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《Remote Sensing Technology and Application》 2012-02
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Study on the Classification Approaches of Yancheng Coastal Wetlands based on ALOS Image

Xue Xingyu,Liu Hongyu(Jiangsu Key Laboratory of Environmental Change and Ecological Construction,School of Geography Science Nanjing Normal University,Nanjing 210046,China)  
The Yancheng coastal wetlands are rich in biodiversity and of significant importance in wetland conservation of the world.How to acquire coastal wetland types information more accurately using remote sensing images is significant to wetland researches.The core zone of Yancheng coastal wetlands are taken as a study area and the classification of wetland types is based on ALOS image.We developed the following methods to improve the classification accurately of wetland types.At first,we use the unsupervised classification method to conduct the primary classification system for the coastal wetlands.Then,the reason for limiting the accuracy of wetland types were found,especially in the ecotones of wetland types.The ecotones among reed marsh,spartina alterniflora marsh and suaeda heteroptera kitag marsh have been revised by using the spectral feature of wetlands,texture,principal component analysis and relative knowledge rules.In addition,the rest parts were revised by GIS rules.Finally,the precision of classification was tested by the GPS data and the average accuracy of wetland types has reached 92.6829% the kappa coefficient reaches 0.9098 in the test region.Which suggested that the multi-level classification method including the knowledge rules and GIS rules are effective to extracting the coastal wetland cover information.
【Fund】: 国家自然科学基金项目“基于生态过程的海滨景观演变动态模拟研究”(41071119);; 江苏省高校自然科学研究重大项目“自然与人为影响下盐城海滨湿地景观演变模拟模型研究”(10KJA170029)
【CateGory Index】: X87
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