Geo‐Social Model: A Conceptual Framework for Real‐time Geocollaboration

Synchronous geocollaboration helps geographically dispersed people to work together in a shared geospatial environment. Its real‐time nature, multiple users' interaction and diversity of work context impose some special social, organizational and technological requirements, making the development of such real‐time geocollaboration systems a challenging task. A conceptual framework is therefore needed to specify and describe what synchronous geocollaboration is, considering its social, spatial and technical aspects. The geo‐social model presented in this article describes a conceptual framework for synchronous geocollaboration systems addressing the above aspects, identifies the core elements of the system and describes how these elements collaborate with each other. This model is presented using application‐level ontology and is then applied to a multi‐agent system based prototype in which multiple users can interact and negotiate in a shared 3D geospatial environment.     

VGDI – Advancing the Concept: Volunteered Geo‐Dynamic Information and its Benefits for Population Dynamics Modeling

The concept of Volunteered Geographic Information (VGI) has progressed from being an exotic prospect to making a profound impact on GIScience and geography in general, as initially anticipated. However, while massive and manifold data is continuously produced voluntarily and applications are built for information and knowledge extraction, the initially introduced concept of VGI lacks certain methodological perspectives in this regard which have not been fully elaborated. In this article we highlight and discuss an important gap in this concept, i.e. the lack of formal acknowledgment of temporal aspects. By coining the proposed advanced framework ‘Volunteered Geo‐Dynamic Information’ (VGDI), we attempt to lay the ground for full conceptual and applied spatio‐temporal integration. To illustrate that integrative approach of VGDI and its benefits, we describe the potential impact on the field of dynamic population distribution modeling. While traditional approaches in that domain rely on survey‐based data and statistics as well as static geographic information, the use of VGDI enables a dynamic setup. Foursquare venue and user check‐in data are presented for a test site in Lisbon, Portugal. Two core modules of spatio‐temporal population assessment are thereby addressed, namely time use profiling and target zone characterization, motivated by the potential integration in existing population dynamics frameworks such as the DynaPop model.     

Detecting Non‐personal and Spam Users on Geo‐tagged Twitter Network

With the rapid growth and popularity of mobile devices and location‐aware technologies, online social networks such as Twitter have become an important data source for scientists to conduct geo‐social network research. Non‐personal accounts, spam users and junk tweets, however, pose severe problems to the extraction of meaningful information and the validation of any research findings on tweets or twitter users. Therefore, the detection of such users is a critical and fundamental step for twitter‐related geographic research. In this study, we develop a methodological framework to: (1) extract user characteristics based on geographic, graph‐based and content‐based features of tweets; (2) construct a training dataset by manually inspecting and labeling a large sample of twitter users; and (3) derive reliable rules and knowledge for detecting non‐personal users with supervised classification methods. The extracted geographic characteristics of a user include maximum speed, mean speed, the number of different counties that the user has been to, and others. Content‐based characteristics for a user include the number of tweets per month, the percentage of tweets with URLs or Hashtags, and the percentage of tweets with emotions, detected with sentiment analysis. The extracted rules are theoretically interesting and practically useful. Specifically, the results show that geographic features, such as the average speed and frequency of county changes, can serve as important indicators of non‐personal users. For non‐spatial characteristics, the percentage of tweets with a high human factor index, the percentage of tweets with URLs, and the percentage of tweets with mentioned/replied users are the top three features in detecting non‐personal users.     

面向GIS数据共享的概念模型设计研究

Ｇ Ｉ Ｓ 数据共享的主要问题是数据的语义共享。在数据共享的保障基础———技术基础、标准化体系及政策法规体系中,标准化工作最为直接,而其中面向数据共享的概念模型的设计又是最基础性的工作之一。面向数据共享的概念模型设计的主要任务是寻求一种规范化、标准化的约束法则来保障数据的共享,为了保障数据共享的安全性,所设计的概念模型应能提供用于共享的抽象概念,这些抽象概念所描述的是地理概念而非纯空间概念,并应能提供语义抽象机制。采用语义数据模型的方法,提出利用地理特征这一概念作为建模的基本概念。通过一个实例对其应用进行了初步探讨。     

Integrating GIS‐Based Geo‐Atom Theory and Voxel Automata to Simulate the Dispersal of Airborne Pollutants

Environmental processes are usually conceptualized as complex systems whose dynamics are best understood by examining the relationships and interactions of their constituent parts. The cellular automata paradigm, as a bottom‐up modeling approach, has been widely used to study the macroscopic behavior of these complex natural processes. However, the cellular automata models are largely restricted to the two‐dimensional spatial perspective even though the process dynamics they represent evolve in the three spatial dimensions. The objective of this study is to develop a voxel‐based automata approach for modeling the propagation of airborne pollutants in three‐dimensional space over time. The GIS‐based geo‐atom theory was used to manage the data within the automaton. The simulation results indicate the model has the capability to generate effective four‐dimensional (4D) simulations from simple transition rules that describe the processes of particle advection and diffusion. The application of voxel‐based automata and the geo‐atom concepts allows for a detailed 4D analysis and tracking of the changes in the voxel space at every time‐step. The proposed modeling approach provides new means to examine the relationships between pattern and process in 4D.     

Combining Geo‐SOM and Hierarchical Clustering to Explore Geospatial Data

Geo‐SOM is a useful geovisualization technique for revealing patterns in spatial data, but is ineffective in supporting interactive exploration of patterns hidden in different Geo‐SOM sizes. Based on the divide and group principle in geovisualization, the article proposes a new methodology that combines Geo‐SOM and hierarchical clustering to tackle this problem. Geo‐SOM was used to “divide” the dataset into several homogeneous subsets; hierarchical clustering was then used to “group” neighboring homogeneous subsets for pattern exploration in different levels of granularity, thus permitting exploration of patterns at multiple scales. An artificial dataset was used for validating the method's effectiveness. As a case study, the rush hour motorcycle flow data in Taipei City, Taiwan were analyzed. Compared with the best result generated solely by Geo‐SOM, the proposed method performed better in capturing the homogeneous zones in the artificial dataset. For the case study, the proposed method discovered six clusters with unique data and spatial patterns at different levels of granularity, while the original Geo‐SOM only identified two. Among the four hierarchical clustering methods, Ward's clustering performed the best in pattern discovery. The results demonstrated the effectiveness of the approach in visually and interactively exploring data and spatial patterns in geospatial data.     

Geo‐questionnaire: A Method and Tool for Public Preference Elicitation in Land Use Planning

Geo‐questionnaire involves an integration of sketchable maps with questions, aimed at eliciting public preferences and attitudes about land allocation and services. Respondents can link their answers with corresponding locations on a map by marking points or sketching polygon features. Geo‐questionnaires have been used to learn about perceptions and preferences of city residents for specific types of land use, place‐based services, and development projects. This article reports on results of an empirical study, in which an online geo‐questionnaire was designed and implemented to elicit preferences of residents in guiding an urban development plan. Preferences collected in the form of polygon sketches were processed using GIS operations and mapped for visual interpretation. The article focuses on aggregation and analysis of respondent preferences including the analysis of positional and attribute uncertainty. Results of the study show that geo‐questionnaire is a scalable method for eliciting public preferences with a potential for meaningfully informing land use planning.     

The Scope and Conceptual Content of Analytical Cartography

Over the last three decades analytical cartography has grown from Tobler's concept of "solving cartographic problems" into a broader and deeper scientific specialization that includes the development and expansion of analytical/mathematical spatial theory and model building. In many instances Tobler himself has led the way to these new insights and developments. Fundamental concepts begin with Tobler's cartographic transformations; Nyerges' deep and surface structure and data levels; and Moellering's real and virtual maps; the sampling theorem; and concepts of spatial primitives and objects. This list can be expanded to include additional analytical concepts such as spatial frequencies, spatial surface neighborhood operators, information theory, fractals, Fourier theory, topological network theory, and analytical visualization, to name a few. This base of analytical theory can be employed to analyze and/or develop such things as spatial surfaces, terrain analysis, spatial data schemas, spatial data structures, spatial query languages, spatial overlay and partitioning, shape analysis, surface generalization, cartographic generalization, and analytical visualization. More analytical uses of theory, strategies of analysis, and implementations are being developed and continue to multiply as the field continues to grow and mature. A primary goal is to expand the mathematical/analytical theory of spatial data analysis, and theory building and analytical visualization as analytical cartography takes its place in the geographic information sciences. The research future for this area appears very bright indeed.     

类别制图及其误差建模的概念框架(英文稿)

尽管离散目标和连续场的误差建模已得到了发展, 名义场却存在实质性的和多半悬而未决的概念问题。致力于为确定信息和不确定特性整合出一个概念框架。这个概念模型是基于判别空间而构建的; 后者是由面状类别时空表象的特质或驱动过程定义的。这个模型通过加入特定类的平均结构( 其可进行基于判别变量的回归分析) 的方式, 奠定类别制图一致性的基础, 并且使基于尺度的误差建模变得更为简便易行。这种误差建模可以有效地仿效观测者在类别、边界位置、多边形个数和边界网络拓扑特性等方面的差异。通过基于模拟数据的实验, 与基于指示克里格的随机仿真结果相对比, 肯定判别空间模型在确定平均面状类别( 反映判别变量的平均响应) 以及空间不确定性( 实为空间自相关的残差在地理空间的镜像) 的复现性或可重复性。     

面向GeoBML的作战任务建模与表达

针对目前指控系统的任务模型在地理信息语义描述上还不完善,不能满足战场环境仿真系统与指控系统之间的互操作问题,构建一种基于GeoBML的作战任务模型来有效解析指控系统的关键信息需求。分析了作战任务过程结构化特征,采用面向对象的方法构建作战任务和仿真过程概念模型;分析GeoBML的数据模型和形式化语法,使用形式化语言建立作战任务的语义模型;定义任务过程对象数据结构,构建任务驱动下的仿真过程数据映射模型;最后,基于该模型设计战场环境仿真平台组件并应用,验证其合理性与可扩展性。     

A GIS Toolbox for Measuring and Mapping Person‐Based Space‐Time Accessibility

This article presents a toolbox to compute and map person‐based accessibility indicators, based on classical time geography concepts. The intent is to provide GIS and urban planning practitioners with a user‐friendly and easily customizable tool. While it relies on well‐known concepts, the toolbox implements a major innovation in person‐based accessibility assessment by taking into account opening hours when measuring the accessibility of urban facilities. The toolbox can be downloaded from http://bit.ly/1h6yg5Z .     

Geospatial Human‐environment Simulation through Integration of Massive Multiplayer Online Games and Geographic Information Systems

This article reports on the initial development of a generic framework for integrating Geographic Information Systems (GIS) with Massive Multi‐player Online Gaming (MMOG) technology to support the integrated modeling of human‐environment resource management and decision‐making. We review Web 2.0 concepts, online maps, and games as key technologies to realize a participatory construction of spatial simulation and decision making practices. Through a design‐based research approach we develop a prototype framework, “GeoGame”, that allows users to play board‐game‐style simulations on top of an online map. Through several iterations we demonstrate the implementation of a range of design artifacts including: real‐time, multi‐user editing of online maps, web services, game lobby, user‐modifiable rules and scenarios building, chat, discussion, and market transactions. Based on observational, analytical, experimental and functional evaluations of design artifacts as well as a literature review, we argue that a MMO GeoGame‐framework offers a viable approach to address the complex dynamics of human‐environmental systems that require a simultaneous reconciliation of both top‐down and bottom‐up decision making where stakeholders are an integral part of a modeling environment. Further research will offer additional insight into the development of social‐environmental models using stakeholder input and the use of such models to explore properties of complex dynamic systems.     

Street‐segment‐based salt and abrasive prediction for winter maintenance using machine learning and GIS

Salting operations are essential but expensive in northern winters. We aim to predict the quantity of salt and abrasive needed for a specific road segment for each hour. An estimate of the quantity allows managers to better manage the loads in the trucks and to propose optimal vehicle routes based on the forecast, which will allow them to optimize costs. This article uses machine‐learning techniques based on truck telemetry data, weather conditions, and segment attributes. Geographic information systems (GIS) allow us to exploit the street‐network characteristics, which were ignored by previous prediction models. The results show that the XGBoost method performs better than other techniques (R² = 0.83).     

Integrating GIS and Data Visualization Tools for Distributed Hydrologic Modeling

Distributed hydrologic models are an integral component of spatial decision support systems for watershed management. At these basin (and larger) scales, a common problem in hydrology and other environmental sciences arises from the need to cope with the increasingly sophisticated models and software tools that are used in the management, processing, and analysis of large volumes of data collected from advanced in situ and remote monitoring instruments. The diversity of these tools, and the need for experts and non-experts alike to be able to easily use them, suggests a non-trivial integration problem of building customized systems from disparate (and in many cases proprietary) components. In this paper we address the systems integration problem within the context of a study of surface-subsurface-atmosphere interactions involving soil moisture remote sensing and hydrologic simulation. The simple early steps that were taken highlight the role of the different components and tools in the integration effort. An alternative approach is presented for creating an integrated system, based on a data flow model with the modular components linked within a flexible framework. An example is developed based on established systems integration techniques from the field of computer aided design.     

Appreciative GIS and Strength‐Based Community Change

Problem‐solving is embedded deeply in the digital DNA of GIS. Most projects involving GIS 1.0 and 2.0 raise community weaknesses, failures and other problems and use them to motivate change. The projects often create a future that does not differ greatly from the past or last long. Although looking into community problems is important and sometimes necessary, the steps of problem‐solving do not always leave people feeling happy. To inspire communities to create change based on their strengths and achievements, and to provide better participant experience, this article develops the concept of a new form of GIS called Appreciative GIS (AGIS). AGIS are grounded in the affirmative premise that every community, however challenged, is gifted with certain assets, potentials and strengths which, when effectively exploited, can take that community to a better and sustainable future. Based on Earth's internal structure, the article develops a useful layered community model where crust, mantle and core strata represent the community's body, life‐draining and life‐giving elements in that order. The model helps explain the different views of the community from current GIS and AGIS perspectives. A Total GIS (TGIS) cube is also developed and used to indicate that current GIS commonly focus on elements of the mantle or what we do not have, what we cannot do and what makes us weak. AGIS, on the other hand, dig up the core and cultivate what we have, what we can possibly do and what makes us strong. In a significant departure from the linear approach of problem‐solving, the article suggests implementing AGIS through a 7G cyclical method. The article contends that although AGIS may not be the whole enchilada, they can serve as a beacon of hope and a powerful source of inspiration especially for individuals and groups who are perceived or made to perceive themselves as dysfunctional, weak or poor.     

UML和象形图建立GIS数据库概念模型初探

空间数据库模型的构建是地理信息系统应用的基础,传统的地理信息数据库在管理机制、时间维的加入、对空间数据多尺度的表达等多方面存在问题,要解决这些问题就必须从建立可行的数据库概念模型开始研究。本文论述了为什么用UML和象形图可以解决这些问题,详细地说明了用这种方法建模的过程,并用一个实例来证明这种方法的可用性。     

可视化建模技术在GIS中的研究与应用

可视化建模是利用围绕现实想法组织模型的一种思考问题的方法。该技术以其简化需求、易于理解问题、沟通问题等特点被广泛应用于软件开发的各个环节中。本文分析了空间信息处理的特点,结合可视化建模和工作流的技术,提出了空间处理建模的概念,并探讨了空间处理建模的建模流程及应用方式。     

基于GIS和元胞自动机的荒漠化演化预测模型

荒漠化是当今全球最严重的环境与社会经济问题之一 ,荒漠化以其发展速度和严重的灾害性而引起国际学术界的广泛关注。开展荒漠化变化的驱动因素及其作用机制研究 ,尤其是在此基础上对荒漠化与其驱动因素之间的关系进行量化及动态模拟模型研究 ,对荒漠化的防治和治理具有十分重要的意义。尝试利用3S技术 ,结合元胞自动机理论架构出一套荒漠化动态模拟模型 ,进而对北京及邻区荒漠化的发展趋势进行预测。实验证明 ,这套系统是对荒漠化演化机制从宏观和微观角度进行模拟的有效方法。     

A Conceptual Framework for Uncertainty Investigation in Map‐based Land Cover Change Modelling

Uncertainty research represents a research stream of high interest within the community of geographical information science. Its elements, terminology and typology are still under strong discussion and adopted methods for analysis are currently under intensive development. This paper presents a conceptual framework for systematic investigation of uncertainty which occurs in applications of land cover change modelling in Geographical Information Systems (GIS) based on historical map data. Historical, in this context, means the map is old enough to allow identification of changes in landscape elements of interest, such as vegetation. To date such analyses are rarely conducted or not satisfactorily carried out, despite the fact that historical map data represent a potentially rich information source. The general validity and practicability of the framework for related applications is demonstrated with reference to one example in which forest cover change in Switzerland is investigated. The conceptual model consists of three domains in which main potential sources of uncertainty are systematically exposed. Existing links between data quality research and uncertainty are investigated to access the complex nature of uncertainty and to characterise the most suitable concepts for analysis. In accordance with these concepts appropriate methods and procedures are suggested to assess uncertainty in each domain. One domain is the production‐oriented amount of uncertainty which is inherent in the historical map. Vagueness and ambiguity represent suitable concepts for analysis. Transformation‐oriented uncertainty as the second domain occurs owing to editing and processing of digital data. Thereby, the suitable concept of uncertainty is error. The third domain is the application‐oriented uncertainty which occurs in comparing semantically different data. This domain relates to multi‐temporal discord which assumes the assessment of ‘equi‐temporal’ ambiguity and is thus connected to the production‐oriented domain. The framework provides an estimation of the overall amount of uncertainty. This can be linked to subsequent assessment of ‘fitness for use’. Thus the model provides a practicable and systematic approach to access the complex nature of uncertainty in the scope of land cover change modelling.