Study On Knowledge Discovery-based Identification, Detection And Evalution Law Mining Of Pearl River Estuary Wetlands

Wetland is an important and special ecosystem, which exists in hydrophilic ecosystem (deep lake, ocean) and land ecosystem (forest, lawn). Wetland is one of the most productive ecosystem and one of the most Biodiversity ecosystems. It provides many kinds of resources about production and life, and it also has high value of economics, environmental benefit, and much zoology function. In the recent years, wetland recourse in China has decreased because of the frequently action of human being. Wetland detection using Remote Sensing, which in the purpose of effective inspection and reasonable protection about wetland, and the research in concern have become the most important research direction in the area of wetland research.Remote sensing technique and GIS technique have been wildly used in the area of wetland recourse actuality survey, dynamic change detection and wetland mapping etc. Remote sensing technique has many advantages, such as wide observation, huge information, ration information, fast renewed information, multi-temporal, many plat form, rich history data, and can be contrasted feature etc, which makes the practice of remote sensing stand out and important in the area of wetland research. With the achievement of computer software and hardware these years, the GPS and GIS technology developed fast and popularization. The combination of 3S technology made the efficiency of improved in the practice of wetland research with the technology of remote sensing.This paper make the core area (Pearl River Estuary) of Pearl River Delta as the research area, gaining different types of wetland information using Knowledge Discovery and Data Mining method with multi-temporal, multi-resolution, multi-imaging mode remote images (Optical remote sensing, Radar remote sensing), and detection the dynamic changing of wetlands in the Pearl River Estuary in the recent 20 years. Analyzing the changing feature, and use the space-time association rule mining method to obtain the Association Rules about wetland evolvement and human actions. The results will support basic dada and decision gist, and have important theoretical meanings, practical meanings, and social meanings. Through overall analysis and discussion, the main conclusions were drawn in this article as follows:(1) In the research of wetland identify, and dynamic changes detection using remote sensing, the methods of knowledge discovery and data mining are effective, and can acquire good classify precision. Decision tree arithmetic, neural networks arithmetic, Rough Set arithmetic, Support Vector Machine, and NaiveBayes arithmetic were used in this article.(2) The identifying of the wetland information with Decision tree arithmetic has the highest precision. The research of this article make clear that during the several knowledge discovery methods, Decision tree arithmetic has the highest classify precision and require less remote sensing data.(3) The wetland resource of Pearl River Estuary decreased from 1988 to 2004. This article used 4 temporal Landsat TM data to detection the dynamic changes about the Pearl River Estuary Wetland, and analysis the changing speed, bilateral change dynamic degree, spatial center of gravity distribution displacement of wetlands. The analyzed result means that the wetland resource of Pear River Estuary decreased from 1988, but it had been protected and recovered, the area increased from2002.(4) The Association Rules method can obtain the wetland evolution law. Association Rules is one of the knowledge discovery method, and it can capture the association of different items (wetlands and other influence attributes). This article gives the sample of Dongguang City, on the level of three scales of pixel, town and grid to mining the Association Rules about the wetland evolution and the social economic statistical attributes, environmental attributes, and land use attributes. The research indicates that grid scale is the best space scale for mining the wetland evolution association rules. There are strong association among The decrease of wetland evolution of Dongguan, the increase of environment attributions, the increase of new comers and the decline of agricultural population and the agriculture outcome, the expand of city land.(5) The remote sensing data of multi-resolution, multi-imaging mode has been used successfully in the research of wetland remote sensing. When we using the remote sensing technology and knowledge discovery method to do the research about wetland resource, passive imaging optical remote sensing, such as SPOT (2.5m spatial resolution) and Landsat TM (30m spatial resolution) and active imaging Radar remote sensing, such Envisat ASAR (30m spatial resolution) and Radarsat SAR (6m spatial resolution) were used in this article. The research indicates that the combined use of multi-source remote sensing data can colligate all the advantages to offset the lack of information with single remote sensing data. It can enlarges the application of each information, and improve the precision of wetland information acquiring.