Study on Vegetation Extraction Method of Lianyungang Coastal Wetland Based on Phenological Characteristics
Coastal wetland is a special ecosystem between land and sea.The vegetation of coastal wetland has an important influence on the function of its ecosystem.It is of great significance to study the rapid and accurate extraction method of coastal wetland vegetation for the ecological protection and management of coastal wetland.The vegetation types of coastal wetlands are mostly herbaceous vegetation.The spectral characteristics and spatial characteristics of images between different vegetation types are similar,and the separability is small,which leads to the difficulty of vegetation remote sensing classification.Fusion of vegetation phenological character-istics has become an important means to improve classification accuracy.In this study,the coast-al wetland of Lianyungang was taken as the research area,and the PIE-Engine remote sensing cloud computing platform was used to obtain 72 scenes of Sentinel-2 images in 2022 to construct NDVI time series model.The Fourier function was used to fit the vegetation phenological charac-teristic curve,analyze the vegetation phenological characteristics,and integrate the phenological characteristics for vegetation classification.The results show that the overall accuracy of vegeta-tion classification is 83.83%and the Kappa coefficient is 0.76 after the fusion of phenological fea-tures.Compared with the single-phase image method,the classification accuracy is increased by 16.6 percentage points and the Kappa coefficient is increased by 0.23.Therefore the use of vege-tation phenological features can effectively improve the classification accuracy.
coastal wetland vegetationphenological characteristicsSentinel-2 imagePIE-En-gine platformtime series
NETL
NSTL
万方数据
