Coastal wetland has many ecological service functions such as shoreline protection,biodiversity conservation,material production,energy exchange,and providing leisure and scientific research space. Vegetation is an important part of coastal wetland,and its distribution,structural changes and other landscape information reflect the health status of coastal wetlands to a large extent. In order to analyze the feasibil-ity of identifying vegetation species under ebb and flow of coastal wetland by remote sensing,two periods of Landsat 8 ebb and flow images were selected to classify vegetation in coastal wetland of Yellow River Delta based on statistical discriminant,decision tree supervised classifi-cation and unsupervised classification methods. The results showed that the classification effect of statistical discriminant supervised classifica-tion was the best,the classification accuracy was up to 97％,and the vegetation types could be accurately distinguished,and the ebb and flow had little effect on the classification results. The research indicated that remote sensing technology is feasible to extract vegetation information of coastal wetland under different tidal conditions,which can provide technical and data support for vegetation monitoring,ecological restora-tion and blue carbon storage estimation of coastal wetland.
关键词
滨海湿地/植被提取/统计判别式监督分类/非监督分类/决策树监督分类
Key words
Coastal wetland/Vegetation abstraction/Statistical discriminant supervised classification/Unsupervised classification/Decision tree supervised classification
维普
万方数据