Plenary Lecture

A GIS-based decision support system for revegetation of lands contaminated from mining activities

Prof. Daoliang Li
P. O. Box 121
EU-China Center for Information & Communication Technologies
China Agricultural University
17 Tsinghua East Road
Beijing,100083, P. R. China

Abstract: 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). The 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 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 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 behaviour into four fields, i.e. financial, social, technical and environmental criterion. In turn these fields will be analysed into a lower level of evaluation criteria.

Brief Biography of the Speaker:
Prof. Dr. Daoliang Li , is the Director of the EU-China centre for information & communication technologies, China Agricultural University . He is principal research interest is digital agriculture and rural information society technologies , especially for artificial intelligence, Decision Support System, Remote Sensing and GIS applications in aquaculture and land management . He is a member of International Federation for Information Processing, deputy head of Chinese Society of Agriculture and the executive director of Information Group, Chinese Society of Agricultural Engineering. He also is the chief scientist in rural information society development of Dongying, Wuzhou, Baiyin Government. He was the chairman od the Second IFIP Conference on Artificial Intelligence Applications and Innovations Beijing, China, September 7-9, 2005. he coord inated many international and national research projects, and has published more than 50 national, international journals and 3 books.