Spatial Decision Support System Research Articles

A time-based model and GIS framework for assessing hazardous materials transportation risk in urban areas

Every day, trucks carrying hazardous materials (hazmat) in a large and densely populated city expose public health risks to the residents of the city as well as risks to the economic assets in the area. In this paper, we introduce a new risk model that considers population exposure along a route and the duration of such exposure, the latter being variable due to the congested nature of road transportation in urban areas. We have developed a spatial decision support system (SDSS) for quantitative risk analysis and the calculation of minimum-risk paths as well as their visualization on digital maps. We illustrate the usage of our proposed model and SDSS via a case study using the real road network of Istanbul, Turkey, a large metropolitan area with more than 15 million residents. We analyze Istanbul's hazmat transportation risk profile using risk analysis techniques via our interactive Geographical Information Systems (GIS)-based decision support system. We then produce a risk map of the city and run several routing scenarios between selected hazmat shipment origins and destinations. Results suggest that the hazmat routes under the new model may not always match with how hazmat is usually transported, with an economic decision-making perspective, in an urban area. Our proposed approach provides decision makers with new insights into urban hazmat transportation and is likely to reduce the consequences of incidents with large impact on public health.

"We Live on Hope...": Ethical Considerations of Humanitarian Use of Drones in Post-Disaster Nepal

As international humanitarian assistance from governments and private donors continued to increase in recent years, the pace of growth, however, has slowed down [1]. For instance, in 2018, while USd17.0 billion out of USd28.1 billion funding was committed to UN-coordinated appeals, there was still a funding shortfall of USd11.1 billion, with only 61% of requirements met [1]. Against this backdrop, international organizations are in - creasingly implementing innovative solutions to respond the needs of affected communities [2], [3]. Many of these solutions involve the use of digital technologies, such as geographic information systems (GIS), robotics, spatial decision support systems, and unmanned aerial vehicles, also known as drones [4]. Although drones are not the first use of robotics in commercial and industrial settings, the humanitarian use of drones represents the first wave of robotics applied in the aid sector, and is representative of emerging technologies being used for humanitarian purposes [5]. Examples of successful drone use in this setting include the 2010 Haiti earthquake (damage inspection), 2012 Hurricane Sandy in the U.S.A. (epidemic prevention), 2013 Typhoon Haiyan in the Philippines (rescue logistics), the 2014 Ebola outbreak in West Africa (medical equipment delivery), and the 2015 Nepal earthquake - the site of this case study - when Nepal was stricken by one of the most devastating natural disasters in history, leaving the country with heavy burdens of immediate emergency relief and long-term postdisaster reconstruction [6]-[8].

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

ABSTRACT 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 seven-factor 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.

Planning and Managing the Integrated Water System: A Spatial Decision Support System to Analyze the Infrastructure Performances

The demand for water is constantly increasing, while there are factors related to climate change and pollution that make it less and less available. Addressing this problem means being able to face it with a global approach, which takes into account that human beings need water to survive, as well as all the systems on which they rely, namely sanitation, health, education, business, and industry. While human behavior is influenced by the growing awareness on this topic promoted by organizations specifically targeting this mission, the need to protect water resources in operational terms has led mainly to the need for smart urban infrastructure planning, consistent with the objective of promoting sustainable development. To this aim, the authorities in charge of monitoring the implementation of the investment plans by operators need to perform accurate evaluations of the technical quality of the services provided. The present paper introduces a framework to design a Multi-criteria Spatial Decision Support System, conceived to help decision-makers define and analyze the investment priorities of the individual service operators. By building a knowledge model of the network under investigation, decision-makers are aware of physical components of the whole system and are provided with an intervention priority index related to the network objects that could be affected by the planning action to be implemented.

Development of a spatial decision support system for land-use suitability assessment: The case of complex tourism accommodation in Greece

Land-use suitability assessment necessitates the analysis of multiple parameters as well as the compliance with the legal framework, the priorities, and the beliefs of all stakeholders involved in forming and implementing spatial policies. The approach followed in this paper is based on combining Ontologies, GIS and Object-oriented programming, to develop a SDSS capable of supporting decision-making in land-use planning. The applicability of the system is demonstrated using the case-study of a Greek island. The proposed approach promotes the integration of modern technologies into the processes of spatial planning and enhances the strong trend towards using the benefits of knowledge-management in decision-making.

The reintroduction of Castor fiber in Piedmont (Italy): An integrated SWOT-spatial multicriteria based approach for the analysis of suitability scenarios

The Castor fiber or Eurasian beaver can change its habitat by building dams and creating ponds. For this reason, Castor fiber is known as an “ecosystem engineer” for aquatic and riparian environments. Despite its ecological importance, at the beginning of the 20th century the population was reduced to only 1200 beavers in Europe and Asia, due to uncontrolled hunting. Recently, some reintroductions and translocations have partly re-established the population. In Italy, however, the beaver disappeared in the 16th century and no action has been taken despite the recommendation of the Council of Europe to perform a feasibility study.This research evaluates beaver reintroduction and identifies suitable areas in Italy and, in particular, in the Piedmont region. In order to achieve this, a SWOT analysis combined with a Spatial Multicriteria Analysis was performed. Firstly, the zoological and ethological aspects concerning this rodent were studied, as well as the historical reasons that led to its disappearance in Italy and near extinction in Eurasia. Secondly, Strengths, Weaknesses, Opportunities and Threats (SWOT) of the territory were identified for beaver reintroduction. The SWOT analysis was implemented, as the starting point for the spatial multicriteria analysis. Thirdly, the Multicriteria Spatial Decision Support System (MC-SDSS) was structured into two criteria, i.e. Potentials and Criticalities, representing the spatialization of strengths and weaknesses. The final result of the MC-SDSS is a map showing suitable areas for beaver reintroduction in Piedmont. This map is the weighted sum of the maps of criticalities and potentialities, performed through a set of GIS operations and weighted through a pairwise comparison of criteria by experts.The analysis was conducted for the Piedmont region, but the integrated approach and the set of criteria can also be applied in other regions. Moreover, this mixed-method approach takes into account the characteristics necessary for the choice of suitable beaver habitats and also includes economic and social aspects. Therefore, it is an improvement on the Habitat Suitability Index (HIS), generally used in reintroductions. The aspects considered in the analysis are fundamental for the future development of a shared action plan, which considers both technical and social motivations and acts for the long-term on a wide area.

Spatial Modeling Considering valley’s Shape and Rural Satisfaction in Check Dams Site Selection and Water Harvesting in the Watershed

Check dams in rural watersheds are useful and popular structures for rain or runoff water harvesting. This study investigates three combined approaches to check dam site selection. The approaches including (i) Spatial Multi-Criteria Evaluation (SMCE), (ii) satisfaction of rural as benefices or exploiters, and (iii) valley’s shape analysis in the Manshad-Yazd watershed located in the center of Iran. A criteria tree model was designed and groups of constraints and factors were used for the spatial decision-making model. Constraints and factors were standardized using Boolean and fuzzy logic, respectively. The factors were weighted based on expert opinions. The factor layers were overlaid for producing a site selection map. Until this stage, geographic information systems (GIS) operated as a spatial decision support system. The decision-making process was completed using valley’s shapes (profiles steepness and cross-sections width/depth10m Min = 4.7 and upstream, Max = 42.7 at downstream), and rural satisfactoriness approaches. The proposed approaches are suggested for rapid, satisfied, and precise mapping of the check dam in the watershed for water harvesting. It is recommended to study the method in watersheds by more various biophysics, socio-economic and valley’s shapes.

RETRACTED ARTICLE: Comparative analysis of spatial interpolation with climatic changes using inverse distance method

An ecological change on the planet the most flighty parameter is precipitation. It causes minor and real changes in the climatic changes. The time and space analyzed on the data and the spatial and temporal patterns are introduced in the required manner. For the unpredictable data to be predicted by using the spatial interpolation techniques. The major spatial interpolation methods are categorized based on the simple and complex mathematical modeling. Those studies involve interpolation techniques such as ordinary Krigging, inverse distance weighted (IDW), Spline, etc., Most of the techniques studied the hydrological modeling and deliver hydro mapping (Younghun Jung and Venkatesh Merwade 2015). Various techniques are used for the hydrological mapping. This study involved comparing the statistical interpolation with precipitation and temperature. The cumulative values in the dataset taken from the year 2001 to the year 2013 used in the study. The monthly and the yearly mean square value calculated using the spatial interpolation techniques (Dhamodarn and Shruthi 2016). The main objective of the study is to find the topographical features and provides high-resolution climate maps using mathematical modeling. In the result of comparing the above interpolation methods in the result will produce the high-resolution climate maps and generate the geographical patterns. Based on the study will produce climate change in the environment like disaster, flood, landslide. The comparative study of interpolation methods and mean variation can be resulted and used for the further implementation of spatial climatic condition and decision support system to the society. The area has undergone the study is Adyar river, situated in latitude 13.0012° N, Longitude 80.2565° E. Inverse Distance Weighted interpolation methods are analyzed by using the Geostatistical tool ArcGIS.

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.

A spatial decision support system for peatland fires prediction and prevention in Bengkalis Regency, Indonesia

A Spatial decision support system (SDSS) is an integrated computer-based system that can be used to support decision makers in addressing spatial problems through iterative approaches with functionality for handling both of spatial and non-spatial databases, analytical modelling capabilities, decision making support, as well as effective data and information presentation utilities. Previously, many studies have proven that this kind of decision support system is also useful in addressing wildfires problems effectively. Considering this technological advancement, this study is primarily aimed to develop a peatland fires management system by implementing the concept of SDSS. Developed system in this study is consisting of two separate sub-system, namely prediction and prevention sub-systems, which are then integrated into one whole working scheme using loose coupling method. Overall, it can be concluded that such integrated prediction and prevention system has various advantages. Firstly, it is useful to establish rapid coordination among involved stakeholders in deciding suitable approaches to prevent peatland fires. Secondly, promoting a more pro-active fire management system that is relied on predict-and-prevent approach. Thirdly, avoiding further delay on fires prevention while minimizing error in resources allocation. Lastly, this kind of decision support system can be rapidly updated following on-going technological and field situation developments.

A social assessment of forest resource based on stakeholders’ perception: an application in three Balkans rural areas

ABSTRACT : An inclusive and transparent participatory process in the Balkan region can facilitate information’s exchange between decision-makers and local community, and increase social acceptance of forest management outcomes. The study – developed in the “FOR Balkans” project – has two main objectives: stakeholders’ engagement in forest management scenarios’ development and implementation of a Spatial Decision Support System to enhance sustainable and multifunctional forest management. To achieve them, a face-to-face questionnaire survey was conducted in three study areas in the Balkans: Shkrel district (Albania), Rugova valley (Kosovo), Knjaževac municipality (Serbia). The questionnaire – provided as a digital application – was administered to a sample of stakeholders in each study area. Stakeholders’ opinions towards ecosystem services and forest management practices were investigated. Results show that in Rugova provisioning services are the most important ecosystem services, that can be enhanced through a greater use of wood residues for energy purposes. In Shkrel, stakeholders consider supporting services as the most important category of ecosystem services that they can be maintained and improved through the implementation of sanitary fellings. In Knjaževac, stakeholders emphasize cultural services’ importance, which can be enhanced by promoting mixed forests and improving recreational facilities.

Development of a land suitability model for citrus cultivation using GIS and multi-criteria assessment techniques in Antalya province of Turkey

Abstract Location selection for citrus orchards is an important topic in terms of sustainable agriculture policies, agricultural planning, and community. This study presents a model to evaluate land suitability for cultivation of citrus in Antalya Province of Turkey. The aim of this study is to provide a Geographical Information System-Multi Criteria Evaluation based spatial decision support system, taking into account the viewpoints of local citrus growers and experts. 13 exclusion criteria, 3 main evaluation criteria (13 sub-criteria), and 52 value ranges were determined for citrus land suitability analysis. Analytic Hierarchy Process was utilised to calculate the weights of evaluation criteria. Inverse Distance Weighting interpolation approach was used to estimate the values of meteorological parameters. Thematic maps were presented for each of the criteria and final suitability map was prepared using Weighted Overlay method in Geographic Information System environment. The final suitability thematic map showed that the suitable zones (1281.19 km2) for citrus cultivation were located in the coastal regions of Antalya province. The average temperature in the winter season was determined to be the most important sub-criteria for citrus cultivation, followed by elevation, the average temperature in the flowering period, land use capability, daily average sunshine time, annual average precipitation, proximity to irrigation ponds and dam lakes and others. Most of the cultivated citrus orchards often coincided with the appropriate sites presented as a result of the study, and most of these sites were generally classified as high and moderate suitable zones. This study will be an important and useful regional guideline in terms of agricultural land use planning, citrus orchards management and community.

A geospatial model for allocating potential urban–industrial zones in a desert: Case study Matrouh, Egypt

Planning for new urban–industrial communities in deserts is a main objective of the Egyptian government. Allocation of such communities should comply with both environmental protection and sustainable consumption of resources. The current study explores such approach, through mapping potential zones for new urban–industrial communities in Matrouh Governorate, Western Desert, Egypt. A spatial multidisciplinary approach has been adopted to facilitate zoning based on satellite data, spatial decision support systems and a geospatial model. Landsat 8, Shuttle Radar Topography Mission in addition to several thematic maps were input for the geospatial model. Three sub-models were created for three themes (visions), two of which were created using spatial multicriteria analysis (land resources and infrastructures), and the third sub-model, namely environmental protection, was created using a binary model. The analytical hierarchy process method was applied to assign relative weights for the resources theme, while the rank-sum method was used for the infrastructure theme. The three sub-models were aggregated to produce the suitability index for three zoning visions. Such index was classified and the highest three suitability values in each suitability index were extracted being the most optimum zones. Such zones are found in the northeastern part of the study area. The most optimum zones amounted to 23,863 km2, 47,707 km2 and 25,474 km2; equivalent to 14.8%, 29.7% and 15.9% for the first, second and third visions, respectively. The resultant maps can be used in site selection, allocation, decisions and for planning new urban communities.

Accessibility and site suitability for healthcare services using GIS-based hybrid decision-making approach: a study in Murshidabad, India

Healthcare accessibility and site suitability analysis is an elongated and complex task that requires evaluation of different decision factors. The main objective of the present study was to develop a hybrid decision-making approach with geographic information systems to integrate spatial and non-spatial data to form a weighted result. This study involved three-tier analyses for assessing accessibility and selecting suitable sites for healthcare facilities, and analysing shortest-path network. The first tier of analysis stressed the spatial distance, density and proximity from existing healthcare to find more deprived and inaccessible areas in term of healthcare facilities. The result revealed that spatial discrepancy exists in the study area in term of access to healthcare facilities and for achieving equal healthcare access, it is essential to propose new plans. Thus, require finding suitable sites for put forward new healthcare service, which was highlighted in the second tier of analysis based on land use land cover, distancing to road and rail, proximity to residential areas, and weighted overlay of accessibility as decision factors. Finally, in the third tier of analysis, the most suitable site among the proposed healthcare was identified using the technique for order of preference by similarity to ideal solution. The road network analysis was also performed in this study to determine the shortest and fastest route from these healthcare facilities to connect with district medical hospital. The present study found some suitable sites throughout the district on inaccessible zones where people are deprived from better healthcare facilities. This attempt will highly helpful for preparing a spatial decision support system which assists the health authorities regarding the healthcare services in inaccessible, underprivileged, and rural areas.Electronic supplementary materialThe online version of this article (10.1007/s41324-020-00330-0) contains supplementary material, which is available to authorized users.

PoleSat_2018: an optimized, automated, geomatics IT tool based on a gravitational model: strategic decision support in hospital catchment area planning

In France and elsewhere, decision-makers, healthcare professionals and health planners need to better understand and specify the provision of medical care. To this end, a hospital-based research project on a gravitational health planning modelling process was initiated in 2002. Since then, geomatics has emerged as a major scientific field for facing new challenges in medical informatics and health planning, thanks to the use of attractive interfaces, new methods and user-friendly IT technologies. Our initial 2002 model has recently been enhanced, optimized and automated as part of a spatial decision support system (PoleSat_2018). These decisive improvements and optimizations were mainly based on Delaunay triangulation, the replacement of human expertise with a heuristic dominance rule that provides a complete automated algorithm, and an online graphical user interface. Rapid, easy planning scenarios (by grouping and/or closing hospitals) give a quasi-instantaneous, strategic visualization of hospital catchment areas for decision-makers who are not experts in geomatics via ready-to-use maps and spreadsheets. This new implementation achieves our main objective, since the proposed deterministic method provides a completely automated, stable algorithm. A custom version of this tool is now being used by the French Ministry of Health for real planning issues. Consequently, PoleSat could be easily generalized as a prospective, strategic decision support tool for various health planning issues.

A spatial decision support system for enhancing resilience to floods: bridging resilience modelling and geovisualization techniques

Abstract. In the context of climate change and increasing urbanization, floods are considerably affecting urban areas. The concept of urban resilience may be an interesting means of responding to urban flood issues. The objective of this research is to propose a spatial decision support tool based on geovisualization techniques and a resilience assessment method. The goal is to localize the level of resilience modelled in different territories. The methodology proposed consists of integrating three resilience indicators applied to a case study in Avignon (Provence-Alpes-Côte d'Azur region, France) and the use of geovisualization techniques: using GIS for data processing and analysis, visualization, mapping, and model processing. The methodology integrates decision-making by identifying characteristics capable of improving urban resilience and facilitating its understanding using a visual tool. The results demonstrate the usefulness of modelling resilience using geovisualization techniques to identify the potential for local resilience; integrate local stakeholders into a process of clarifying the concept through the contribution of visualization; and consider easier access to this concept based on data analysis, processing and visualization through the design of maps.

A Method of Navigational Information Display Using Augmented Virtuality

The preliminary research experiments described herein were aimed to choose an appropriate mixed reality technology for the construction of navigational information display method to be used onboard ships in restricted waters. The method assumes a possibly faithful representation of the environment and the actual navigational situation on a spatial decision support system (SDSS) interface during ship navigation and maneuvering in restricted waters. The paper also presents the architecture and process of building a SDSS, where the method of navigational information display using augmented virtuality was applied.

User Stories-Based Requirement Elicitation for Data Visualization to Support Decision Making in Water Resource Management at Bago River Basin

Understanding of system requirements that satisfy end users’ needs is fundamental of system development, yet challenging when end users are unable to address their needs explicitly. Although a number of scholars have been designing and applying requirement elicitation techniques, there is a research gap in Spatial Decision Support System (SDSS) with Web-based Geographical Information System (Web-GIS) in water resource management for disaster risk reduction. The gap addresses especially design elicitation techniques and their performances 1) to understand data types used for decision making, 2) set timing for sharing the data to accomplish end users’ tasks, and 3) compile the data to be represented so as to facilitate end users’ decision making. This study therefore designed a requirement elicitation technique by advancing User Story Mapping (USM) and validated through a workshop using mock-up system interface with potential end users who are in charge of water resource management in Myanmar’s Bago River Basin. Through the research it could be validated that the user stories-based approach enabled end users to decompose their operation activities into tasks. It also allowed them to link to necessary data with visual image for facilitating their task accomplishments and decision making for water resource management. It was revealed that the benefits of using the designed approach are not only just to summarize necessary data and information for end users’ decision making but also to encourage them to proactively consider data utilization into their operations. For further development of the requirement elicitation to understand end users needs, insights and recommendations for the proposed technique designing and conducting of the workshop were obtained.

Development of a Spatial Decision Support System for Real-Time Flood Early Warning in the Vu Gia-Thu Bon River Basin, Quang Nam Province, Vietnam.

Vu Gia-Thu Bon (VGTB) river basin is an area where flash flood and heavy flood events occur frequently, negatively impacting the local community and socio-economic development of Quang Nam Province. In recent years, structural and non–structural solutions have been implemented to mitigate damages due to floods. However, under the impact of climate change, natural disasters continue to happen unpredictably day by day. It is, therefore, necessary to develop a spatial decision support system for real-time flood warnings in the VGTB river basin, which will support in ensuring the area’s socio-economic development. The main purpose of this study is to develop an online flood warning system in real-time based on Internet-of-Things (IoT) technologies, GIS, telecommunications, and modeling (Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center’s River Analysis System (HEC–RAS)) in order to support the local community in the vulnerable downstream areas in the event of heavy rainfall upstream. The structure of the designed system consists of these following components: (1) real-time hydro-meteorological monitoring network, (2) IoT communication infrastructure (Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), wireless networks), (3) database management system (bio-physical, socio-economic, hydro-meteorological, and inundation), (4) simulating and predicting model (SWAT, HEC–RAS), (5) automated simulating and predicting module, (6) flood warning module via short message service (SMS), (7) WebGIS, application for providing and managing hydro-meteorological and inundation data, and (8) users (citizens and government officers). The entire operating processes of the flood warning system (i.e., hydro-meteorological data collecting, transferring, updating, processing, running SWAT and HEC–RAS, visualizing) are automated. A complete flood warning system for the VGTB river basin has been developed as an outcome of this study, which enables the prediction of flood events 5 h in advance and with high accuracy of 80%.

Urban Flood Risk Assessment in Sidoarjo, Indonesia, Using Fuzzy Multi-Criteria Decision Making

Indonesia is very vulnerable to flooding due to urbanization of land use, industrialization and made worse by climate change. Sidoarjo is an urban area that frequently experiences regular flooding every year. The flooding break up local traffic, disrupting economic distribution and transportation routes. Minimum information about areas that are often flooded causes a lack of people and government attention to the effects of floods. In this paper, we develop a Fuzzy approach to determine the level of urban flood risk in Sidoarjo. The parameters consist of flood inundation, rainfall, population affected, and drainage. The Fuzzy sets produce fuzzy membership values, and evaluation rules determine the level of flood disaster in each village in Sidoarjo, classified into three levels of vulnerability, they are high, medium and low level of flood vulnerability. Analysis of the results of the calculation of flood risk assessment with Fuzzy multi-criteria decision making (FMCDM) shows a good result with accuracy of 66% compared to the analysis of the Sidoarjo Regional Disaster Management Agency inundation data. However, in reality flood risk is not only caused by inundation factor, the FMCDM method is represented a better assessment in real world. The spatial decision support system using geographical information systems (GIS) provides effective, efficient and useful in flood risk management for local and national governmental agencies.