基于珞珈一号的岳麓区第二、三产业GDP公里网格空间化研究

现代化城市中,夜间活动一般需要黑暗环境中灯光照明的支持,从而使夜间灯光可以间接反映城市中的各类生产生活的活跃情况,而利用遥感手段从高空获得的夜间灯光遥感数据可以大面积地折射城市中的社会经济情况。对于研究城市中主要以非第一产业的GDP指标的二、三产业分布研究具有一定的参考价值。同时考虑到第二、三产业活动的特殊性,通过FROM-GLC10的土地利用数据可以过滤与第二、三产业无关的土地覆盖信息,从而为研究城市第二、三产业GDP分布提供更加合理的分析支持。本文通过对岳麓区不透水面的夜间灯光指数研究,完成对岳麓区第二、三产业GDP的公里格网化,实现更高精度的GDP格网化。     

经济空间场与ESDA结合的公共卫生事件应急策略制定

新型冠状病毒肺炎疫情引起了人们对国家公共卫生事件应对能力的广泛关注。基于波及效应梯度场提出了生产诱发梯度,进一步完善了经济空间场理论,并将其与探索性空间数据分析(exploratory spatial data analysis,ESDA)相结合,对医药制造业波及效应及空间布局进行了研究,制定了有效的公共卫生事件应急策略。经济空间场理论分析结果揭示了产业经济空间中医药制造业与各产业部门之间的波及效应,并由此得到了医药密切相关产业。同时,经济空间场理论与ESDA方法的结合能在区分中国大陆各省空间聚集类型的基础上,评估各省公共卫生事件的应对能力,从而为各省提出相应的应急策略和医药制造业发展建议。该方法综合考虑了产业波及效应和产业空间布局现状,不仅能够促进各省医药制造业的健康合理发展,也有助于增强各省突发公共卫生事件的应对能力。     

GIS在现代城市物流配送中的应用

物流作为第三利润的源泉,如今越来越受到各个行业的重视。针对我国物流行业的现状和发展趋势,以ArcGIS软件如何实现物流中心选址和配送最短路径的选择为例,展现了GIS技术在现代城市物流配送中的应用,展望了GIS在该领域广阔的应用前景。     

Conditional versus unconditional industrial agglomeration: disentangling spatial dependence and spatial heterogeneity in the analysis of ICT firms’ distribution in Milan

A series of recent papers have introduced some explorative methods based on Ripley’s K-function (Ripley in J R Stat Soc B 39(2):172–212, 1977) analyzing the micro-geographical patterns of firms. Often the spatial heterogeneity of an area is handled by referring to a case–control design, in which spatial clusters occur as over-concentrations of firms belonging to a specific industry as opposed to the distribution of firms in the whole economy. Therefore, positive, or negative, spatial dependence between firms occurs when a specific sector of industry is seen to present a more aggregated pattern (or more dispersed) than is common in the economy as a whole. This approach has led to the development of relative measures of spatial concentration which, as a consequence, are not straightforwardly comparable across different economies. In this article, we explore a parametric approach based on the inhomogeneous K-function (Baddeley et al. in Statistica Nederlandica 54(3):329–350, 2000) that makes it possible to obtain an absolute measure of the industrial agglomeration that is also able to capture spatial heterogeneity. We provide an empirical application of the approach taken with regard to the spatial distribution of high-tech industries in Milan (Italy) in 2001.     

基于遗传算法的商业区位选址研究

分析了购物商场选址要求的目标约束性条件,采用了GIS空间分析功能,实现了遗传算法确定符合条件的地理范围。     

地理信息产业市场规范化政策初探

首先讨论了地理信息产业市场构成、业务活动和市场链的特点,在借鉴国外地理信息产业和国内有关产业市场管理经验的基础上,分析了目前我国地理信息产业市场准入、市场监管及行业自律等方面的现状,对进一步加强我国地理信息产业市场规范化管理提出了几点政策建议。     

Discovering Spatial Patterns in Origin‐Destination Mobility Data

Mobility and spatial interaction data have become increasingly available due to the wide adoption of location‐aware technologies. Examples of mobility data include human daily activities, vehicle trajectories, and animal movements, among others. In this article we focus on a special type of mobility data, i.e. origin‐destination pairs, and present a new approach to the discovery and understanding of spatio‐temporal patterns in the movements. Specifically, to extract information from complex connections among a large number of point locations, the approach involves two steps: (1) spatial clustering of massive GPS points to recognize potentially meaningful places; and (2) extraction and mapping of the flow measures of clusters to understand the spatial distribution and temporal trends of movements. We present a case study with a large dataset of taxi trajectories in Shenzhen, China to demonstrate and evaluate the methodology. The contribution of the research is two‐fold. First, it presents a new methodology for detecting location patterns and spatial structures embedded in origin‐destination movements. Second, the approach is scalable to large data sets and can summarize massive data to facilitate pattern extraction and understanding.     

Extracting urban functional regions from points of interest and human activities on location‐based social networks

Data about points of interest (POI) have been widely used in studying urban land use types and for sensing human behavior. However, it is difficult to quantify the correct mix or the spatial relations among different POI types indicative of specific urban functions. In this research, we develop a statistical framework to help discover semantically meaningful topics and functional regions based on the co‐occurrence patterns of POI types. The framework applies the latent Dirichlet allocation (LDA) topic modeling technique and incorporates user check‐in activities on location‐based social networks. Using a large corpus of about 100,000 Foursquare venues and user check‐in behavior in the 10 most populated urban areas of the US, we demonstrate the effectiveness of our proposed methodology by identifying distinctive types of latent topics and, further, by extracting urban functional regions using K‐means clustering and Delaunay triangulation spatial constraints clustering. We show that a region can support multiple functions but with different probabilities, while the same type of functional region can span multiple geographically non‐adjacent locations. Since each region can be modeled as a vector consisting of multinomial topic distributions, similar regions with regard to their thematic topic signatures can be identified. Compared with remote sensing images which mainly uncover the physical landscape of urban environments, our popularity‐based POI topic modeling approach can be seen as a complementary social sensing view on urban space based on human activities.     

ESRI地理空间数据与AutoCAD数据的交互共享

近年来,GIS发展迅猛,并呈向其他相关行业渗透、延伸趋势。地理空间数据的跨行业交互共享成为一种新的行业需求。以应用广泛的AutoCAD、Shape数据为例,对2种数据的差异和联系进行了详细分析,深入探讨了二者交互共享的必要性和可能性,归纳总结了实现其共享的方式和建议。力求探索一条基于ESRI空间数据和AutoCAD数据...     

东北地区空气质量时空模式的可视化制图表达

我国的工业化发展严重依赖于煤炭、钢铁、电力、交通等传统污染性产业,这类产业高能耗、高污染的特性造成了严重的环境污染问题。东北地区是我国重要的重化工产业基地及主要粮食产业产区,其生态环境,特别是空气质量备受关注。本文利用点格图对2015年中国东北地区的空气质量时空分布情况进行了可视化表达。在利用日历视图可视化表达空气质量指数级别及首要污染物信息的基础上,还加入了地理参考信息。空气质量点格图为理解和分析东北地区的空气质量现状及其时空分布模式提供了面向大众的、直观有效的方法。利用该方法对空气质量进行分析,有助于辨别空气污染的主要问题、提高公众的环境保护意识,以及制定切实有效的遏制空气污染的政策法规。     

智能时代测绘与位置服务领域的挑战与机遇

由人工智能引发的智能革命星火,正向各行各业蔓延,测绘与时空位置服务的相关方法、技术、产业形态和商业模式所面临的挑战与机遇,是值得深入思考的问题。从人工智能的内涵、历程和趋势出发,阐述了对新一代人工智能特征的理解,并对智能时代来临所带来的机遇和挑战进行了分析。聚焦到测绘与位置服务领域,认为其作为行业,不会消失但必须转型,并分析了转型的可能路径;作为学科,不会扩张但须跨界、交叉和融合;作为职业,将会出现蓝领消失,创客、智士领军的局面。测绘与位置服务行业需要充分挖掘自身优势,将系统性思维、时空观思维和创意性思维作为开启智能时代大门的钥匙,才能实现测绘与位置服务行业向绿色、智能、泛在发展的整体转型。     

利用时序手机通话数据识别城市用地功能

城市土地利用是人的活动与城市物质空间交互所表现出的综合结果,因此人的活动与城市土地利用功能密切相关;具有不同时间段人的活动的空间聚集与分散规律的区域,其所属的社会功能属性亦不相同。随着大数据时代的到来,以居民手机数据为代表的基于位置的服务数据（local basic service,LBS）大量出现,使得实现时空全覆盖和精细化地监测城市人的活动成为可能。因此,利用手机数据的优势,能够实现从人的角度来区分识别城市用地功能类型。利用手机通话详单数据（call detail records,CDRs）提取面向地块尺度的居民通话聚合时序特征,提出了一种城市土地利用类型谱聚类识别方法。以武汉市为例进行实验分析,结果表明,该方法识别城市土地利用的平均精度为54.6%,为探知城市土地利用空间分布提供了一个有效的方法。     

基于北斗室内外无缝位置服务方案设计

随着北斗卫星导航系统组网的日益完善,基于北斗的位置服务相关产业也在飞速发展。互联网技术的不断成熟,也加速了互联网产业与位置服务产业的结合。本文以我国北斗卫星导航系统为支撑,提出集成北斗卫星导航系统、蓝牙/Wi-Fi技术的室内外无缝定位技术和位置服务技术的方法,为城市室内外无缝定位提供新的思路。     

Negotiating on location, timing, duration, and participant in agent-mediated joint activity-travel scheduling

Agent-based simulation has become an important modeling approach in activity-travel analysis. Social activities account for a large amount of travel and have an important effect on activity-travel scheduling. Participants in joint activities usually have various options regarding location, participants, and timing and take different approaches to make their decisions. In this context, joint activity participation requires negotiation among agents involved, so that conflicts among the agents can be addressed. Existing mechanisms do not fully provide a solution when utility functions of agents are nonlinear and non-monotonic. Considering activity-travel scheduling in time and space as an application, we propose a novel negotiation approach, which takes into account these properties, such as continuous and discrete issues, and nonlinear and non-monotonic utility functions, by defining a concession strategy and a search mechanism. The results of experiments show that agents having these properties can negotiate efficiently. Furthermore, the negotiation procedure affects individuals’ choices of location, timing, duration, and participants.     

Regional positioning services as economic and construction activity indicators: the case study of Andalusian Positioning Network (Southern Spain)

The Andalusian Positioning Network (RAP) is a regional GNSS permanent network in Southern Spain that offers two public services for precise positioning: real-time (RAP-Internet Protocol [IP]) and post processing (RAP-File Transfer Protocol [FTP]). Most of the registered users are linked to the construction sector, so the collapse of the housing bubble and the Spanish economic crisis influenced the use of RAP services from 2008. The behaviour of these services has differed somewhat, although analysis for the years 2008–2013 reveals a general decline. Since 2009, the RAP-FTP service demand fell by 50%, but the RAP-IP service was stable until October 2011, when it began a steep decline in December 2012. Analysing the temporal demand and the geospatial connections of RAP-IP with economic impact indicators, we found a high linear correlation between this service and jobs in the construction sector (.98) and permit building (.96). The real-time and associated geoinformation are its main advantages.     

Visualizing spatiotemporal trajectories of mobile social media users using space–time cube

The implementation of social network applications on mobile platforms has significantly elevated the activity of mobile social networking. Mobile social networking offers a channel for recording an individual’s spatiotemporal behaviors when location-detecting capabilities of devices are enabled. It also facilitates the study of time geography on an individual level, which has previously suffered from a scarcity of georeferenced movement data. In this paper, we report on the use of georeferenced tweets to display and analyze the spatiotemporal patterns of daily user trajectories. For georeferenced tweets having both location information in longitude and latitude values and recorded creation time, we apply a space–time cube approach for visualization. Compared to the traditional methodologies for time geography studies such as the travel diary-based approach, the analytics using social media data present challenges broadly associated with those of Big Data, including the characteristics of high velocity, large volume, and heterogeneity. For this study, a batch processing system has been developed for extracting spatiotemporal information from each tweet and then creating trajectories of each individual mobile Twitter user. Using social media data in time geographic research has the benefits of study area flexibility, continuous observation and non-involvement with contributors. For example, during every 30-minute cycle, we collected tweets created by about 50,000 Twitter users living in a geographic region covering New York City to Washington, DC. Each tweet can indicate the exact location of its creator when the tweet was posted. Thus, the linked tweets show a Twitter users’ movement trajectory in space and time. This study explores using data intensive computing for processing Twitter data to generate spatiotemporal information that can recreate the space–time trajectories of their creators.     

雪地上的森林冠层混合反照率模型

反照率通常定义为出射与入射的能量之比，是地表能量平衡中的关键因子。气候变化对反照率也很敏感。典型的气候变化预测是通过GCM与地表模型的结合进行的。目前在地表模型(如BATS模型)中，是通过空气动力学粗糙度Z0与降雪深度d两个参数来估计雪地上树冠的反照率的。在他们的工作基础上，重点考虑对于不同的太阳天顶角，直入一扇出反照率的方向性及其与叶面积指数(LAI)的关系。同时，为了保持BATS模型所需反照率模型的基本特征，主要在几何光学-辐射传输混合模型(GORT)的基础上做了一些近似来达到此目的。最后，以针叶林为例，用MODIS的反照率数据和BOREAS地面观测数据做了初步的模型验证。结果显示模型较符合实际情况。     

A test for the coincident economic and spatial clustering of business enterprises

This paper uses input-output data combined with point process modeling techniques to test whether enterprises linked within nominal buyer-supplier chains have a greater propensity to cluster in space than manufacturing enterprises in general. The methodology controls for the general tendency of firms to seek locations in concentrated agglomerations and isolates the influence of firm interdependence on spatial clustering. Our findings suggest that there is indeed an association between economic linkages and geographic clustering in our study area, but only for some types of economic clusters, mainly those that are comprised mainly of more knowledge-based or technology-intensive sectors. In general, we endeavor to show that spatial analytical methods hold considerable promise for conducting rigorous tests of industrial location questions. Received: 9 September 1998 / Accepted: 12 December 1999     

基础地理数据更新生产模式探讨

随着现代化建设的快速发展,地理信息产业得到了蓬勃发展。当前GIS的核心已从单纯的数据生产转为面向更新的数据生产。本文对当前基础地理数据更新生产的模式和技术方法的发展趋势进行分析,并结合基础地理数据更新生产的特点,从应用角度对更新生产中的方案制作和数据转换技术进行探讨。     

Methods for matching English language addresses

Addresses occupy a niche location within the landscape of textual data, due to the positional importance carried by every word, and the geographic scope it refers to. The task of matching addresses happens every day and is present in various fields such as mail redirection, entity resolution, etc. Our work defines, and formalizes a framework to generate matching and mismatching pairs of addresses in the English language, and use it to evaluate various methods to automatically perform address matching. These methods vary widely from distance-based approaches to deep learning models. By studying the Precision, Recall, and Accuracy metrics of these approaches, we obtain an understanding of the best suited method for this setting of the address matching task.