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• W2364544230 abstract "Wetland is one of the typical ecosystems which can be found in the interaction area between water and land.It is not only our important living environment,but also one of the landscapes which have the richest biodiversity.Since it has many functions such as stabilizing the environment,protecting species gene and providing the resources for the humans,so it plays a very important role in maintaining the region and the global ecological equilibrium.Unfortunately,the wetland was opened up,its area reduces day by day,and the biodiversity encounters the serious disturbance and the destruction since 20th century,because of the contradictory between the population booming and the land resource reducing.The research area in this paper is the Three River Sources area in Qinghai Province.It lies on the west part of China,the center of Qinghai-Tibet Plain,and south of the Qinghai Province.As implied by its name,the Three River Sources area is the source catchments area of Yangtze River,Yellow River and the Lancang River.This area has rich wetland resources for it is covered density rivers,lakes and marshes.25% water of Yangtze River,49% water of Yellow River and 15% o water of Lancang River is coming from this area.In order to better understand the wetland distribution of the Three River Sources area,MOD13Q1 product data and decision tree method for wetland classification were used in this paper.As the dataset have much noises which are called salt and pepper noises,after many experiments,it is found that using the median filter and the principal component(PC) transform methods in the data pre-processing can efficiently revise these MODIS data.In the processing of the decision tree building,the digital elevation model(DEM) is good for separating the lakes and others.To control the curve shape and the threshold of the turning point of the curve in order could make useful of the curve of marshes' NDVI time series and finally finished the construction of the decision tree.Through the accuracy testing,the classification accuracy of lakes reached 96.5%,the overall classification accuracy reached 84.2%,and the kappa coefficient was 0.78.The results showed that the time series of MOD13Q1 data and decision tree method could meet requirements of lakes and marshes classification in a vast scale,but how to use them to classify the river needs more studies in future." @default.
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• W2364544230 date "2010-01-01" @default.
• W2364544230 modified "2023-09-25" @default.
• W2364544230 title "Classification of Remote Sensing Image for Lake and Marsh in the Area of Three River Sources Based on Decision Tree Using MODIS Data" @default.
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