Issue 7.2, August 2003
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Issue 7.2, August 2003
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Pilot-project for “Sisacko-moslavacka County”
Regarding available data and the reality of the humanitarian demining problem, it was decided that the pilot project take place in Sisacko-Moslavacka County, and municipalities of the county would be treated as homogenous zones that would be ranged according to the agreed criteria. According to the available parameters on the area of Sisacko-Moslavacka County, 640 minefields were registered. By terrain surveying, as well as by identification of suspicious areas, a digitized database was created containing all mine-contaminated and suspicious areas with 72 polygons on 11 municipalities in total. Regarding the fact that all aforementioned polygons were not homogenous, and it was impossible to make them homogenous by applying some simple procedure, it was decided that being part of the certain municipality should be a criteria for polygon joining. For example, when forming a set of actions (projects) to be ranked and analyzed, multicriteria analysis should be applied in order to determine the optimal options for risk reduction. Such an approach is reasonable because municipalities are the smallest territorial and political units that are involved in the evaluation of optimal policies for risk reduction.
According to the project demands and in order to ensure all relevant data and enable straightforward generation of more general data, GIS, containing various thematic layers, was created. ArcView and some other Environmental Systems Research Institute (ESRI) tools that enable more complex spatial data analysis were used. When analyzing the problem, the following problem characteristics were evaluated:
Within the project, the following objectives were defined:
As the solving methodology, the following compromised steps are worked out:
According to the fact that during the evaluation of the optimal policies for risk reduction, several groups are involved in the decision process, the activities in the process of problem-solving were defined:
Figure 3 shows a schematic procedure, which contains GIS analysis as a first step and evaluation of relevant criteria presented as thematic layers. For the criteria that can be spatially presented, using GIS analysis, concrete numerical values as input for multicriteria analysis are being evaluated.
For the criteria that cannot be generated by GIS analysis, an expert team evaluation and mathematical estimation were performed. For example, by using data from “mine records” from both parties involved in the war conflict, it is estimated that on the territory of this county, 30,506 mines are placed—24,887 of which can be identified on the already known minefields in eight municipalities. For 5,623 mines, location is unknown, so the most plausible solution is that they are placed on the territory of 11 mine-endangered municipalities or less likely, on the territories of other municipalities in the county that currently are not contaminated with mines. Figure 4 shows the territory that presents possible contact of population and UXO. The obtained area presents an “objective estimated risk” for the domestic population calculated by multiplying the number of inhabitants of settlement that is within, or on, the border of mine-suspected areas with an average population density on the study area.
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| Figure 4: Layout of possible contact of population and UXO. |
The value of infrastructure parameters, which is situated on suspected minefields, is calculated indirectly as well (i.e., around digitized installation infrastructure, a 100-meter double-sided buffer is determined, and after that by implementation of “geoprocessing function” an intersection area of minefields and infrastructure installation is determined). In a similar manner, for the mine-contaminated areas of each of the 11 analyzed municipalities, the values of estimated parameter values for other criteria are evaluated (roads, agriculture areas, forests, parks of nature, etc.—see Figure 5).
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| Figure 5: Layout of intersection area of mine fields and infrastructure installation. |
During multicriteria analysis for each of the criteria, the weights were assigned by the stakeholder involved in the decision process. Namely, it is important to involve representatives of social and political associations from the municipalities’ territory, which are included in the priority ranking, in order to obtain results that would be accepted by them as optimal ones.
For the numerical part of multicriteria analysis, two methods, PROMETHEE and GAIA “Decision Lab 2000,” are used. It is the commercial name of software distributed by “Visual Decision” from Canada. Contemporary architecture of this software, based on the Decision Support System (DSS) enables comfortable work and widespread support for the decision-making processes.
A large part of the information, most of which is possible to visualize (graphs, various colored diagrams) gives the decision-maker a complete insight into the problem characteristics and possible results of various problem-solving scenarios. Table 1 presents results of the numerical analysis for Sisacko-Moslavacka County by the PROMETHEE method. For example, look at the evaluated ranks that present priority assessment for the 11 contaminated municipalities (presented results are not the final optimal solution).
Achieved synthetic parameter “Phi” presents valorization of priorities based on defined criteria and weighting coefficients. Table 1 shows that municipality Slunj is ranked first and represents demining priority because the total Phi value of 0.5364 dominates the second-ranked municipality, Petrinja, with Phi value of 0.3077. Follow the ranks of other municipalities to the last one, municipality Gvozd with negative priority value Phi -0.2397.
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Table 1: Ranked municipalities. |
Synthetic parameter Phi is very convenient for the expression of differences or definition of priority “power,” so it can be used for the determination of demining funds relations of each municipality. For example, if someone wants to distribute the total amount of money to the top four ranked municipalities, the proportion of the distribution can be based on Phi indicator value (Figure 6).
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| Figure 6: Illustrative layout of fund distribution based on obtained rank and calculated priority “Phi.” |
Figure 7 shows the layout of the relations between criteria obtained by GAIA software, namely by application of principal component analysis for Phi values for each criterion. Insight into the criteria relations is important for understanding the problem and recognition of the correlation between different criteria parameters. As Figure 7 shows, it is easy to notice criteria with a high degree of correlation and criteria in conflicting positions.
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| Figure 7: Geometrical presentation of the relations between criteria is shown by GAIA method. |
Conclusions and Summary
The developed hierarchic approach of priority assessment for demining, using multicriteria analysis and GIS support, illustrated the possibility of objective valorization in humanitarian demining that is acceptable for most stakeholders in the decision process. The relatively small costs of data collection, editing and analysis with simple control and transparency through all hierarchic levels, as well as involvement of all stakeholders (directly or indirectly) in the decision process, give such an approach an advantage compared to the other methods being used.
References
Contact Information
Nenad Mladineo
Faculty of Civil Engineering
University of Split
21000 Split, Croatia
E-mail: mladineo@gradst.hr
Snjezana Knezic
Faculty of Civil Engineering
University of Split
21000 Split, Croatia
E-mail: knezic@gradst.hr
Damir Gorseta
South-Eastern Europe Mine Action Coordination Council
1292 Ig, Slovenia
E-mail: gorseta@itf-fund.si