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.     

CEMPS: A prototype spatial decision support system to aid in planning emergency evacuations

CEMPS is a prototype spatial decision support system which links the topographical support and analysis provided by a geographic information system, ARC/INFO, with the ability to simulate the dynamics of an evacuation process. CEMPS has been designed to enable emergency planners to experiment with different emergency evacuation plans in order to devise a plan which meets their requirements. ARC/INFO is used to parameterize a dynamic simulation with topographical information and to display its results. The prototype runs on a Sun SPARCStation cluster but could be modified to run on other hardware and software.     

Spatial decision support system for home-delivered services

 We present a spatial decision support system for the non-profit sector, designed to assist planning in the area of home-delivered services such as meals on wheels. Using data collected from existing programs, current and forecasted demographic data, and a set of algorithmic tools, we provide a system for evaluating current meals on wheels facilities, and for making incremental facility location decisions that satisfy coverage and equity requirements. Received: 27 September 2000 / Accepted: 22 March 2001     

GIS- and RS-based spatial decision support: structure of a spatial environmental information system (SEIS)

Abstract

The development of spatial decision support for environmental resource management, e.g. forest and agroecosystem management, biodiversity conservation, or hydrological planning, started in the 1980s and was the focus of many research groups in the 1990s. The combined availability of spatial data and communication, computing, positioning, geographic information system (GIS)- and remote sensing (RS)-technologies has been responsible for the implementation of complex SDSS since the late 1990s. The regional GIS-based modelling of environmental resources, and therefore ecosystems in general, requires setting-up an extensive geo and model database. Spatial data on topography, soil, climate, land use, hydrology, flora, fauna and anthropogenic activities have to be available. Therefore, GIS- and RS-technologies are of central importance for spatial data handling and analysis. In this context, the structure of spatial environmental information systems (SEIS) is introduced. In SEIS, the input data for environmental resource management are organised in at least seven sub-information systems: base geodata information system (BGDIS), climate information system (CIS), soil information system (SIS), land use information system (LUIS), hydrological information system (HIS), spatial/temporal biodiversity information system (STBIS), forest/agricultural management information system (FAMIS). The major tasks of a SEIS are to (i) provide environmental resource information on a regional level, (ii) analyse the impact of anthropogenic activities and (iii) simulate scenarios of different impacts.     

Spatial understanding and decision support system: A prototype for public GIS

The idea of public participation GIS involves the use of GIS tools to help laypcople understand the spatial consequences of proposed projects, evaluate alternatives, and create new solutions. The widening use of information networks creates opportunities for making GIS a widely accessible decision-making tool, bypassing the constraints of location and time. This paper presents a prototype software that enables group collaboration across space and time using the Internet infrastructure. The prototype, called Spatial Understanding and Decision Support System (SUDSS), was designed to facilitate a controlled experiment in collaborative group work aimed at solving a realistic land-use planning problem. The paper discusses design considerations for a distributed public GIS and presents the functionality of SUDSS using the example of group participation in developing a land-use zoning plan.     

A GIS-based decision support system for analysis of route choice in congested urban road networks

Urban congestion patterns have become ubiquitous and complex. Traditional, “static” approaches are no longer adequate for analyzing network flows and conducting minimum cost routing. This paper reports on a GIS-based decision support tool for modeling dynamic network congestion and conducting minimum cost routing. The system predicts network flows at a detailed level of temporal resolution, capturing dynamic congestion propagation effects. A Route Planner module solves for the combined departure time and minimum cost routing required for a trip to reach its destination by a given deadline. The GIS provides effective decision support through its database management capabilities, graphical user interfaces and cartographic visualization. This supports analyses of “what-if?” scenarios for strategic planning and tactical management subject to unplanned network disturbances. Received: 1 October 1999/Accepted: 21 September 2000     

防汛会商决策支持系统实现方法

防汛会商属于风险决策和群决策,本文基于决策支持理论,结合我国防汛指挥的实际情况,详细分析论证了当今的信息技术特点和应用前景,阐述了信息领域的网络技术、地理信息系统技术、数据仓库技术和人工智能等在防汛会商决策支持系统中的实际应用。概述了防汛会商决策支持系统的总体结构和实现思路。     

The framework of a geospatial semantic web-based spatial decision support system for Digital Earth

Abstract

While significant progress has been made to implement the Digital Earth vision, current implementation only makes it easy to integrate and share spatial data from distributed sources and has limited capabilities to integrate data and models for simulating social and physical processes. To achieve effectiveness of decision-making using Digital Earth for understanding the Earth and its systems, new infrastructures that provide capabilities of computational simulation are needed. This paper proposed a framework of geospatial semantic web-based interoperable spatial decision support systems (SDSSs) to expand capabilities of the currently implemented infrastructure of Digital Earth. Main technologies applied in the framework such as heterogeneous ontology integration, ontology-based catalog service, and web service composition were introduced. We proposed a partition-refinement algorithm for ontology matching and integration, and an algorithm for web service discovery and composition. The proposed interoperable SDSS enables decision-makers to reuse and integrate geospatial data and geoprocessing resources from heterogeneous sources across the Internet. Based on the proposed framework, a prototype to assist in protective boundary delimitation for Lunan Stone Forest conservation was implemented to demonstrate how ontology-based web services and the services-oriented architecture can contribute to the development of interoperable SDSSs in support of Digital Earth for decision-making.     

A new trapezoidal-mesh based data model for spatial operations

This paper presents a new spatial data model based on trapezoidal-mesh for implementing spatial operations within geographical information systems (GIS). Based only on the solid foundation of spatial operations, diversified application models can be established to bridge the gap between Digital Earth models and the real world with its real-world problems (‘connecting through location’). In this paper, the involved polygon features are decomposed into a series of trapezoidal-meshes. Then, geo-processing operations are employed on these meshes rather than the original polygon features, resulting in a relatively simple spatial computation. As a kind of model designed by integrating raster with vector, the model presented here has advantages over other models when carrying out spatial operations insofar as providing a solid foundation for achieving the grand goal of Digital Earth. The concept of this data model and the two extensive examples of its application in spatial operations are elaborated upon in this article. As a result, this article and the research that supports it, proves that the adoption of the trapezoidal-mesh model greatly improves the efficiency of spatial operations in GIS.     

Development of a GIS-based decision support system for assessing land use status

IntroductionAgriculturallandusepatternsandtheirchangesaretightlyrelatedwithagriculturepolicyandfoodsecurityissuesundergrowingfooddemand,assess mentofglobalclimatechangeimpactsonagricul ture,environmentalissuesduetotheintensificationofagriculturallandusessuchaswaterpollution,soildegradation,andrecentlywaterscarcityissues.Soasustainableandholisticplanningandmanage mentoflandresourcesshouldcombineallthesere latedinformationwithefficienttoolsforassessmentandevaluationinordertopermitbroad ,interact…     

Development of a GIS-based decision support system for assessing land use status

The objectives of this study are to assess land suitability and to predict the spatial and temporal changes in land use types (LUTs) by using GIS-based land use management decision support system. A GIS database with data on climate, topography, soil characteristic, irrigation condition, fertilizer application, and special socioeconomic activities has been developed and used for the evaluation of land productivity for different crops by integrating with a crop growth model—the erosion productivity impact calculator (EPIC). International food policy simulation model (IFPSIM) is also embedded into GIS for the predictions of how crop demands and crop market prices will change under alternative policy scenarios. An inference engine (IE) including land use choice model is developed to illustrate land use choice behavior based on logit models, which allows to analyze how diversified factors ranging from climate changes, crop price changes to land management changes can effect the distribution of agricultural land use. A test for integrated simulation is taken in each 0.1o by 0.1o grid cell to predict the change of agricultural land use types at global level. Global land use changes are simulated from 1992 to 2050.     

Developing a web-based spatial decision support system for geothermal exploration at the Olkaria geothermal field

ABSTRACT

Geothermal exploration is a complex process that spans a number of disciplines. Before a decision is made to drill a geothermal well, there is need for an extensive exploration process to determine the most suitable location. The process of evaluating and analyzing data from individual scientific disciplines can be complex and tedious. Attempts have been made at solving this problem using GIS-based tools but the uptake of these tools is often hindered by the limited knowledge of GIS by decision makers. This paper presents an approach for solving the geothermal exploration question through a web-based spatial decision support system (SDSS) that incorporates the various geosciences through a multi-criteria spatial decision analysis model. The results reveal a decision-making gap that is to be filled using a novel, automated exploration SDSS. This approach hypothesizes an easier and faster decision-making process. The research focuses on Olkaria, an active geothermal area in Kenya, East Africa and highlights a pragmatic approach to identifying priority areas for drilling. It evaluates contributions made by many disciplines in identifying potential sites ideal for harnessing geothermal energy and the gaps that emerge in an effort to synergize the results from the different disciplines.     

土地利用优化配置人工免疫并行决策支持系统

目的 从土地资源优化配置的两大核心问题的基本特点和求解需求出发,提出了面向土地资源优化配置问题求解的多目标人工免疫优化模型框架;对智能决策支持系统的架构、算法扩展与应用扩展接口、优化模型的并行化策略等关键技术进行了设计;选取湖北省秭归县作为实验区,对系统的通用性与可扩展性进行了验证,并对优化模型的多目标寻优能力和并行性能进行了评估。     

基于密度的小生境粒子群算法在空间信息服务选择中的应用

针对现有空间信息服务选择技术的不足,提出了一种基于粒子群优化算法的多目标优化策略,通过同时优化多个QoS参数,产生一组满足约束条件的Pareto最优解。针对多峰函数的多目标优化问题,采用基于改进密度聚类的小生境技术,保证了解的多样性。构建了模拟试验环境,验证了算法的可行性和效率。     

顾及地理矢量场空间变化特征的多分辨率纹理可视化方法

网络环境下海量、高维、动态、多尺度地理空间矢量场数据的在线高效可视化,一直是大规模密集矢量场数据集成与综合应用分析亟须解决的关键问题。地理矢量场数据蕴含大量非规则、多尺度、时空异质的变化特征与结构,传统矢量场纹理可视化方法,受全局统一采样密度的限制,存在典型的稠密遮挡、特征模糊的问题。针对上述问题,本文提出了一种顾及地理矢量场空间变化特征的多分辨率纹理可视化方法,引入复合信息熵定量显式描述矢量场的空间变化,以此驱动图像空间内多频噪声纹理生成、矢量场多分辨率纹理的构建与增强表达,有效克服传统纹理可视化方法的技术瓶颈。最后采用风场数据进行试验,验证了本文方法的可靠性与有效性。     

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.     

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.     

Assessment of Sentinel-1A data for rice crop classification using random forests and support vector machines

This study developed an approach to map rice-cropping systems in An Giang and Dong Thap provinces, South Vietnam using multi-temporal Sentinel-1A (S1A) data. The data were processed through four steps: (1) data pre-processing, (2) constructing smooth time series VH backscatter data, (3) rice crop classification using random forests (RF) and support vector machines (SVM) and (4) accuracy assessment. The results indicated that the smooth VH backscatter profiles reflected the temporal characteristics of rice-cropping patterns in the study region. The comparisons between the classification results and the ground reference data indicated that the overall accuracy and Kappa coefficient achieved from RF were 86.1% and 0.72, respectively, which were slightly more accurate than SVM (overall accuracy of 83.4% and Kappa coefficient of 0.67). These results were reaffirmed by the government’s rice area statistics with the relative error in area (REA) values of 0.2 and 2.2% for RF and SVM, respectively.