Territorial Planning for Coastal Zones in Chile:The Need for Geographical-Environmental and Natural Risk Indicators for Spatial Decision Support Systems

Coastal zones are very dynamic and fragile environments, constituting a landscape ever more heterogeneous, fragmented and with increasing levels of complexity due to the changing relationship between man and nature. Integrated coastal zone management therefore requires detailed knowledge of the system and its components, based—to a large extent—on technical and scientific information. However, the information generated must be in line with the political requirements necessary for decision-making and planning. Thus the use of indicators to give a simplified view of the many components of the territory, and at the same time to provide important information about patterns or trends, becomes a tool of the utmost importance. These indicators can be understood as measurable characteristics of the environment, which facilitate comprehension of the processes occurring at different scales and serve as a reference to inform the population and support decision-making. The aim of the present note is to demonstrate briefly the need to develop geographical-environmental and natural risk indicators to facilitate comprehension of the dynamic of spatial and temporal landscape patterns, particularly in coastal environments. This approach offers an historical summary of the natural, socio-economic and political processes which currently make up the territory, and which without doubt will continue to influence it in the future. At the same time, it is proposed that information should be integrated on the basis of this framework with a view to generating spatial decision support systems in a context of planning and integrated management of the coastal zones of Chile.

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

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 decisionmaking 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 partitionrefinement 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 local spatial decision support system for developing countries based on MCA,fuzzy sets and OWA–case study of a municipality in Cuba

This paper presents a Spatial Decision Support System for local governments of developing countries.It allows municipality government,enterprises,scientific community and civil society to address decision problems using GIS.The framework is supported by four modules of information technologies:Environmental Decision Support Database,Data Manipulation,Decision Support,and Mapping.A case study is presented covering the implementation of this framework in one municipality of Cuba.An example of land suitability planning for coconut crops is used to evaluate the system performance and usability.Results show local municipalities are able to use this framework to solve local decision problems using state of the art decision making even with low infrastructure development.

A New Mathematical Framework and Spatial Decision Support System for Modeling Cascade Interdependency of Critical Infrastructure during Geo-Disasters

Critical infrastructures（CI） are designated sectors that if incapacitated or destroyed by natural disasters would have a serious impact on national security and economic and social welfare. Due to the interdependency of critical infrastructures failure of one infrastructure during a natural disaster such as earthquake or flood may cause failure of another and so on through a cascade or escalating effect. Quantification of these types of interdependencies between critical infrastructures is essential for effective response and management of resources for rescue, recovery, and restoration during times of crises. This paper proposes a new mathematical framework based on an asymmetric relation matrix constructed in a bottom-up approach for modeling and analyzing interdependencies of critical infrastructures. Asymmetric dependency matrices can be constructed using the asymmetric incidence coefficient based on node-level relationships defined between nodes for measuring the strength of interdependency between node and node, node and network, and networks and networks. These asymmetric matrices are further analyzed for ranking infrastructures in terms of their relative importance and for identifying nodes and infrastructure networks that play a critical role in chain effects among infrastructures involved in geo-disaster events such as flooding. Examples of interdependency analysis for the identification of vulnerabilities among fifteen national defense-related infrastructure sectors by the Australian government and a simulated example using the newly developed GIS-based network simulator Geo PN are used to validate and demonstrate the implementation and effectiveness of interdependency analysis methods in analyzing infrastructure interdependency during a flooding event.

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 multicriteria 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.

An ontology-based multicriteria spatial decision support system:a case study of house selection

The paper proposes an ontology-based multicriteria spatial decision support system(MC-SDSS)for the house selection problem.The house selection ontology serves as a foundation for spatial multicriteria decision analysis(MCDA)in the house selection domain.It is built using the Web Ontology Language(OWL).The ontology represents the spatial MCDA knowledge associated with house selection using semantic machine-interpretable concepts and relationships in such a way that they can be used by machines not just for display purposes,but also for processing,automation,integration,and reuse across applications.It contains concepts(or classes)including quantitative and qualitative criteria(objectives and attributes),decision alternatives(houses for sale),criterion weights,and location attributes of the decision alternatives.The concepts are organized into a hierarchical classification structure using the Analytic Hierarchy Process.To evaluate the decision alternatives,a set of rules is implemented within the OWL knowledge base with the Semantic Web Rule Language.The rules are expressed as combinations of the OWL concepts and their properties.The paper illustrates an implementation of the proposed ontology-based MC-SDSS architecture using a case study of house selection in the City of Tehran,Iran.

A cyberGIS-enabled multi-criteria spatial decision support system: A case study on flood emergency management

With the increased frequency of natural hazards and disasters and consequent losses,it is imperative to develop efficient and timely strategies for emergency response and relief operations.In this paper,we propose a cyberGIS-enabled multi-criteria spatial decision support system for supporting rapid decision making during emergency management.It combines a high-performance computing environment(cyberGIS-Jupyter)and multi-criteria decision analysis models(Weighted Sum Model(WSM)and Technique for Order Preference by Similarity to Ideal Solution Model(TOPSIS))with various types of social vulnerability indicators to solve decision problems that contain conflicting evaluation criteria in a flood emergency situation.Social media data(e.g.Twitter data)was used as an additional tool to support the decision-making process.Our case study involves two decision goals generated based on a past flood event in the city of Austin,Texas,U.S.A.As our result shows,WSM produces more diverse values and higher output category estimations than the TOPSIS model.Finally,the model was validated using an innovative questionnaire.This cyberGIS-enabled spatial decision support system allows collaborative problem solving and efficient knowledge transformation between decision makers,where different emergency responders can formulate their decision objectives,select relevant evaluation criteria,and perform interactive weighting and sensitivity analyses.

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

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 subinformation 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.

A Decision Support System for Spatial Analysis of Agricultural Production in Madagascar

In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Géomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.

Geographical Design of Riparian Buffers with Long-term Vegetation Cover Reconstructed in Agricultural Landscapes

Reconstructing long-term vegetation cover along streams has become a popular practice for ecological restoration in fragmented agricultural landscapes. To maximize ecological restoration benefits with the least cost, this paper developed a GIS- based model framework for the geographical design of the location and width of riparian buffers to be reconstructed with long-term vegetation cover. The framework integrated three models： the 0-1 mathematical programming model, an economical model and an ecological model. It was tested in an agricultural landscape with a drainage system consisting of 92 stream segments with cropland banks. Each segment had five restoration options in terms of buffer width： 0, 5, 10, 15 and 20 m, thus making a total of 460 decision units in the landscape. For each unit, the economical model estimated the annual rental payment to the farmer who owned the targeted cropland margin along a stream to be converted into a vegetation buffer, whereas the ecological model predicted its corresponding habitat benefits at the landscape level. The 0-1 programming model minimized the total payments, subject to the designed habitat improvement and proposed acreages of riparian cropland set-aside annually. The model identified a cost-effective combination of riparian buffers from 460 units. The results showed that achieving the habitat improvement goal at the least cost required a spatial configuration of vegetation buffers with variable width. This finding suggests that the size and location of buffers directly affect restoration costs and environmental benefits. Thus, the best management practices of agricultural landscape restoration can only be achieved by a specific geographical design with the model framework.

Gap analysis in decision support systems for real-estate in the era of the digital earth

Searching for a property is inherently a multicriteria spatial decision.The decision is primarily based on three high-level criteria composed of household needs,building facilities,and location characteristics.Location choice is driven by diverse characteristics;including but not limited to environmental factors,access,services,and the socioeconomic status of a neighbourhood.This article aims to identify the gap between theory and practice in presenting information on location choice by using a gap analysis methodology through the development of a sevenfactor classification tool and an assessment of international property websites.Despite the availability of digital earth data,the results suggest that real-estate websites are poor at providing sufficient location information to support efficient spatial decision making.Based on a case study in Dublin,Ireland,we find that although neighbourhood digital earth data may be readily available to support decision making,the gap persists.We hypothesise that the reason is two-fold.Firstly,there is a technical challenge to transform location data into usable information.Secondly,the market may not wish to provide location information which can be perceived as negative.We conclude this article with a discussion of critical issues necessary for designing a spatial decision support system for real-estate decision making.

Supporting integrative maritime spatial planning by operationalising SEANERGY – a tool to study cross-sectoral synergies and conflicts

With growing pressures on marine ecosystems and on marine space,an increasingly needed strategy to optimise the use of marine space is to co-locate synergic marine human uses in close spatial–temporal proximity while separating conflicting marine human uses.The ArcMap toolbox SEANERGY is a new,cross-sectoral spatial decision support tool(DST)that enables maritime spatial planners to consider synergies and conflicts between marine uses to support assessments of co-location options.Cross-sectoral approaches are important to reach more integrative maritime spatial planning(MSP)processes.As this article demonstrates through a Baltic Sea analysis,SEANERGY presents a crosssectoral use catalogue for MSP through enabling the tool users to answer important specific questions to spatially and/or numerically weight potential synergies/conflicts between marine uses.The article discusses to what degree such a cross-sectoral perspective can support integrative MSP processes.While MSP integrative challenges still exist,SEANERGY enables MSP processes to move towards developing shared goals and initiate discussions built on best available knowledge regarding potential use-use synergies and use-use conflicts for whole sea basins at once.

Multi-criteria land evaluation for suitability analysis of wheat:a case study of a watershed in eastern plateau region,India

Improper land use results in land degradation as well as decline in agricultural productivity.To obtain optimum benefit from the land,proper utilization of its resources is necessary.Land suitability analysis is the evaluation and grouping of specific areas of land in terms of their suitability for a defined use,which is a precondition for sustainable land use planning.This study investigated the applicability of Geographical Information System(GIS)techniques in combination with multi-criteria land evaluation for analysing land suitability.The study used the weighted overlay technique for multi-criteria evaluation with GIS for the assessment of suitability of wheat cultivation in Beko watershed(Purulia,India).The watershed area is moderately suitable for wheat crop production,with constraints like imperfect drainage and poor soil depth.

Short-term emergency response planning and risk assessment via an integrated modeling system for nuclear power plants in complex terrain

Short-term predictions of potential impacts from accidental release of various radionuclides at nuclear power plants are acutely needed, especially after the Fukushima accident in Japan. An integrated modeling system that provides expert services to assess the consequences of accidental or intentional releases of radioactive materials to the atmosphere has received wide attention. These scenarios can be initiated either by accident due to human, software, or mechanical failures, or from intentional acts such as sabotage and radioIogicaI dispersal devices. Stringent action might be required just minutes after the occurrence of accidental or intentional release. To fulfill the basic functions of emergency preparedness and response systems, previous studies seldom consider the suitability of air pollutant dispersion models or the connectivity between source term, disper- sion, and exposure assessment models in a holistic context for decision support. Therefore, the Gaussian plume and puff models, which are only suitable for illustrating neutral air pollutants in fiat terrain conditional to limited meteorological situations, are frequently used to predict the impact from accidental release of industrial sources. In situations with complex terrain or special meteorological conditions, the proposing emergency response actions might be questionable and even intractable to decision- makers responsible for maintaining public health and environmental quality. This study is a preliminary effort to integrate the source term, dispersion, and exposure assessment models into a Spatial Decision Support System （SDSS） to tackle the complex issues for short-term emergency response planning and risk assessment at nuclear power plants. Through a series model screening procedures, we found that the diagnostic （objective） wind field model with the aid of sufficient on-site meteorological monitoring data was the most applicable model to promptly address the trend of local wind field patterns. However, most of the hazardous materials being released into the environment from nuclear power plants are not neutral pollutants, so the particle and multi-segment puff models can be regarded as the most suitable models to incorporate into the output of the diagnostic wind field model in a modern emergency preparedness and response system. The proposed SDSS illustrates the state-of-the-art system design based on the situation of complex terrain in South Taiwan. This system design of SDSS with 3- dimensional animation capability using a tailored source term model in connection with ArcView~ Geographical Information System map layers and remote sensing images is useful for meeting the design goal of nuclear power plants located in complex terrain.