Web-based Spatial Decision Support System Research Articles

Web-based spatial decision support system for precision agriculture: A tool for delineating dynamic management unit zones (MUZs)

Precision agriculture (PA) is a farming management concept that aims to provide agronomic, economic, and environmental benefits. One of the fields of research in PA is the delineation of Management Unit Zones (MUZs). MUZs are the sub-division of fields featuring an inter-zonal variation delineated by agronomists for on-field PA operations. To develop MUZs, three factors typically need to be considered: input multi-dimensional data, procedures to process the information, and the optimal number of zones a field should be divided into. PA uses digital technologies to collect and analyze a large amount of data, outline MUZs, monitor crops, and carry out site-specific crop management. Web-based spatial decision support systems (WB-SDSS) can provide users with tools that ease the complex procedures for PA. The objective of this study is twofold: on the one hand, we developed a free and open source (FOSS) WB-SDSS to facilitate the implementation and use of such tools for delineating MUZs and monitoring crops; on the other, a MUZs outline procedure was developed based on Sentinel-2 and Planetscope time series data, and spatio-temporal dynamic clustering model using fuzzy c-means. Our study highlighted that the WB-SDSS might be a helpful solution for harmonizing data collected from different sources, easing the implementation and use of complex geospatial procedures for PA, and delineating MUZs. We tested the system on a particularly representative farm in the Emilia Romagna region (Northern Italy), with 512 hectares of durum wheat crops. Using the WB-SDSS, we quickly delineated homogeneous zones for 27 fields in the study area during the phenological cycle of durum wheat (November 2018-June 2019).

Development of web-based spatial decision support system using landslide hazard mapping outcomes: an example of GIS-based hazard assessment

Presently, the risk of natural hazards is continuously increasing which may cause noticeable casualties and destruction under the influence of climate change. Information regarding the hazard characteristics, capacity, susceptibility, and vulnerability in pre-disaster phases is critical in realizing efficient disaster management. There are numerous GIS-based hazard assessment studies have been done by researchers every year; however, most of their GIS-based outcomes have rarely been effectively used for supporting the decision-making processes in real situations. The objective of the study is to propose an appropriate way of using these GIS-based hazard assessment outcomes to develop a Web-based platform to effectively support the decision-making processes. The GIS-based hazard assessment outcomes from previous work are used in this study to develop a Web-based spatial decision support system as an example of practicing the proposed approach. Finally, there are 3 modules including general module, thematic single factor maps module, and results module have been designed and developed in the system. This approach provides a new way of making better use of all kinds of GIS-based hazard assessment outcomes, which can be used as an effective decision-making support tool. In addition, it can be used as a guideline for future research.

Effective medical center finding during COVID-19 pandemic using a spatial DSS centered on ontology engineering.

The global spread of the coronavirus has generated one of the most critical circumstances forcing healthcare systems to deal with it everywhere in the world. The complexity of crisis management, particularly in Iran, the unfamiliarity of the disease, and a lack of expertise, provided the foundation for researchers and implementers to propose innovative solutions. One of the most important obstacles in COVID-19 crisis management is the lack of information and the need for immediate and real-time data on the situation and appropriate solutions. Such complex problems fall into the category of semi-structured problems. In this respect, decision support systems use people’s mental resources with computer capabilities to improve the quality of decisions. In synergetic situations, for instance, healthcare domains cooperating with spatial solutions, coming to a decision needs logical reasoning and high-level analysis. Therefore, it is necessary to add rich semantics to different classes of involved data, find their relationships, and conceptualize the knowledge domain. For the COVID-19 case in this study, ontologies allow for querying over such established relationships to find related medical solutions based on description logic. Bringing such capabilities to a spatial decision support system (SDSS) can help with better control of the COVID-19 pandemic. Ontology-based SDSS solution has been developed in this study due to the complexity of information related to coronavirus and its geospatial aspect in the city of Tehran. According to the results, ontology can rationalize different classes and properties about the user’s clinical information, various medical centers, and users’ priority. Then, based on the user’s requests in a web-based SDSS, the system focuses on the inference made, advises the users on choosing the most related medical center, and navigates the user on a map. The ontology’s capacity for reasoning, overcoming knowledge gaps, and combining geographic and descriptive criteria to choose a medical center all contributed to promising outcomes and the satisfaction of the sample community of evaluators.

An intelligent web-based spatial group decision support system to investigate the role of the opponents’ modeling in urban land use planning

Urban land-use planning decisions generally require negotiation between multiple stakeholders to reach an agreement on a specific plan. Computer-aided tools such as group decision support systems can facilitate the actors in this complicated process. In the context of these systems, using software agents enhance the effectiveness and efficiency of group decision support. The software agents can perform some computational and analytical tasks on behalf of the stakeholders. In more advanced cases, the agents can also learn stakeholders’ preferences and behavior to help them make good decisions. This paper proposes an intelligent web-based spatial group decision support system to investigate the role of opponents modeling in urban land use planning by using a multi-agent system approach. For this purpose, two successive meetings are held in which the system is used: in the first meeting, the stakeholders revise the existing plans and respond to other stakeholders’ requests. During the meeting, software agents attempt to model the behavior of the stakeholders they are associated with, based on a Bayesian learning method in combination with social value orientation theory to describe stakeholders’ decision behavior in a group context. In the second meeting, the software agents help the stakeholders in the step of plan revision by providing the information obtained to the stakeholders. In an application, a comparison of the results of the meetings showed that the provided information about the opponents reduced the negotiation time and contributed to reaching a better spatial configuration of land-uses based on a criterion provided by social value orientation theory.

Wind farms selection using geospatial technologies and energy generation capacity in Gwadar

Pakistan has been a victim of energy crisis since last few decades. This energy crisis has adversely affected country’s socio-economic development and continues to do so. The continuously increasing demand–supply gap has negatively impacted the economic stability of the country. With the recent awareness and development of alternate energy resources like wind and solar, the current energy crisis can be minimized. However, proper planning is essential for successful execution of these renewable energy projects. This study aims to identify the suitable sites for wind farms in District Gwadar, Balochistan using Geographical Information Systems (GIS) and Web-based Spatial Decision Support System (SDSS). In this study, multi-criteria decision making is applied which assists breaking down the site selection complexity. Multi-Criteria evaluation methods provides different set of procedures that facilitate decision making by analyzing different alternatives. The underlying geospatial and ICT technologies used in this analysis form the core component of the planning process. Gwadar is currently drawing investor’s attention due to its geographical location, deep seaport, and proposed China–Pakistan Economic Corridor (CPEC). This research is useful for stakeholders of Wind Energy to explore the wind potentials using GIS as an interactive decision-making tool during the pre-feasibility stage.Furthermore, this research has considered the environmental, social and economic aspects during the decision-making process of wind farm development. This is the strength of multi-criteria evaluation as differently weighted scenarios provide different output, depending on the factors considered of highest importance. A detailed analysis of the sites in terms of their wind potential and energy generation capacity has also been reported in this study. This long coastline of Balochistan with huge wind energy potential has not been explored yet and therefore this study will assist researchers to further explore this area and can have a positive impact on CPEC.

A web-based spatial decision support system for monitoring the risk of water contamination in private wells

ABSTRACT Long-term exposure to contaminated water can cause health effects, such as cancer. Accurate spatial prediction of inorganic compounds (e.g. arsenic) and pathogens in groundwater is critical for water supply management. Ideally, environmental health agencies would have access to an early warning system to alert well owners of risks of such contamination. The estimation and dissemination of these risks can be facilitated by the combination of Geographic Information Systems and spatial analysis capabilities – i.e., spatial decision support system (SDSS). However, the use of SDSS, especially web-based SDSS, is rare for spatially explicit studies of drinking water quality of private wells. In this study, we introduce the interactive Well Water Risk Estimation(iWWRE), a web-based SDSS to facilitate the monitoring of water contamination in private wells across Gaston County, North Carolina (US). Our system implements geoprocessing web services and generates dynamic spatial analysis results based on a database of private wells. Environmental health scientists using our system can conduct fine-grained spatial interpolation on 1) a particular type of contaminant such as arsenic, 2) on various subsets through a temporal query. Visuals consist of an estimation map, cross validation information, Kriging variance and contour lines that delineate areas with maximum contaminant levels (MCL), as set by the US Environmental Protection Agency (EPA). Our web-based SDSS was developed jointly with environmental health specialists who found it particularly critical for the monitoring of local contamination trends, and a useful tool to reach out to private well users in highly elevated contaminated areas.

An Integrated Participative Spatial Decision Support System for Smart Energy Urban Scenarios: A Financial and Economic Approach

The decision-making process regarding heating supply system options in a district perspective is extremely challenging. This paper aims to present a new method to support urban energy decisions in real-time processes, which was developed in the context of a European project (DIMMER (District Information Modeling and Management for Energy Reduction, 2013–2016)). The method is composed of three parts: (i) a new web-based spatial decision support system (SDSS), called “Dashboard”; (ii) an ad hoc energy-attribute analysis (EAA) tool to be integrated into Dashboard; and (iii) a multi-criteria decision analysis (MCDA). In contrast to other SDSSs, one of the main strengths of Dashboard is the ability to acquire, store, and manage both geo-referenced and non-geo-referenced data, and perform real-time analyses of spatial problems taking into account a wide range of information. In this sense, Dashboard can formally visualize and assess a potentially infinite number of attributes and information, as it is able to read and process very large web databases. This characteristic makes Dashboard a very effective tool that can be used in real-time during focus groups or workshops to understand how the criterion trade-offs evolve when one, or several, decision parameters change. The paper describes the main procedure of the new method and testing of Dashboard test on a district in Turin (Italy).

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

ABSTRACTGeothermal 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.

SmartScape™: A web-based decision support system for assessing the tradeoffs among multiple ecosystem services under crop-change scenarios

Agricultural lands have experienced rapid changes during the last decade. In the absence of preventative crop change policies, these changes can affect multiple ecosystem services simultaneously. The objective of this paper is to describe a web-based spatial decision support system (SDSS), which we call the SmartScape™, that helps policymakers to evaluate the consequence of crop changes on various ecosystem services in agriculture landscapes. This paper specifically provides an overview of a newly developed SDSS architecture that: (1) integrates multiple open-source software tools to build a user-friendly web client; (2) integrates a variety of spatial and temporal data and environmental models, into an interactive environment to allow stakeholders with various interests to build crop change scenarios; and (3) allows stakeholders to evaluate and identify suitable crop change policies by visualizing the tradeoffs among multiple ecosystem services in a timely manner. We demonstrate the utility of this architecture through (4) an analysis of a crop change scenario for an agriculture-dominated landscape in Dane County, Wisconsin, USA. Assessment of participant feedback from potential users (group of stakeholders from Dane County as well as group of scientists who were experts in various disciplines, such as computer science, landscape ecology, agriculture, water quality, soil chemistry and climate change) reveals that this SmartScape™ is an effective tool to show the general consequences of various types of crop changes for developing effective crop changes policy in Wisconsin, USA.

Analyzing crop change scenario with the SmartScape™ spatial decision support system

Agricultural land use is increasingly changing due to different anthropogenic activities. A combination of economic, socio-political, and cultural factors exerts a direct impact on agricultural changes. This study aims to illustrate how stakeholders and policymakers can take advantage of a web-based spatial decision support system (SDSS), namely SmartScape™ to either test existing crop change policies or produce effective crop change decisions using tradeoff analysis. We addressed the consequences of two common crop change scenarios for Dane county in Wisconsin, United States, (a) replacing perennial energy crops with annual energy crops and (b) replacing annual energy crops with perennial energy crops. The results suggested that converting areas under grass and alfalfa production that were located on high quality soil and flat slope to corn promoted a net-income and availability of gross biofuel. Additionally, the model outcome proposed that converting areas under corn and soy production that were located on high slope to grass promoted net-energy, phosphorus loading, soil loss, soil carbon sequestration, nitrous oxide emission, grassland bird habitat, pollinator abundance, and biocontrol. Therefore, SmartScape™ can assist strategic crop change policy by comparing the tradeoff among ecosystem services to ensure that crop change policies have outcomes that are agreeable to a diversity of policymakers.

Coping with climate change: The role of spatial decision support tools in facilitating community adaptation

Climate change challenges communities to visualize spatial patterns of risk, assess their vulnerability to those risks, and prepare adaptation plans to lower vulnerability. This paper outlines the design and implementation of a prototype web-based spatial decision support system (SDSS), referred to as the Community Adaptation Viewer (CAV), to assist adaptation planning. Thin-client, Javascript enabled web-SDSS software was constructed to allow interaction with urban infrastructure, and support “on-the-fly” assessment of social and economic vulnerability. Facilitated, decision-making workshops were conducted with small groups of stakeholders to evaluate the effectiveness of the prototype. The test case illustrates that high levels of information integration are practical to achieve, and that the SDSS can significantly enhance the ability of communities to conduct elaborate, geographically-specific climate change adaptation planning. Given the long time frame required to fulfil some adaptation plans, it is crucial that communities begin to develop and invest in adaptation strategies as soon as possible.

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment.The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sites are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well.

Housing evaluation with web-SDSS in urban regeneration actions

Urban regeneration is increasingly a ‘universal issue’ and a crucial factor in the new trends of urban planning. It is no longer only an area for study and research, but it has become part of new urban and housing policies. Urban regeneration involves complex decisions as a consequence of the multiple dimensions of the problems such as special technical requirements, safety concerns, and socio-economic, environmental, aesthetic and political impacts, among others. This multi-dimensional nature of urban regeneration projects and the large capital investments required justify the development and use of state-of-the-art decision support methodologies to assist decision makers. This research focuses on the development of a multi-criteria approach for the evaluation of building conservation status in urban regeneration projects. This paper presents a web-based spatial decision support system (SDSS) to help decision makers in analysis of problems and in the definition of strategies and priorities of intervention. An example of an application to a real-world context is also presented.

SPATIAL ANALYSIS BASED HEALTH AND SAFETY RISK ASSESSMENT FOR LINEAR CONSTRUCTION PROJECTS

Abstract. This paper describes an on-going study that aims to develop a web-based spatial decision support system model for proactive health and safety management in linear construction projects. Currently, health and safety management is usually performed reactively instead of proactive management since hazard identification and risk assessment is mostly performed on paper based documents that are not effectively used at site. This leads to accidents and fatalities at construction sites. The proposed system automatically identifies the spatial risks according to the topographic and layout map of the site, project specification and health and safety regulations by means of spatial analysis. It enables the workers and management personnel to access the possible hazards and thematic risk map of any portion of the construction site for linear projects. Finally, the described approach provides the proposed mitigation measures for the identified hazards. The developed system is expected to raise awareness in H&S among workers and engineers, and increase participation of workers to health and safety management.

Environmental risk management with the use of multi-criteria spatial decision support system DECERNS

Environmental risk-based land management requires implementation of tools for spatial information analysis, problem-oriented models for assessment of risk values, and corresponding methods for decision-making support. A new framework decision evaluation in complex risk network systems (DECERNS) has been developed to address this class of problems. DECERNS is a web-based spatial decision support system (WebSDSS) for multi-criteria analysis of a wide range of spatially-distributed alternatives, including land-use planning and management. It integrates basic and advanced GIS functions with several multi-criteria decision analysis (MCDA) methods and tools. One of the features of the DECERNS WebSDSS is a capability to incorporate various generic and site-specific models for risk analysis and assessment of other decision criteria which are considered within a multi-criteria problem. This paper provides an overview of methods and tools used in DECERNS, emphasising the integration of models into the WebSDSS. Application of DECERNS for a case study on multi-criteria risk management for 137Cs contaminated land resulting from Chernobyl is presented.

Online Decision Support System of Used Car SelectionUsing K-Nearest Neighbor Technique

This paper, we present Decision Support Systems (DSS) for used car selection using k-nearest neighbor (k-NN) algorithm. This system presents a user-friendly web-based spatial decision support system aimed for selling vehicle. There are two functions that are searching using k-nearest neighbor algorithm, and searching in the database to find one or more matching datasets with the user query. For a web search query, records contain vehicle type, brand, model, year, size, prince and type of engine. By contrast, k-nearest neighbor was estimated from data normalized of the training data set. The result showed that (DSS) present highly effective and sustainable tools for searching vehicle. Before buying a car, user must get some information or study about what kind of car is suitable for them. Basically, the buyer who wants to buy a new car model can visit the showroom to get more information. In used car, some model is very old and out of the showroom. Moreover, nowadays, internet can be used to get the information. The web database is finding one or more matching datasets with the user query. In this system, user can query the records that are able to select the suitable car. By contrast, the Decision support system (DSS) is the method that will make decision according to the information or feed back that are key in by users.

A web-based spatial decision support system to enhance public participation in urban planning processes

Urban planning processes are complex and multidimensional and they require re-thinking of traditional approaches. One of the theories increasingly researched by urban planners is realisation of participatory planning to facilitate public participation. This approach, as an effective bottom-up method, should increase the capabilities of planners to solve urban problems by including the general public in the urban planning process. This paper proposes a framework for a Web-based spatial decision support system (WebGIS-SDSS) adjusted to a participatory urban planning approach. The framework, called Web-based participatory urban planning (WPUP), has been implemented in a case study. It offers a Web-based spatial forum to demonstrate how the proposed system can not only help citizens to share their idea regarding urban plans, but also help planners to implement applicable bottom-up and public participation decision-making theory in the urban planning process. WPUP supports the deliberative and analytic components of the collaborative spatial decision-making process. It facilitates inclusion of local knowledge in urban planning to complement traditional approaches. WPUP provides easy access to urban plans and decisions, improves communication among planners and public, involves citizens’ preferences on planning in a timely manner, and finally facilitates participatory planning approach.

A Web-based spatial decision support system for accessibility analysis—concepts and methods

The main aim of this paper is to describe the concept of the spatial decision support system (SDSS), which combines network analysis and spatial analysis of accessibility with an interactive Web-based map application. There are two main objectives of this research: (1) to assess the spatial variation of accessibility to certain services within the city area, based on the network analysis and (2) to share the results with potential users in the form of a Web application. The intended system can help people answer such questions as “Which part of the city has good access to primary schools and parks?” These questions involve a multi-criteria spatial analysis and can be asked by both citizens and local authorities. The accessibility analysis can help them take better decisions regarding location and accessibility. In this paper the concept of an open source Web-based SDSS is proposed. Its prototype is based on the GeoServer, which is used as a Web Map Service provider. The Web user interface is built using the ExtJS and the GeoExt frameworks with the OpenLayers as a main map client. Finally, a dynamic Styled Layer Descriptor, generated with a PHP script, is incorporated in order to create interactive and user-oriented maps.

Web-Based Spatial Decision Support System andWatershed Management with a Case Study

In order to maintain a proper balance between development pressure and water resources protection, and also to improve public participation, efficient tools and techniques for soil and water conservation projects are needed. This paper describes the development and application of a web-based watershed management spatial decision support system, WebWMPI. The WebWMPI uses the Watershed Management Priority Indices (WMPI) approach which is a prioritizing method for watershed management planning and it integrates land use/cover, hydrological data, soils, slope, roads, and other spatial data. The land is divided into three categories: Conservation Priority Index (CPI) land, Restoration Priority Index (RPI) land, and Stormwater Management Priority Index (SMPI) land. Within each category, spatial factors are rated based on their influence on water resources and critical areas can be identified for soil conservation, water quality protection and improvement. The WebWMPI has user-friendly client side graphical interfaces which enable the public to interactively run the server side Geographic Information System to evaluate different scenarios for watershed planning and management. The system was applied for Dry Run Creek watershed (Cedar Falls, Iowa, US) as a demonstration and it can be easily used in other watersheds to prioritize crucial areas and to increase public participation for soil and water conservation projects.

A web spatial decision support system for vehicle routing using Google Maps

This article presents a user-friendly web-based spatial decision support system (wSDSS) aimed at generating optimized vehicle routes for multiple vehicle routing problems that involve serving the demand located along arcs of a transportation network. The wSDSS incorporates Google Maps ™ (cartography and network data), a database, a heuristic and an ant-colony meta-heuristic developed by the authors to generate routes and detailed individual vehicle route maps. It accommodates realistic system specifics, such as vehicle capacity and shift time constraints, as well as network constraints such as one-way streets and prohibited turns. The wSDSS can be used for “what-if” analysis related to possible changes to input parameters such as vehicle capacity, maximum driving shift time, seasonal variations of demand, network modifications, and imposed arc orientations. Since just a web browser is needed, it can be easily adapted to be widely used in many real-world situations. The system was tested for urban trash collection in Coimbra, Portugal.