Title :
A study on forest ecological environment gradient with remote sensing, GIS and expert system
Author :
Zhang, Xiao-li ; You, Xian-xiang ; Liu, Xu-sheng ; Huang, Hua-guo
Author_Institution :
Coll. of Resources & Environ., Beijing Forestry Univ., China
Abstract :
This study deals with the synthetic evaluation of the ecological environment quality in different levels supported by remote sensing (RS), geographic information system (GIS) and expert system (ES). By this study, a new integrated method on the prediction of ecological environment variation and the decision-making of the ecological environment protection were proposed. Firstly, based on the comprehensive analysis on the forest ecological environmental factors in the different levels in Beijing, the environmental factors were extracted by using RS technique, ground investigation and statistics analysis. In view of the result of above analysis, the system of evaluation and index was defined. Secondly, the environmental factors data was extracted by RS and ground investigation, and the GIS spatial database, ES knowledge base was built. With the knowledge discovered from data base (KDD) techniques, the dynamic spatial knowledge base was developed. Then, a digital environment model of forest ecologic was built, which was used to analysis the ecological environment gradient. Also, this study developed an integrated software system of "3S" (RS, GIS, ES). Using this system, the distribution maps of the environment gradient of different levels were produced automatically, which effects the spatial-temporal pattern of the ecological environment situation and the interrelation of the environmental factors.
Keywords :
data mining; decision making; ecology; environmental factors; expert systems; forestry; geographic information systems; remote sensing; GIS spatial database; KDD techniques; decision-making; digital environment model; distribution maps; dynamic spatial knowledge base; ecological environment protection; ecological environment variation; environmental factors data; expert system; forest ecological environment gradient; geographic information system; knowledge discovered from data base; remote sensing; spatial-temporal pattern; statistics analysis; Biological system modeling; Data mining; Decision making; Environmental factors; Expert systems; Geographic Information Systems; Protection; Remote sensing; Spatial databases; Statistical analysis;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259907