Research On Remote Sensing Monitoring Technology Of The Khanka-Lake Wetland Resource

Wetland as one kind of important natural resource, distributes at the global each place and has an irreplaceable function in the local ecological balance and provides the wild habit for the valuable animals and plants (especially waterfowl). Presently, "kidney of the Earth"-wetland, it can't bear the heavy load, Over-exploiting caused the wetland sharp cutoff in large area site and the global climatic change; made the wetland to face the serious situation. The remote sensing is the most powerful method, which applied widely for its valuable features such as rapid information replacement, covers widely, updates very fast and real-time dynamic.This research take the Khanka Lake wetland as the study area, used the TM image of the Khanka Lake area acquired on October 2005, September 1994, June and September 1989, combining the related statistical material and data, to conduct research on the extraction of wetland information, the dynamic change, the landscape pattern as well as the driving force factors. It provided the scientific basis for the protection of the Khanka Lake wetland, and provided the reference for other similar wetland types. The main content included:(1) Extraction of Khanka Lake wetland information. On the base of remote sensing image processing, first, we carried on the optimized wave band combination through OIF and the analysis of the inter-(relation) of various bands, choose the pseudocolor combination of5,4,3; Then we analyzed the spectral characteristic of ground, choosed the classification of MLC (Maximum Likelihood Classification) and decision tree to extract information of Khanka Lake wetland, and made a comparison and analysis on the experimental results. The research indicated that, the decision tree can realize the extraction of wetland information better.(2) Wetland change monitor research. Using the result of extraction of wetland information, we used the post-classification comparison to study the wetland change, and obtained the wetland type, the area distribution as well as the type dynamic change in different time, made a contrastive analysis of the change situation in the Khanka Lake wetland.(3) Landscape pattern and the driving force factors analysis. First used three thematic maps to analysis wetland landscape index in the study area, obtained the table of landscape metrics. We used the model of Markov process to simulate the change of wetland types, the results are satisfying. We analyzed the driving force factors of wetland change from the angle of natural and human factor combined the situation of wetland change.