A GIS-Based Decision Support System For The Rehabilitation And Revegetation Of Coal Mine Spoil

This paper presents the development of a knowledge based integrated decision support system (E.X.I.S) for the extractive industries to provide information concerning the environmental impact of extractive operations on land quality, surface and ground waters, and the best solutions for the rehabilitation/revegetation of the waste disposal areas to the relevant target groups (extractive industries, regional authorities, national authorities, research institutes, public). GIS was integrated with the decision-making models for the rehabilitation and revegetation of mine spoil. The system design involves several steps including site selection ? mine type identification ? waste identification ? selection of rehabilitation (revegetation or other methods). The knowledge based model consists of two integral parts: the model base, in which the input data are processed and classified using special fuzzy algorithms and criteria and the knowledge model, which hosts the various decision algorithms concerning evaluation of vegetation covers, selection of trees and plant species, selection of rehabilitation and revegetation schemes and also economic analysis for each option. The system input will include parameters on site characteristics (climate, topography, geology, hydrology etc), waste type and properties (physical-geotechnical and geochemical data) as well as environmental parameters of the existing waste disposal area. Based on the values of the above parameters and the characteristics of the rehabilitation technologies developed worldwide, the system, using IF-THEN rules will define a list of appropriate techniques for the rehabilitation of the examined waste. Then, the model will involve the application of multi-criteria analysis (MCA), i.e. a structured system for ranking alternatives and making selections and decisions. Each technique shall be judged based on its behavior into four fields, i.e. financial, social, technical and environmental criteria. In turn these fields will be analyzed into a lower level of evaluation criteria.