12 medium categories (basic spatial data, site resource data, site facilities data, socio-economic data, environmental benefits data, people flow statistics, dynamic monitoring data, positioning communication data, network media data, social network data, credit card spending data, and activity data), and over 30 sub-categories; not only that, the spatiotemporal big data has six aspects of significant features, such as being objective, multi-source, dynamic, potential, sophisticated and human-oriented, bringing digital landscape planning and design a new development opportunity. Thus, we see that many scholars in the industry have carried out the discussion on the landscape planning and design based on the spatiotemporal big data, covering the areas of the composition and activity analysis and planning and design of tourists in urban parks based on the big data of mobile communication, the spatial behavior pattern analysis and planning and design research of tourists in historical and cultural scenic areas based on the big data of positioning and navigation, the urban green space system analysis and park green space planning and design research based on the social network big data, the urban ecosystem change analysis and planning management research based on the environmental perception big data, the residential building layout and environmental planning and design research based on the numerical simulation big data, as well as the street scale landscape planning and design based on the geo-tagging landscape photo big data.

While seeing the achievements of exploration and research, we should also pay attention to the challenges faced in the application of spatiotemporal big data in the field of landscape planning and design, mainly in two aspects. One is that the access to big data is still relatively limited, and a lot of landscape spatiotemporal big data are stored in institutional or enterprise servers, and for the majority of landscape design and planning practitioners, no real spatiotemporal big data can be readily applied; the second is the processing power of big data is still relatively limited, and most landscape planning practitioners' skills of big data analysis and application have not yet reached the expected level, analysis, so they cannot try to apply big data in their own landscape planning and design studies. However, facing the future, the above-mentioned challenges will be gradually solved, since the state has promulgated the Action Plan for Promoting Big Data Development, and the urban and rural landscape planning and design field has shown the following five trends in the application of spatiotemporal big data: 1) the eco-environment of big data application gradually building up, 2) the technology system of big data application gradually taking shape, 3) the talent strength of big data application gradually expanding, 4) the multi-source integration of big data application innovatively developing, and 5) the human-oriented characteristics of big data application showing up. The landscape planning and design based on spatiotemporal big data is bound to embody the human-oriented characteristics, help to analyze people’s natural, social, cultural and emotional multidimensional features through big data, and then use planning and design techniques in space, time, facilities, environment, and multiple dimensions to meet the people's needs.

Last but not the least, we are grateful to Professor Dang Anrong of Tsinghua University for his contributions to the thematic papers in this issue.