关键词: 时间序列, 植被指数, 物候特征, CART 算法, 滨海湿地

Abstract:

Based on three months of Landsat8 remote sensing images and vector data of the core area of Yancheng national rare birds nature reserve and vector data in 2014,using CART-based decision tree classifier to extract phragmites,suaeda,spartina,fish ponds,mud flat,waters and wetlands information and then changes of vegetation are analyzed.Using vegetation index NDVI,RVI,DVI series spectrum curves to get a wetland vegetation type in the window period,through the vegetation index,the first principal component,tasseled Cap transformation,the original bands(red,near-infrared),unsupervised classification image,sequence subsets are built.Results showed that:1) The window period for vegetation classification is from March to December,phragmites,suaeda,Spartina discrimination of maximal order during this decision tree classification of remote sensing images for the data source can improve the accuracy of classification;2) CART-based decision tree classifier to Yancheng wetland vegetation and distinguish have good overall classification accuracy for 99.88%,99.18% and 97.61% and good Kappa coefficient for 0.99,0.99 and 0.97;3) In 2014,the area of phragmites grew from 61.69km ² to 63.08km ²and spartina from 38.01km ²to 44.78km ² while suaeda had fallen from 26.37km ²to 19.63km ².

Key words: time series, vegetation index, phenological characteristics, CART algorithm, coastal wetland