Spatial Decision Problems Research Articles

Performing of spatial hydro-geomorphology analysis to detect the potential flood susceptibility in kr. keureuto watershed using ahp-mcdm approach

Flood is one of the most destructive natural disasters that causes loss of lives, properties, and significant resources, repeatedly occurring throughout Aceh, particularly in North Aceh. Given the more frequent floods and their damaging effects, it appears urgent and crucial to enhance the identification and mapping of flood susceptibility. One method that has been developed is the flood susceptibility mapping method. However, this method cannot address the challenges of flood susceptibility zone delineation due to the uncertainty of evaluation processes and the complex nonlinear relationships between indicators and risk levels, given that flood mapping is a multi-criteria spatial decision problem requiring hydrologic and geographic information. The objectives of this research are to assess flood susceptibility using the AHP-MCDM and to integrate using GIS to produce flood susceptibility map in Kr. Keureuto Watershed. Seven criteria from hydrologic and geographic information of the watershed were collected and analyzed using ArcGIS, and the weight of criteria using AHP from 25 expert responders. The results shows that there are four distinct levels of flood susceptibility: very high, high, medium, and low vulnerable. Significantly, the downstream Kr. Keureuto watershed emerges as highly susceptible to flooding, compared to the upstream zone.

Integrating GIS and location modeling: A relational approach

AbstractPlanners and geospatial analysts have long been using GIS and optimization methods to solve a wide range of spatial decision problems from routing and facility location to political redistricting. However, there has been a notable disconnection between the tools of GIS and optimization, constraining the capability of spatial decision‐making in GIS. This article presents relational linear programming (RELP), a new framework and tool for bridging the gap between the two fields by integrating a generic optimization solver into GIS: a solver for integer linear programming (ILP). In particular, we choose relational/spatial databases as the GIS platform. We demonstrate that not only data, but also programs for spatial problems (in the form of ILP) can be managed and executed in SQL inside spatial databases. The main focus of this article is on location modeling, and we show how classic models can be formulated succinctly in a declarative way using SQL. The declarative approach of RELP allows researchers to focus on formulating new spatial decision problems without being bogged down in sophisticated programming. The integrated approach allows data processing and decision‐making in one language. Therefore, it brings the power of location modeling to non‐specialist GIS practitioners.

Some theoretical notes on spatial discounting

Spatial discounting is a largely underexplored area of decision-making research, both theoretically and empirically, especially when compared to intertemporal choice, which has received significant attention in psychology and animal behaviour. Spatial decision problems seem to share some of the same features of a temporal decision problem (namely, the risk of reward objects disappearing and the opportunity cost of waiting), but there are several additional factors that affect the appropriate discount function for distant rewards. These include more significant opportunity costs, changes in the distances to all the other available opportunities, the post-reward costs of getting back home, the complex energetics associated with locomotion and all the additional risks faced by travelling itself. This paper organises and explores these factors and suggests some normative models that should predict the adaptive behaviour of animals and humans.

Analitik Hiyerarşi Prosesi (AHP) ve Coğrafi Bilgi Sistemleri (CBS) kullanılarak Osmaniye'deki Rüzgar Enerjisi Santrallerinin (RES) Yatırımına Uygun Alanların Belirlenmesi

Renewable energy sources are considered as clean energy sources. They have a much lower environmental impact than other energy sources. Among the renewable energy sources, the wind is an important energy source. In many countries the wind power production is so popular and many alternative research techniques related to wind energy are applied. Wind energy comes to the forefront today due to the increasing population of countries and the increase in energy needs. In our country the studies about the renewable energy has evolved rapidly over the past decade. The cost of initial installation of Wind Energy Plants (WEP) is high and they can only be installed if certain conditions are met. Site selection for wind turbine installation is not a technical process only, also a complex process is necessary for involving social, economic, physical and environmental sanctions. Therefore, site selection of wind energy plants is a very complex spatial decision problem for decision makers. For the different site selection studies multi criteria evaluation methods are often used. In the study, potential WEP investment areas of Osmaniye province were determined by using, Geographical Information Systems (GIS), Analytic Hierarchy Process (AHP) method and remote sensing. The criteria selected according to the general characteristics of the study area were combined with ArcGIS software using the weight values obtained with AHP and suitable areas for the WEP installation were determined. The land suitability index maps for the WEP siting is created in the ArcGIS program. The weighted Sum analysis of the Spatial Analyst Tool is used for this purpose. According to the results, 14.30% of the study area are suitable, 15.84% are moderate suitable and 69.86% are not suitable for wind energy plant siting

Toward building a 3D Web-based spatial decision framework for apartment selection

In the last few decades, there has been a growing interest in effectively incorporating the analytic modeling capabilities of decision support systems and the spatial modeling capabilities of geospatial information systems to solve complex spatial decision-making problems in various fields. Spatial decision support systems assist decision makers in exploring, structuring, and generating solutions for complicated spatial decision problems such as apartment selection. The selection of an apartment is a decision which plays an important role in human life. The good location is the critical factor that affects the value and potential of a real estate. This emphasizes the significance of spatial factors in decision making in real estate business. The spatial accessibility value of each apartment to different service categories can be used while choosing the most suitable apartment. Hence, the study covers not only non-spatial aspects, for example, unit price, house size, and number of rooms, but also spatial aspects, such as spatial accessibility, of the apartment selection. To sum up, this study proposes a spatial decision framework, called EMEKLI, to facilitate the decision-making process for the selection of an apartment in the presence of different priorities and uncertainties among the decision criteria. Furthermore, the recommendations obtained from the decision-making process are shared with the decision makers in the 3D environment through a virtual globe.

COMPARISON OF TOPSIS AND VIKOR MULTI CRITERIA DECISION ANALYSIS TECHNIQUES

Nowadays, beside Geographical Information Systems (GIS) analysis capabilities, Multi Criteria Decision Analysis (MCDA) techniques have been applied to a large amount of spatial decision problems. MCDA techniques are widely used in different kind of site suitability analysis in the field of environmental, engineering, topographical, social and economic perpectives. When planners are giving decision to related problems, there are limitations, expectations and requirements are involved in this stage. Right decision giving require to characterize the complex criteria structure and select appropriate data. The most used MCDA techniques in GIS are Analytical Hierarchy Process (AHP), The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR). In this study, TOPSIS and VIKOR techniques are compared to each other according to the models and capabilities.

Spatial multi-attribute decision analysis: Axiomatic foundations and incomplete preference information

This paper advances the theoretical foundations and the methodology of spatial decision analysis in which multi-attribute consequences of decision alternatives vary over a spatial region. First, we introduce necessary and sufficient conditions for representing the decision maker’s preferences among such decision alternatives with an additive spatial value function. This new axiomatization allows for the representation of preferences when the spatial region consists of an infinite number of locations, which is often the case in practical applications. Moreover, we show that spatial value functions suggested in the existing literature can be interpreted as special cases of our additive spatial value function. Second, motivated by the high effort required to elicit preferences in spatial decision problems, we develop a method for utilizing the additive spatial value function with incomplete preference information about spatial weights describing the importance of locations and attribute weights. This method provides defensible decision recommendations through the use of dominance concepts and decision rules. The applicability of the developed value function and analysis method is illustrated with a real-life application in air defense planning.

A multi-criteria evaluation approach in navigation technique for micro-jet for damage & need assessment in disaster response scenarios

In a disaster response situation, Unmanned Aerial Vehicle (UAV) can be an effective medium for the assessment of damages/needs of affected regions through the collection of situational information in the form of texts, audio-visuals, images etc. Through field deployment in disaster response situations, it is challenging to determine the navigation route for a UAV to cover the appropriate shelter points within its allocated flight time due to the energy constraints. Besides, it is a very arduous task to predict the favorable weather conditions and data-rate through the actual deployment of UAVs in post-disaster situations. In this paper, a novel navigation technique for micro-jet has been designed based on the spatial data. The navigation technique has been thought of as a spatial decision problem which has further been solved systematically by means of Multi-Criteria Decision Making (MCDM) technique. A Multi-Criteria Evaluation Technique has been adopted for effective transformation of spatial and calibration parameters into meaningful decisions. The navigation path has been obtained dynamically based on the solution of the spatial decision problem. This decision problem utilizes the parameters likes wind speed, wind direction, remaining flight time, the distance between the neighboring Shelter Points, the volume of data to be transferred etc. From the simulations, it has been analyzed that the newly proposed navigation technique can significantly improve the flight time of micro-jet by consuming less energy. The proposed approach has a prolonged flight duration and consumes less energy compared to the previously proposed techniques i.e. MIN_ROUTE and ROUTE_PRIORITY for different variations of wind speed and wind direction. Two field trials at different venues have been conducted using a customized micro-jet (equipped with a Single Board Computer with 2.4 GHz Wi-Fi connectivity) to analyze, (a) optimal altitude for navigation route at which data transfer rate would be maximum, (b) performance in terms of flight path calibration parameters of micro-jet, data transfer rate and the volume of data transfer while implementing the navigation route generated during simulation at the optimal altitude for a particular wind speed and wind direction. It has been observed that (1) in the initial deployment, at an altitude of 55 meters, for the wind speed 3 m/s and wind direction towards south the highest data rate of 154.51 KBps has been achieved, (2) in the subsequent field trial, during navigation the highest data rate of 942.08 KBps, at 50–55 meters altitude at wind speed of 1.66 m/s and with the wind direction towards north-east, has been achieved.

Development of a web graphic model with fuzzy-decision-making Trial and Evaluation Laboratory/Multi-criteria-Spatial Decision Support System (F-DEMATEL/MC-SDSS) for sustainable planning and construction of rural housings

There is often a complicated process for planning and constructing rural housings under the influence of (mass)-tourism in reservoir areas, involving multiple evaluation criteria use and geographical information analysis. With some methodologies within a unique framework considering current increasing construction sprawls and ecological consequences, these approaches will overcome existing shortcomings, especially spatial decision and visual impact problems on sustainable rural housing planning and construction. This paper presents a distinct web-based graphic model of sustainable rural housing planning and construction with a Fuzzy-DEcision-MAking Trial and Evaluation Laboratory/Multi-Criteria-Spatial Decision Support System (F-DEMATEL/MC-SDSS) method in a Geographic Information System (GIS) environment applied to Alange, Spain as a case study. The aim of this methodology is to optimally eco-design rural housings under (mass)-tourism in reservoir areas, as for their sensitivity and effect. The methodology presents herein the combined method of GIS and Multi-Criteria Decision Aid (MCDA) together with F-DEMATEL method. Because of the technological improvements in the area of information systems, it has a great necessity to study in what way to combine GIS, MCDA, Weighted Linear Combination (WLC), sensitivity analysis, the Internet, modeling, and database, targeting to generate MC-SDSS based on a web-based platform. A methodological framework named as web-based F-DEMATEL/MC-SDSS is suggested by means of a totally united GIS and definite MCDA model by programed in ArcGIS software’s Visual Basic for Applications (VBA) and Model View Controller (MVC) to be an object-oriented system. These program languages interact on an algorithmic web server that processing the MCDA products. The model consists of four main modules: the general overview module, the F-DEMATEL/MC-SDSS module, the sensitivity analysis module, and, finally, the final result module especially with the buildings suitability option, which users can access consecutively. Through the web graphic model developed, seven rural housings constructed in the area can be checked their suitability based on the selected criteria of decision-makers. Therefore, the results can be used to verify sustainable housings’ sites and designs differentiated parts of space as the asynchronous process of decision-makings. Thus, this model can be a channel to collaborate and communicate the spatial design and visual impact strategies of sustainable housings for decision-makers, who have practical and specific purposes.

Risk assessment of coal mining above confined aquifer based on maximizing deviation in a GIS environment

Accidents in coal mining may lead to personnel fatalities, economic losses, and delayed production, and safety has long been a primary concern in coal mining. So, decision-making in coal mine safety is important. In this study, with respect to multicriteria decision-making problems associated with geographic space, based on maximizing deviation, a decision model is established to evaluate safety of coal mining above confined aquifer. Then, a weighted linear combination operator composed of geographic space information which corresponds to each criterion has been established in a geographic information system (GIS) environment. The decision model is demonstrated by using the data from the Xiegou Coal Mine in Shanxi Province, China. The result indicates that an optimization model needs to be established when the information on the criteria weight is completely unknown. However, the safety of mining is affected by faults as there is a complicated geological structure in the coal mine. Then, another optimization model needs to be proposed, in which the active participation of decision-makers (experts) is included. The weights of criteria need to be limited within a certain range in accordance with the judgement of the decision-makers. This new decision model is effective and advantageous in dealing with spatial decision problems in coal mine safety, since the completely unknown weight information can be considered, but the weights of criteria which are limited within a certain range in accordance with the preference of the decision-makers (experts) are also considered.

Design and development of a generic spatial decision support system, based on artificial intelligence and multicriteria decision analysis

A new integrated and generic Spatial Decision Support System (SDSS) is presented based on a combination of Artificial Intelligence and Multicriteria Decision Analysis techniques. The approach proposed is developed to address commonly faced spatial decision problems of site selection, site ranking, impact assessment and spatial knowledge discovery under one system. The site selection module utilises a theme-based Analytical Hierarchy Process. Two novel site ranking techniques are introduced. The first is based on a systematic neighbourhood comparison of sites with respect to key datasets (criterions). The second utilises multivariate ordering capability of one-dimensional Self-Organizing Maps. The site impact assessment module utilises a new spatially enabled Rapid Impact Assessment Matrix. A spatial variant of General Regression Neural Networks is developed for Geographically Weighted Regression (GWR) and prediction analysis. The developed system is proposed as a useful modern tool that facilitates quantitative and evidence based decision making in multicriteria decision environment. The intended users of the system are decision makers in government organisations, in particular those involved in planning and development when taking into account socio-economic, environmental and public health related issues.

The value of information for correlated GLMs

We examine the situation where a decision maker is considering investing in a number of projects with uncertain revenues. Before making a decision, the investor has the option to purchase data which carry information about the outcomes from pertinent projects. When these projects are correlated, the data are informative about all the projects. The value of information is the maximum amount the investor would pay to acquire these data.The problem can be seen from a sampling design perspective where the sampling criterion is the maximisation of the value of information minus the sampling cost. The examples we have in mind are in the spatial setting where the sampling is performed at spatial coordinates or spatial regions.In this paper we discuss the case where the outcome of each project is modelled by a generalised linear mixed model. When the distribution is non-Gaussian, the value of information does not have a closed form expression. We use the Laplace approximation and matrix approximations to derive an analytical expression to the value of information, and examine its sensitivity under different parameter settings and distributions. In the Gaussian case the proposed technique is exact. Our analytical method is compared against the alternative Monte-Carlo method, and we show similarity of results for various sample sizes of the data. The closed form results are much faster to compute. Model weighting and bootstrap are used to measure the sensitivity of our analysis to model and parameter uncertainty. A general guidance on making decisions using our results is offered.Application of the method is presented in a spatial decision problem for treating the Bovine Tuberculosis in the United Kingdom, and for rock fall avoidance decisions in a Norwegian mine.

GIS BASED DECISION SUPPORT SYSTEM FOR SEISMIC RISK IN BUCHAREST. CASE STUDY – THE HISTORICAL CENTRE

Because of the increasing volume of information, problem decisions tend to be more difficult to deal with. Achieving an objective and making a suitable decision may become a real challenge. In order to better deal with decision making, decision support systems (DSS) have been developed. The decision support systems (DSS) can be used in any kind of a decision-making process and are very suitable in situations that involve a lot of stakeholders and a large number of criteria. DSS offers support in the decision-making process (<em>how</em> a decision should be made), and it does not focus on the result (<em>what</em> decision that should be made). DSS can also involve a large number of stakeholders and criteria, in the same time. A limitation of this method is that, regardless of the mathematical results, the final decision has to be made by the decision maker. Depending on the nature of the decision problem, a decision maker can use decision support systems (DSS), if the decision problem is economic or technical, and spatial decision support systems (SDSS), if the decision maker is faced with a spatial decision problem. The main objective of the present study is to apply a spatial decision support system in order to find a suitable shelter in the historical centre of Bucharest City in the post-disaster phase, in case of an earthquake occurrence. The present work represents a first step in applying SDSS in the context of the seismic risk in Bucharest. For the present paper, the SMCE Module for ILWIS 3.4 was used. The method included the following steps: structuring the problem in a decision tree, applying standardization and weighting methods to the criteria, finding suitable alternatives and choosing one of the alternatives. The results show that several buildings can be used as a shelter and among these are ‘Creditul Roman’ Bank Palace, the National History Museum and the National Bank of Romania.

Real-time collaborative GIS: A technological review

Collaborative Geographic Information Systems (CGIS) have become an important research area over the past two decades. This paper provides a critical review of the development of real-time CGIS, which is a branch under Collaborative GIS study. A real-time CGIS system provides a multi-user, real-time collaborative work environment, i.e., what you see is what I see (WYSIWIS), for spatial decision support and problem solving. The research about this kind of system has mainly focused on system architecture and modelling, collaborative awareness, concurrent control, collaborative behaviour modelling and other related key issues. The paper presents a two-stage historic development process of real-time CGIS, summarizes major research progress and representative developments by analysing their key technical issues, and based on the review discusses some research problems that need to be solved and some future research directions.

GIS BASED DECISION SUPPORT SYSTEM FOR SEISMIC RISK IN BUCHAREST. CASE STUDY – THE HISTORICAL CENTRE

Because of the increasing volume of information, problem decisions tend to be more difficult to deal with. Achieving an objective and making a suitable decision may become a real challenge. In order to better deal with decision making, decision support systems (DSS) have been developed. The decision support systems (DSS) can be used in any kind of a decision-making process and are very suitable in situations that involve a lot of stakeholders and a large number of criteria. DSS offers support in the decision-making process (how a decision should be made), and it does not focus on the result (what decision that should be made). DSS can also involve a large number of stakeholders and criteria, in the same time. A limitation of this method is that, regardless of the mathematical results, the final decision has to be made by the decision maker. Depending on the nature of the decision problem, a decision maker can use decision support systems (DSS), if the decision problem is economic or technical, and spatial decision support systems (SDSS), if the decision maker is faced with a spatial decision problem. The main objective of the present study is to apply a spatial decision support system in order to find a suitable shelter in the historical centre of Bucharest City in the post-disaster phase, in case of an earthquake occurrence. The present work represents a first step in applying SDSS in the context of the seismic risk in Bucharest. For the present paper, the SMCE Module for ILWIS 3.4 was used. The method included the following steps: structuring the problem in a decision tree, applying standardization and weighting methods to the criteria, finding suitable alternatives and choosing one of the alternatives. The results show that several buildings can be used as a shelter and among these are ‘Creditul Roman’ Bank Palace, the National History Museum and the National Bank of Romania.

Application of a Spatial Intelligent Decision System on Self-Rated Health Status Estimation

Self- assessed general health status is a commonly-used survey technique since it can be used as a predictor for several public health risks such as mortality, deprivation, and fear of crime or poverty. Therefore, it is a useful alternative measure to help assessing the public health situation of a neighborhood or town, and can be utilized by authorities in many decision support situations related to public health, budget allocation and general policy-making, among others. It can be considered as spatial decision problems, since both data location and spatial relationships make a prominent impact during the decision making process. This paper utilizes a recently-developed spatial intelligent decision system, named, Spatial RIMER(+), to model the self-rated health estimation decision problem using real data in the areas of Northern Ireland, UK. The goal is to learn from past or partial observations on self-rated health status to predict its future or neighborhood behavior and reference it in the map. Three scenarios in line of this goal are discussed in details, i.e., estimation of unknown, downscaling, and predictions over time. They are used to demonstrate the flexibility and applicability of the spatial decision support system and their positive capabilities in terms of accuracy, efficiency and visualization.

Decision Support Systems for environmental management: A case study on wastewater from agriculture

Dealing with spatial decision problems means combining and transforming geographical data (input) into a resultant decision (output), interfacing a Geographical Information System (GIS) with Multi-Criteria Decision Analysis (MCDA) methods. The conventional MCDA approach assumes the spatial homogeneity of alternatives within the case study area, although it is often unrealistic. On the other side, GIS provides excellent data acquisition, storage, manipulation and analysis capabilities, but in the case of a value structure analysis this capability is lower. For these reasons, several studies in the last twenty years have given attention to MCDA-GIS integration and to the development of Spatial Decision Support Systems (SDSS). Hitherto, most of these applications are based only on a formal integration between the two approaches. In this paper, we propose a complete MCDA-GIS integration with a plurality of MCDA methodologies, grouped in a suite. More precisely, we considered an open-source GIS (GRASS GIS 6.4) and a modular package including five MCDA modules based on five different methodologies. The methods included are: ELECTRE I, Fuzzy set, REGIME analysis, Analytic Hierarchy Process and Dominance-based Rough Set Approach. Thanks to the modular nature of the package, it is possible to add new methods without modifying the existing structure. To present the suite, we applied each module to the same case study, making comparisons. The strong points of the MCDA-GIS integration we developed are its open-source setting and the user friendly interface, both thanks to GRASS GIS, and the use of raster data. Moreover, our suite is a genuine case of perfect integration, where the spatial nature of criteria is always present.

Development of a Web-based Multi-criteria Spatial Decision Support System for the assessment of environmental sustainability of dairy farms

The assessment of the environmental sustainability of agricultural infrastructures involves the use of multiple evaluation criteria and the analysis of geographical information. A Geographic Information System (GIS) is a computer system capable of assembling, storing, analysing, and displaying geographically referenced information. However, the GIS technology still suffers from several shortcomings due in large part to a lack of capable analytical capacity of supporting spatial decision problems. The most common solution for GIS to evolve into an effective tool for decision support is to couple them with operational research tools and in particular Multicriteria Decision Aid (MCDA). Due to the technological advances in the field of information systems, there is a great need to research how to integrate GIS, MCDA, the Internet, modeling and databases aiming at creating Web Multicriteria Spatial Decision Support Systems (Web MC-SDSSs). A Web MC-SDSS methodological framework is proposed for a fully integrated system of GIS and a specific MCDA method – ELECTRE TRI, through the construction of a Macro written in Visual Basic for Applications (VBA) in ArcGIS software. This macro interacts with a Web Algorithm Server for computing MCDA results. The developed Web MC-SDSS, named ELECTRE TRI in ArcGIS, is applied on a case study analysing the environmental sustainability of dairy farms in the Entre-Douro-e-Minho (EDM) Region.

GIS-based multi-criteria analysis for land use suitability assessment in City of Regina

Land use suitability assessment is a key factor in any urban and suburban planning and decision-making processes. The assessment is evaluated by a series of criteria involving socio-economic needs. To deal with the conflicting, disproportionate and multiple criteria, land usage will be characterized with respect to the preferences and importance. Meanwhile, many spatial decision problems can be typically analyzed and interpreted visually by applying GIS for mapping and analysis. Accordingly, this study is to introduce the Multi-criteria decision analysis into the land use suitability analysis along with the existing perspective evolving the role of GIS. For case study, it is the first time to conduct the identification of the current land use situations in City of Regina by using GIS, combined with multi-criteria analysis ideology for existing condition analysis with three criteria referring to social and economic factors. Finally, the study identified five suitability levels, which has revealed the trends, challenges and prospects of land use analysis for urban extension in City of Regina. Comparing the simulated land use suitable classes to the existing land use pattern, difference and optionality have been presented. The results are providing valuable information for the urban extension for policy and decision makers. To improve the accuracy and the reliability of the real-world case study, criteria selection and weight assignments ranks the first place. The integrated use of data analysis and Multi-criteria Decision Analysis approach, in a GIS context, resulted in a visible assessment of current land use in Regina.

GIS Based Multi-criteria Analysis for Industrial Site Selection

Site selection is one of the basic vital decisions in the start-up process, expansion or relocation of businesses of all kinds. Construction of a new industrial system is a major long-term investment, and in this sense determining the location is critical point on the road to success or failure of industrial system. One of the main objectives in industrial site selection is finding the most appropriate site with desired conditions defined by the selection criteria. Most of the data used by managers and decision makers in industrial site selection are geographical which means that industrial site selection process is spatial decision problem. Such studies are becoming more and more common, due to the availability of the Geographic Information Systems (GIS) with user-friendly interfaces. Geographic information systems (GIS) are powerful tool for spatial analysis which provides functionality to capture, store, query, analyze, display and output geographic information. Geographic Information Systems are used in conjunction with other systems and methods such as systems for decision making (DSS) and the method for multi-criteria decision making (MCDM). Synergistic effect is generated by combining these tools contribute to the efficiency and quality of spatial analysis for industrial site selection. This paper presents a successful solution for spatial decision support in the case of spatial analysis of Vojvodina as a region of interest for industrial site selection.