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.     

空间决策支持系统开发平台及其应用实例

空间决策支持系统（Ｓｐａｔｉａｌ Ｄｅｃｉｓｉｏｎ Ｓｕｐｐｏｒｔ Ｓｙｓｔｅｍ ＳＤＳＳ）作为在地理信息系统（ＧＩＳ）和决策支持系统（ＤＳＳ）基础上发展起来的一个新光科学技术领域,自本世纪８０年代中后期后来,在国内外已引起越来越广泛的关注和重视。通过大量文献的分析表明：对这种系统目前尚有许多不同的理解和认识。作者认为只有那些能够帮助决策者生成、比较和选择空间决策方案的信息系统才能纳入ＳＤＳＳ的范     

Detection of geothermal anomalies using Landsat 8 TIRS data in Tulu Moye geothermal prospect,Main Ethiopian Rift

Despite the high geothermal potential of the Main Ethiopian Rift (MER), risks associated with the industry and the difficulty of identifying possible targets using ground surveys alone continue to impede the development of geothermal power diligence in Ethiopia. In this paper, we investigate the geothermal potential of the Tulu Moye prospect area in the MER using Landsat 8, which is an important and cost-effective method of detecting geothermal anomalies. Data with a path/row of 168/054 were obtained from the Landsat 8 Operational Land Imager (OLI) and Thermal Infrared (TIR) sensors for October 17, 2014. Based on radiometric calibration, atmospheric correction (with the 6S model) and an NDVI-based threshold method for calculating land surface emissivity, a split-window algorithm was applied to retrieve the land surface temperature (LST) of the study area. Results show LST values ranging from 292.2 to 315.8 K, with the highest values found in barren lands. A comparison of LST between the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 shows a maximum difference of 1.47 K. Anomalous areas were also discovered, where LST was about 3-9 K higher than the background area. We identified seven of these as areas of high geothermal activity in the Tulu Moye prospective geothermal area. Auxiliary data and overlay analysis tools eliminated any non-geothermal influences. The research reveals that the distribution of highy prospective geothermal areas is consistent with the development and distribution of faults in the study area. Magmatism is the thermal source and faults provide conduits for the heat to flow from earth’s interior to the surface, facilitating the presence of geothermal anomalies. Finally, TIR remote sensing methods prove to be a robust and cost-effective technique for detecting LST anomalies in the geologically active area of MER. Moreover, combining TIR remote sensing with knowledge of the structural geology of the area and geothermal mechanisms is an efficient approach to detecting geothermal areas.     

地形效应校正的遥感地热异常提取

在山地复杂地形条件下,利用热红外遥感获得的地表温度分布显著受到地形的影响,真实的地热异常信息往往难以识别,热红外遥感应用于山区地热勘探受到极大限制。以广东龙川地热勘查区为研究区,初步探讨了山地环境中如何抑制地形效应,以有效提取地热异常。首先,基于Landsat ETM+遥感数据反演地表温度,分析坡向和坡度两个地形因子与地表温度的关系;然后,在此基础上,将研究区的地表温度按坡向分成3个子区(阳坡、过渡坡和阴坡),根据阳坡地表温度与坡向的线性拟合关系将其校正到水平坡度上;最后,结合地质构造分布和地表覆被情况,在3个子区识别了4处地热异常,并与已知地热点进行比较验证。结果表明:坡向分区和阳坡坡度校正能够有效抑制地形效应,提高遥感地热异常识别精度,为山区地热资源的预测评价提供新思路。     

建立面向区域农业可持续发展的空间决策支持系统的方法探讨

在解决诸如工业选址的空间问题时，空间决策支持系统避免了流行的商用ＧＩＳ软件在空间信息的分析评价，时空分布，预测和模拟以及决策等模型分析功能的不足，该文提出了建立ＳＤＳＳ的两种基本途径；一是利用现有ＧＩＳ与分析决策模型进行集成联结生成ＳＤＳＳ；另一种途径是自行开发具有空间数据管理和分析决策模型的一体化ＳＤＳＳ。     

空间决策支持系统及其支撑软件的设计与应用

本文讨论了SDSS的概念和基本理论,以决策支持为目标,面向半结构化和非结构化问题,用模型驱动的SDSS,是GIS未来的发展方向。在技术上用C语言实现了SDSS支撑软件的设计,并应用于国家科技攻关课题“三川河流域区域治理与开发信息系统”,取得了良好效果;同时对SDSS开发中存在问题作了讨论。     

Testing Popular Visualization Techniques for Representing Model Uncertainty

Many land allocation issues, such as land-use planning, require input from extensive spatial databases and involve complex decision-making. Spatial decision support systems (SDSS) are designed to make these issues more transparent and to support the design and evaluation of land allocation alternatives. In this paper we analyze techniques for visualizing uncertainty of an urban growth model called SLEUTH, which is designed to aid decision-makers in the field of urban planning and fits into the computational framework of an SDSS. Two simple visualization techniques for portraying uncertainty—static comparison and toggling—are applied to SLEUTH results and rendered with different background information and color schemes. In order to evaluate the effectiveness of the two visualization techniques, a web-based survey was developed showing the visualizations along with questions about the usefulness of the two techniques. The web survey proved to be quickly accessible and easy to understand by the participants. Participants in the survey were mainly recruited among planners and decision-makers. They acknowledged the usefulness of portraying uncertainty for decision-making purposes. They slightly favored the static comparison technique over toggling. Both visualization techniques were applied to an urban growth case study for the greater Santa Barbara area in California, USA.     

Geologic remote sensing for geothermal exploration: A review

This paper is a comprehensive review of the potential for remote sensing in exploring for geothermal resources. Temperature gradients in the earth crust are typically 25–30 °C per kilometer depth, however in active volcanic areas situated in subduction or rift zones gradients of up to 150 °C per kilometer depth can be reached. In such volcanic areas, meteoric water in permeable and porous rocks is heated and hot water is trapped to form a geothermal reservoir. At the Earth's surface hot springs and fumaroles are evidence of hot geothermal water. In low enthalpy systems the heat can be used for heating/cooling and drying while in high enthalpy systems energy is generated using hot water or steam. In this paper we review the potential of remote sensing in the exploration for geothermal resources. We embark from the traditional suite of geophysical and geochemical prospecting techniques to arrive at parameters at the Earth surface that can be measured by earth observing satellites. Next, we summarize direct and indirect detection of geothermal potential using alteration mineralogy, temperature anomalies and heat fluxes, geobotanical anomalies and Earth surface deformation. A section of this paper is dedicated to published remote sensing studies illustrating the principles of mapping: surface deformation, gaseous emissions, mineral mapping, heat flux measurements, temperature mapping and geobotany. In a case study from the La Pacana caldera (Chili) geothermal field we illustrate the cross cutting relationships between various surface manifestations of geothermal reservoirs and how remotely sensed indicators can contribute to exploration. We conclude that although remote sensing of geothermal systems has not reached full maturity, there is great potential for integrating these surface measurements in a exploration framework. A number of recommendations for future research result from our analysis of geothermal systems and the present contributions of remote sensing to studying these systems. These are grouped along a number of question lines: ‘how reproducible are remote sensing products’, ‘can long term monitoring of geothermal systems be achieved’ and ‘do surface manifestations link to subsurface features’?     

Accounting for Spatial Uncertainty in Optimization with Spatial Decision Support Systems

Spatial decision support systems (SDSS) are designed to make complex resource allocation problems more transparent and to support the design and evaluation of allocation plans. Recent developments in this field focus on the design of allocation plans using optimization techniques. In this paper we analyze how uncertainty in spatial (input) data propagates through, and affects the results of, an optimization model. The optimization model calculates the optimal location for a ski run based on a slope map, which is derived from a digital elevation model (DEM). The uncertainty propagation is a generic method following a Monte Carlo approach, whereby realizations of the spatially correlated DEM error are generated using 'sequential Gaussian simulation'. We successfully applied the methodology to a case study in the Austrian Alps, showing the influence of spatial uncertainty on the optimal location of a ski run and the associated development costs. We also discuss the feasibility of routine incorporation of uncertainty propagation methodologies in an SDSS.     

The development of spatial decision support system tool for marine spatial planning

A major problem associated with marine spatial planning (MSP) involves the difficult and time-consuming practice of creating a scenario that encompasses complex datasets in near real time via the use of a simple spatial analysis method. Moreover, decision-makers require a reliable, user-friendly system to quickly and accessibly acquire accurate spatial planning information. The development of national spatial data infrastructure (NSDI), which links the spatial data of a nation’s many diverse institutions, may pave the way for the development of a tool that can better utilize spatial datasets, such as a spatial decision support system (SDSS). Thus, this project aimed to develop an SDSS for MSP and to evaluate the feasibility of its integration within the NSDI framework. The seaweed culture was selected as an example due to its economic and technological acceptance by traditional fishers. Additionally, a multi-criteria analysis was used to develop the tool. Furthermore, a feasibility evaluation of its implementation within the NSDI framework was conducted based on the Delphi method. The results of the assessment indicated that the SDSS can be incorporated into the NSDI framework by addressing the policy issue – one map policy, updating custodians’ decree and data, and improve the standard and protocol.     

Cartography: Making Sense of Our Worlds

Abstract

One goal of cartographic research is to improve the usefulness of maps. To do so, we must consider the process of spatial knowledge acquisition, the role of maps in that process, and the content of cognitive representations derived. Research from psychology, geography, and other disciplines related to these issues is reviewed. This review is used to suggest potential new directions for research with particular attention to spatial problem solving and geographic instruction. A classroom experiment related to these issues is then described. The experiment highlights some of the implications that a concern for the process of spatial knowledge acquisition will have on questions and methods of cartographic research as well as on the use of maps in geographic instruction. It also provides evidence of independent but interrelated verbal and spatial components of regional images that can be altered by directed map work.     

The application of day and night time ASTER satellite imagery for geothermal and mineral mapping in East Africa

There is considerable interest in optimizing geothermal exploration techniques via the mapping of alteration and evaporate mineralisation, as well as of thermal emissions associated with geothermally active areas on the Earth’s surface. Optical and thermal satellite sensor technologies, improvements in processing algorithms and the means for large scale (e.g. 1:250,000) spatial data distribution are required for detecting both these attributes. The extensive visible, -near, -shortwave and thermal infrared (VNIR-SWIR-TIR) data archive acquired by the multi-spectral Advanced Spaceborne Thermal Emission Reflectance Radiometer (ASTER) provides a rich source of geoscience related imagery for geothermal exploration. Examples of generating large scale mosaicked ASTER imagery to provide province to continental mineral mapping have been undertaken in areas including such as Australia, western USA, Namibia and Zagros Mountains Iran. In addition, ASTER’s thermal infrared imagery also provides night time land surface temperature (LST) estimates relevant for detecting possible geothermal related anomalies.This study outlines existing methods for the application of ASTER data for geothermal exploration in East Africa. The study area encompasses a section of the East African Rift System across the Tanzanian and Kenyan border. The area includes rugged volcanic terrain which has had geological mapping of limited coverage at detailed scales, from various heritages and mapping agencies. This study summarizes the technology, the processing methodology and initial results in applying ASTER imagery for such compositional and thermal anomaly mapping related to geothermal activity. Fields observations have been used from the geothermal springs of Lake Natron, Tanzania, and compared with ASTER derived spectral composition and land surface temperature results. Published geothermal fields within the Kenyan portion of the study area have also been incorporated into this study.     

Development of a spatial decision support system for monitoring earthquake-induced landslides based on aerial photographs and the finite element method

The evaluation of slope stability is essential for the management of landslide hazards. The integration of spatial information and geomechanical modeling facilitates the understanding and evaluation of landslide hazards. In this study, we use a spatial decision support system (SDSS)—incorporating aerial photographic data, GIS techniques, field investigations, and finite element geomechanical modeling—to analyze the mechanisms of the Hungtaiping landslide, which was induced by the 1999 Chi-Chi earthquake. The analysis clarifies the slide mechanisms that cannot be revealed either by examining aerial photographic or underground exploration data alone. The finite element modeling calibrated using digital aerial photographic data shows that the landslide results from the deformation and slides of the thick colluvium. Surficial displacements in the twenties of meters are attributed to the slide between the colluvium and the bedrock as well as the shear deformation and slides within the colluvium. The landslide SDSS can help determine model parameters, evaluate slide mechanisms and remediation measures, and predict slope behavior for a subsequent earthquake event.     

Exploring differences of visual attention in pedestrian navigation when using 2D maps and 3D geo-browsers

ABSTRACT

Despite the now-ubiquitous two-dimensional (2D) electronic maps, three-dimensional (3D) globe viewers, or 3D geo-browsers such as Google Earth and NASA World Wind have gained much attention. However, the effect of such interactive 3D geo-browsers on spatial knowledge acquisition and decision-making is not well known. This study aims to explore the potential benefits of using interactive 3D geo-browsers in three processes of pedestrian navigation (self-localization, spatial knowledge acquisition, and decision-making) in digital environments. We employed eye tracking to show differences of visual attention in pedestrian navigation between a 2D map (Google Map) and a 3D geo-browser (Google Earth). The results indicated that benefits and drawbacks of 3D representations are task dependent. Participants using the 3D geo-browser had an extensively visual search resulting in significantly longer response time than the 2D participants for spatial knowledge acquisition, whereas 3D users performed a more efficient visual search and resulted in a better navigation performance at complex decision points. We speculate that the inefficient knowledge acquisition when using the 3D geo-browser was most probably due to information overload and obstructed views. Landmarks in photorealistic 3D models assisted recall of spatial knowledge from mental maps, which contributed to efficient decision-making at a complex turning point. These empirical results can be helpful to improve the usability of pedestrian navigation systems.     

空间决策支持系统在商业智能中的应用研究

介绍了空间决策支持系统和商业智能的基本概念。分析了对商业决策有影响的空间因素，并借鉴Huff模型对网点吸引力进行了表达。描述了商业空间决策支持系统的总体设计。     

Challenges and strategies for the visual exploration of complex environmental data

ABSTRACT

In this opinion paper, we, a group of scientists from environmental-, geo-, ocean- and information science, argue visual data exploration should become a common analytics approach in Earth system science due to its potential for analysis and interpretation of large and complex spatio-temporal data. We discuss the challenges that appear such as synthesis of heterogeneous data from various sources, reducing the amount of information and facilitating multidisciplinary, collaborative research. We argue that to fully exploit the potential of visual data exploration, several bottlenecks and challenges have to be addressed: providing an efficient data management and an integrated modular workflow, developing and applying suitable visual exploration concepts and methods with the help of effective and tailored tools as well as generating and raising the awareness of visual data exploration and education. We are convinced visual data exploration is worth the effort since it significantly facilitates insight into environmental data and derivation of knowledge from it.     

Heterogeneous surface displacement pattern at the Hatchobaru geothermal field inferred from SAR interferometry time-series

We estimated surface displacements using persistent scatterer SAR interferometry (PS-InSAR) around the Hatchobaru geothermal field, Japan, from 18 ALOS/PALSAR images acquired from July 2007 to December 2010. Generally, geothermal fields, covered with natural targets such as rocky terrain and vegetation, have been one of the difficult targets for PS-InSAR analysis. However, we applied space adaptive filtering to increase the number of pixels for measuring surface displacement. The results of our analysis demonstrate ground subsidence with decaying velocity over the observation period around the geothermal field. The spatial pattern of ground subsidence includes sharp boundaries of subsidence that can be interpreted as fault traces. We demonstrated the usefulness of PS-InSAR analysis with the space adaptive filtering to estimate surface displacements with high spatial resolution and high spatial density around a geothermal field.     

Interface Design for Geographic Visualization: Tools for Representing Reliability

Digital "softcopy" maps are becoming the norm—replacing static paper maps in applications from wayfinding to scientific research. As a result, the design of interface tools that allow users to manipulate map parameters effectively and efficiently is likely to become as fundamental to cartography as the design of maps themselves. This article presents some principles for the design of interfaces to geo-referenced data. These principles are summarized in a hierarchical approach to interface design with conceptual, operational, and implementational levels. This hierarchical approach leads designers from questions about the goals of the system and the users of that system to the creation of tools to accomplish those goals and interface controls that allow effective interaction with the tools. The article goes on to describe the application of these principles to a prototype geographic visualization system designed for exploration of spatial data sets and visualization of reliability of both data and data abstractions associated with environmental change. The prototype involves a synthesis of concepts and methods derived from cartography, scientific visualization, and exploratory data analysis into a system for exploratory spatial data analysis and spatial decision support.     

Integrating a Raster Geographical Information System with Multi‐Objective Land Allocation Optimization for Conservation Reserve Design

The multi‐objective land allocation problem is to optimize the selection of land for different uses based on a set of decision objectives. For most applications, a geographical information system (GIS) is either absent or loosely coupled through file exchange. In this article the evolutionary algorithm (EA), a heuristic solution method for optimization problems, is integrated with a raster GIS to form a spatial decision support system (SDSS) for multi‐objective conservation reserve design. The SDSS effectively combines the functions of a GIS for data management, analysis, and visualization, with the optimization capability of the EA; and provides a uniform way to solve conservation reserve design problems with different types of constraints and objectives. The SDSS is demonstrated through application to the creation of conservation reserves in Bolivia to protect 17 endemic mammals.