Classification of Yellow River Estuary Wetland based on hyperspectral remote sensing imagery

In recent decades, under the combined effects of climate change, human activities and other factors, the surface state of the Yellow River estuary has undergone dramatic changes. Therefore, the use of remote sensing means to classify and identify the wetlands at the estuary of the Yellow River is extremely important for the rational utilization, development and protection of wetland resources in this area. According to the phenological characteristics of vegetation such as reed, tamarix, and suaeda, this paper selects the hyperspectral data of “Zhuhai-1” in September 2021 and divides the study into seven categories: tamarix, reed, suaeda, spartina alterniflora, clear water, turbid water and tidal flats in combination with random forest classification. The results show that: After the analysis of the envelope removal method, it can be seen that near the band3-band6, band10, band11, band14-band16, band20, band25 bands, 7 kinds of land types can be better identified; The overall classification accuracy is 85.94%, and the Kappa coefficient is 0.84, and the classification accuracy is ideal.