Cartoblography: Experiments in Using and Organising the Spatial Context of Micro‐blogging

Blogs, micro‐blogs and online forums underpin a more interconnected world. People communicate ever more and are increasingly keen to explain and illustrate their lives; showing where they are and what they are doing. Desktop, online and mobile mapping landscapes have never been as rich or diverse yet this challenges cartography to adapt and remain relevant in the modern mapping world. We explore the spatial expression and potential value of micro‐blogging and Twitter as a social networking tool. Examples of “twitter maps” are reviewed that leverage the Twitter API and online map services to locate some component of the “tweet”. Scope, function and design are illustrated through development of two proof‐of‐concept map mashups that support collaborative real‐time mapping and the organisation and display of information for mass user events. Through the experiments in using and organising data in this way we demonstrate the value of “cartoblography”– a framework for mapping the spatial context of micro‐blogging.     

Understanding User Interaction Patterns within Online Systems for Public‐Participation Transportation Planning

Many research projects in public‐participation geographic information systems focused on the development of software prototypes that were conceptualized to complement traditional forms of public participation. Given the challenges introduced by the heterogeneity of their user base, system design, and decision making process, empirical evaluations of such systems based on actual use have been scarce. This article reports on a rigorous empirical assessment of human‐computer interaction of users of a web‐based system for participatory transportation planning. We devised three groups of participants with below‐average, average, and above‐average interaction duration through hierarchical cluster analysis. Subsequently, the characteristics of the clusters were subjected to logistic regression analysis to determine the significance and strength of statistical associations between duration of interaction and a host of individual‐level variables. Our results indicate a statistically significant reduction of the odds‐ratio for participants with above‐average duration of interaction in the case of no prior experience with online transportation discussions. No significant associations were found between overall duration of interaction and sociodemographic background, cognitive decision‐making style, and travel behavior. We advocate for the development of adaptable participatory systems which accommodate flexibility in terms of both the user interface and pathways of the decision making process.     

Similarity Weighted Instance‐based Learning for the Generation of Transition Potentials in Land Use Change Modeling

Land use change models are increasingly being used to evaluate the effect of land change on climate and biodiversity and to generate scenarios of deforestation. Although many methods are available to model land transition potentials, they are usually not user‐friendly and require the specification of many parameters, making the task difficult for decision makers not familiar with the tools, as well as making the process difficult to interpret. In this article we propose a simple method for modeling transition potentials. SimWeight is an instance‐based learning algorithm based on the logic of the K‐Nearest Neighbor algorithm. The method identifies the relevance of each driver variable and predicts the transition potential of locations given known instances of change. A case study was used to demonstrate and validate the method. Comparison of results with the Multi‐Layer Perceptron neural network (MLP) suggests that SimWeight performs similarly in its capacity to predict transition potentials, without the need for complex parameters. Another advantage of SimWeight is that it is amenable to parallelization for deployment on a cloud computing platform.     

环境空气质量系列专题地图制图方法研究

环境与发展是当今世界共同关注的重大问题。目前我国经济正处于高速发展时期,随着经济社会的快速发展和城镇一体化进程的加快,空气污染问题日趋严重,对人体健康造成很大伤害,因此环境保护的重要性日益突出。本文通过建立环境质量空间数据库,利用地理信息软件ArcGIS为基础平台,将环境空气质量监测数据与地理空间位置进行地理匹配,利用地理信息可视化技术,实现环境空气质量监测数据中各主要空气污染物的浓度时间分布的可视化表达,制作环境空气质量专题地图,有助于有效地从海量监测数据中发现有价值的信息,为环境保护部门提供决策参考依据。     

Spatial Prediction of Landslide Hazard Using Fuzzy k-means and Dempster-Shafer Theory

Landslide databases and input parameters used for modeling landslide hazard often contain imprecisions and uncertainties inherent in the decision‐making process. Dealing with imprecision and uncertainty requires techniques that go beyond classical logic. In this paper, methods of fuzzy k‐means classification were used to assign digital terrain attributes to continuous landform classes whereas the Dempster‐Shafer theory of evidence was used to represent and manage imprecise information and to deal with uncertainties. The paper introduces the integration of the fuzzy k‐means classification method and the Dempster‐Shafer theory of evidence to model landslide hazard in roaded and roadless areas illustrated through a case study in the Clearwater National Forest in central Idaho, USA. Sample probabilistic maps of landslide hazard potential and uncertainties are presented. The probabilistic maps are intended to help decision‐making in effective forest management and planning.     

A New GIScience Application for Visualized Natural Resources Management and Decision Support

This article presents two decision support plug‐ins in free GIS software: ArcGIS Explorer Desktop. The ubiquitous WebGIS Analysis Toolkit for Extensive Resources (uWATER) focuses on providing GIS analysis functions: spatial and attribute queries in the public services tool for users with limited access to commercial GIS software. The interface of uWATER is general enough to support decision‐making in numerous management issues in natural resources, economics and agriculture. The uWATER‐Pumping Assessment (uWATER‐PA) toolkit, on the other hand, is an extended package targeting the specific environmental issue of groundwater pumping impacts. The uWATER‐PA package is an excellent alternative to evaluating complex groundwater pumping assessment issues before investing significant time, labor, and funds in monitoring and detailed scientific study. It incorporates simulation of the physics of groundwater flow and user interaction into GIS software. A graphical user interface makes both data entry and interpretation of results intuitive to non‐technical individuals. Results are presented as colored drawdown maps and can be saved in GIS format for future dissemination. The impact of drawdown on existing wells can be characterized and mapped, through the use of uWATER's spatial query capabilities and the drawdown maps generated by uWATER‐PA.     

Geomorphometry from unmanned aerial surveys

Unmanned aerial systems (UASs) are widely used for remote sensing, including the production of high‐resolution digital elevation models (DEMs). We study the possibilities of UAS‐based aerial surveys to produce photogrammetrically sound, high‐resolution DEMs intended for geomorphometric modeling. The study was conducted at the Zaoksky testing ground (Russia). To carry out an aerial survey, we used a UAS Geoscan‐101 equipped with a Sony DSC‐RX1 camera and a Topcon GNSS receiver. Aerial photographs were processed using Agisoft PhotoScan Professional software. Applying dense point cloud generation and classification, we produced DEMs with resolutions of 6 cm, 20 cm, and 1 m. Using a universal spectral analytical method, we derived models of several morphometric variables (i.e., slope gradient, horizontal, vertical, minimal, and maximal curvatures) from DEMs with resolutions of 20 cm and 1 m. We found that it is possible to produce noiseless models and well‐readable maps of morphometric variables for grassy areas with separately standing groups of trees and shrubs. However, UAS‐based DEMs cannot be applied for modeling of forested areas: there occur pronounced unrecoverable artifacts due to errors of automated classification of the dense point cloud. Finally, we present recommendations for the production of UAS‐derived, photogrammetrically sound, high‐resolution DEMs intended for geomorphometry.     

Location Intelligence: An Innovative Approach to Business Location Decision‐making

As one of the leading ‘world cities’, London is particularly reliant on sources of foreign direct investment (FDI). In the face of increasing global competition and a difficult economic climate, the capital must compete effectively to encourage and support such investors. Through a collaborative study with London's official FDI promotion agency, Think London, the need for a coherent framework for data, methodologies and tools to inform business location decision‐making became apparent. This article discusses the development of a rich environment to explore, compare and rank London's business neighbourhoods. This is achieved through the development and evaluation of a model for location‐based decision support. First, we discuss the development of a geo‐business classification for London which draws upon methods and practices common in geodemographic neighbourhood classification. A geo‐business classification is developed, encapsulating relevant location variables using Principal Components Analysis into a set of composite area profiles. Second, we discuss the implementation of an appropriate Multi‐Criteria Decision Making methodology, in this case Analytical Hierarchy Process (AHP), enabling the aggregation of the geo‐business classification and decision‐makers' preferences into discrete decision alternatives. Finally, we present the results of the integration of both data and model through the development and evaluation of a web‐based prototype.     

An integrated virtual geographic environmental simulation framework: a case study of flood disaster simulation

Dynamic flood disaster simulation is an emerging and promising technology significantly useful in urban planning, risk assessment, and integrated decision support systems. It is still an important issue to integrate the large assets such as dynamic observational data, numerical flood simulation models, geographic information technologies, and computing resources into a unified framework. For the intended end user, it is also a holistic solution to create computer interpretable representations and gain insightful understanding of the dynamic disaster processes, the complex impacts, and interactions of disaster factors. In particular, it is still difficult to access and join harmonized data, processing algorithms, and models that are provided by different environmental information infrastructures. In this paper, we demonstrate a virtual geographic environments-based integrated environmental simulation framework for flood disaster management based on the notion of interlinked resources, which is capable of automated accumulating and manipulating of sensor data, creating dynamic geo-analysis and three-dimensional visualizations of ongoing geo-process, and updating the contents of simulation models representing the real environment. The prototype system is evaluated by applying it as a proof of concept to integrate in situ weather observations, numerical weather and flood disaster simulation models, visualization, and analysis of the real time flood event. Case applications indicate that the developed framework can be adopted for use by decision-makers for short-term planning and control since the resulting simulation and visualization are completely based on the latest status of environment.     

Assessing Resistance to Volunteered Geographic Information Reporting within Local Government

Using volunteered geographic information (VGI) as a cost‐saving environmental monitoring and public participation mechanism has been thought to be a proof of concept to assist environmental decision‐making with insufficient managerial resources. However, research literature also often found institutional resistance when implementing VGI as part of the decision‐making process. This research develops a conceptual framework as the foundation to conduct a cross‐case comparison for four empirical cases in recreation and invasive species monitoring, but general enough for other such case comparisons. The VGI Reporting Assessment Framework (VGI‐RAF) adopted aspects of the Decision Situation Assessment (DSA) framework as the foundation to address institutional flexibility, stakeholder dynamics, and technical considerations. Using a cross‐case comparison can accumulate deep observations from cases and increase validity of insights through comparing processes. Results show that eight aspects of the VGI‐RAF reveal the suitability of embedding voluntary information within existing institutional decision‐making processes. VGI‐RAF depicts considerations for: (1) existing participation arrangements, (2) institutional arrangements, (3) managers’ needs and stakeholder expectation, and (4) interaction mechanism and technical needs. The cross‐comparison results indicate that a public participation mechanism should be accompanied by VGI development to increase effectiveness. Institutional arrangements should match local government's information needs with participants’ expectations. Knowledge gaps between institutional information needs and volunteer knowledge should be filled through technology enhancements. For ease of implementation and to promote long‐term success, we recommend that volunteered information be connected with existing communication channels to minimize changes to existing information systems.     

Temporal Accuracy in Urban Growth Forecasting: A Study Using the SLEUTH Model

This study attempts to establish multi‐temporal accuracy of the predicted maps produced by a land use change simulation model over time. Validation of the forecasted results is an essential part of predictive modeling and it becomes even more important when the models are used for decision making purposes. The present study uses a popular land use change model called SLEUTH to investigate the temporal trend of accuracy of the predicted maps. The study first investigates the trend of accuracy of the predicted maps from the immediate future to the distant future. Secondly, it investigates the impact of the prediction date range on the accuracy of the predicted maps. The objectives are tested for the city of Gorizia (Italy) using three sets of map comparison techniques, Kappa coefficients, Kappa Simulation and quantity disagreement and allocation disagreement. Results show that, in addition to the model's performance, the decrease in the accuracy of the predicted maps is dependent on factors such as urban history, uncertainty of input data and accuracy of reference maps.     

Revealing Uncertainties in Land Change Modeling Using Probabilities

Land change models are frequently used to analyze current land change processes and possible future developments. However, the outcome of such models is accompanied by uncertainties that have to be taken into account in order to address their reliability for science and decision‐making. While a range of approaches exist that quantify the disagreement of land change maps, the quantification of uncertainty remains a major challenge. The aim of this article is therefore to reveal uncertainties in land change modeling by developing two measures: quantity uncertainty and allocation uncertainty. We choose a Bayesian Belief Network modeling approach for deforestation in Brazil to develop and apply the two measures to the resulting probability surface. Quantity uncertainty describes the uncertainty about the correct number of cells in a land change map assigned to different land change categories and allocation uncertainty expresses the uncertainty about the correct spatial placement of a cell in the land change map. Thus, uncertainty can be quantified even in those cases where no reference data exist. Informing about uncertainty in probabilistic outcomes may be an important asset when land change projections are being used in science and decision‐making and moreover, they may also be further evaluated for other spatial applications.     

A Task-Based Approach to User Interface Design for a Web-Based Hydrologic Information Systems

Hydroinformatics is a new and rapidly developing field that integrates knowledge and understanding of water resources with the latest developments in information technology to improve decision‐making in many critical applications. It encompasses methods for data capture, storage, processing, analysis and visualization, and the use of advanced modeling, simulation, optimization and knowledge‐based tools and systems infrastructure. Three types of hydrological data are most commonly used: flow rate in major rivers and streams, height of water in wells, and precipitation. To get a complete view of the state of water at a given point in space and time, one must analyze many different types of hydrological data together to derive information using an online GIS tool. To help use these disparate data sources more effectively and efficiently, we have built an online interface called the IJEDI WebCenter for Hydroinformatics using a task‐based approach. In this design, we first identify the tasks that users perform to study water‐related issues, then organize data for each task, and build task‐specific tools to present and analyze data and information. In a study involving both novices and experts in hydrology, we found that the both groups performed water‐related studies more effectively and efficiently than they would have without the WebCenter.     

Creating a conceptual framework to improve the re‐usability of open geographic data in cities

Open data has a profound effect on the working environment within which information is created and shared at all levels. At the local government level, open data initiatives have resulted in higher transparency in policy, a greater engagement between decision‐makers and citizens, and have changed the culture about how data analysis and evidence are used to support local governance. This article, based on data collected through an on‐line survey, participatory workshops with data user communities in four cities (in Colombia and Spain), and interviews with Valencia good‐government office, identifies four elements for a conceptual framework to improve the re‐usability of open geographic data in cities. The essential elements defined in this research are the definition of data user communities and their needs, the creation of the community of reuse, user‐focused metadata, and reuse‐focused legal terms. The definition of these indicators provides a framework for authorities to re‐shape their current open data strategy to include data user requirements. At the end of this article, a roadmap for future research and implementation is presented, considering some reflections on the conceptual framework.     

Spatial Approaches to Modeling Dispersion of Communicable Diseases – A Review

The dispersion of communicable diseases in a population is intrinsically spatial. In the last several decades, a range of spatial approaches has been devised to model epidemiological processes; and they differ significantly from each other. A review of spatially oriented epidemiological models is necessary to assess advances in spatial approaches to modeling disease dispersion and to help identify those most appropriate for specific research goals. The most notable difference in the design of these spatially oriented models is the scale and mobility of the modeling unit. Using two criteria, this review identifies six types of spatially oriented models. These include: (1) population‐based wave models, (2) sub‐population models, (3) individual‐based cellular automata models, (4) mobile sub‐population models, (5) individual‐based spatially implicit models, and (6) individual‐based mobile models. Each model type is evaluated in terms of its design principles, assumptions, and intended applications. For the evaluation of design, four aspects of design principles are discussed: the modeling unit, the interaction between the modeling units, the spatial process, and the temporal process utilized in a design. Insights gained from this review can be useful for devising much‐needed spatially and temporally oriented strategies to forecast, prevent, and control communicable diseases.     

An integrated environment for developing knowledge-based spatial decision support systems

Knowledge-based spatial decision support systems (KBSDSS) incorporate heuristic reasoning, and analytical and spatial modelling capabilities to support decision making in resource and environmental management. They are able to provide the assistance for both the structuring and formulation of the spatial problem, and the design and execution of a solution process by automatically integrating different types of models and data. This paper presents a KBSDSS development environment, which connects a GIS tool (ARC/INFO) with an expert system tool (CLIPS) and a hypertext diagramming tool (HARDY). ARC/INFO provides capabilities for spatial data handling. CLIPS is used to develop knowledge bases and heuristic reasoning. HARDY is used to represent spatial problems in terms of diagrams that can then be translated into a CLIPS knowledge base for evaluation. The development environment allows users to structure their problems and develop models for particular requirements and domains.     

A web‐based visualization tool for exploring stakeholder conflicts in land‐use planning

This article describes an open source web‐based visualization tool for exploring stakeholder conflicts in land‐use planning. It implements a multi‐criteria, decision‐analytic framework which solves a conflict‐constrained knapsack problem in order to find Pareto efficient combinations of actions which maximize public value, given the conflict constraint. The user interface is centered around an interactive map in which geographical subareas are color‐shaded in proportion to the mean strength of preference for a particular chosen action within the population in the selected area. The aim of this work is to investigate the use of web technologies and formal problem‐solving methods for improving public participation in land‐use planning and support local governments in the pursuit of improved decision‐making. The tool was developed using the free statistical programming language R and the web application framework Shiny. Its usefulness is demonstrated through a case study in Upplands Väsby municipality in Stockholm County, Sweden. The article ends with a summary together with some ideas for future research and development.     

Design Considerations and Evaluation of a Collaborative, Spatio-Temporal Decision Support System

Collaborative spatial decision support systems (C‐SDSS) have been used to help groups of stakeholders understand data and search for opportunities at resolving local and regional decision problems in various domains including land use, trans‐ portation, and water resources. The key issue in designing an effective C‐SDSS is the anticipation of user information needs. Knowledge of user information needs can guide system designers in achieving a C‐SDSS that fits the decision process. In this paper we present a design approach that is informed by stakeholder concerns, as part of a user needs assessment. The approach is based on the premise that knowing stakeholders’ concerns can help anticipate user information needs and consequently lead to a more usable C‐SDSS. We demonstrate the approach with the example of a spatio‐temporal decision problem involving conjunctive water administration in the Boise River Basin in southwestern Idaho. The spatial dimension of the decision task involves delineating the areas of conjunctive water administration while the temporal dimension involves selecting the year in which a given area will start to be administered. We show how the elicitation of stakeholder concerns leads to functional specification of a collaborative spatio‐temporal decision support system.     

Rendering 2D Lines on 3D Terrain Model with Optimization in Visual Quality and Running Performance

With the gradual shift from 2D maps to a 3D virtual environment, various visual artifacts were generated by overlaying 2D map symbols on 3D terrain models. This work proposes a novel screen‐based method for rendering 2D vector lines with the accuracy of more than one pixel on the screen in real time. First, screen pixels are inversely projected onto a 3D terrain surface, and then onto the 2D vector plane. Next, these pixels are classified into three categories in terms of their intersection situation with the 2D lines. After that, a multiple sampling process is applied to the pixels that intersect with the 2D lines in order to eliminate visual artifacts, such as intermittence and aliasing (in pixel scale). Finally, a suitable point‐in‐polygon judgment is implemented to color each sample point quickly. The algorithm is realized in a heterogeneously parallel model so that the performance is improved and becomes acceptable.     

A Combined Biophysical and Economic GIS Framework to Assess Sugarcane Cropping Potential in Brazil

Recently, the increasing demand for biofuels triggered a new phase for the sugar‐alcohol sector. In Brazil, as well as in other tropical countries, this process raised worries regarding the possible direct and indirect effects of the crop's expansion on the conversion of native vegetation coverings. Therefore, the modeling of spatial‐economic surfaces, representing the potential rent variation in its spatial component, for economic activities, may be a useful tool in the decision‐making process. Hence, here we propose and present the results of a combined framework composed of two modules using the modeling platform Dinamica EGO. The first module simulates sugarcane's growth, calculating the daily response of the crop to environmental conditions during the stages of the plant's development. The second module estimates rents for sugarcane cultivation in Brazil, identifying areas where this activity would bring higher economic return, looking at simulated productivity, production costs and selling prices in a way that is spatially explicit for Brazil. Two different scenarios for production costs were tested, and results ranged from negative values to maxima of R$/ha 929 and R$/ha 1176 for standard and efficient costs of production, respectively. The model successfully indicated non‐profitable and profitable areas, and regions where high expected economic return overlaps endangered ecosystems.