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- W4310346626 abstract "In this paper, based on the GF_1 satellite data of Danjiangkou wetland from 2015 to 2020, the multi-year raster images are classified by softmax classification algorithm, which realized the reuse of wetland classifier based on machine learning method and the dynamic monitoring of land cover change of Danjiangkou wetland. The results showed that the area proportion of Danjiangkou wetland fluctuated and increased from 2015 to 2020, which were 20.44%, 19.10%, 21.50%, 26.23%, 23.58% and 27.35%, respectively, among which the increase was mainly water area. The classification results are verified, and the overall classification accuracy and Kappa coefficient are above 94.0% and 0.898. It is considered that softmax classification algorithm based on GF_1 data is a feasible method to obtain accurate wetland land cover classification information, which can provide research reference for the extraction of wetland land cover information." @default.
- W4310346626 created "2022-12-09" @default.
- W4310346626 creator A5064149994 @default.
- W4310346626 date "2022-11-30" @default.
- W4310346626 modified "2023-10-14" @default.
- W4310346626 title "Land Cover Change Information Extraction of Danjiangkou Wetland Based on GF_1 Data and Softmax Algorithm" @default.
- W4310346626 cites W1998511120 @default.
- W4310346626 cites W2146189581 @default.
- W4310346626 doi "https://doi.org/10.1007/978-981-19-8202-6_29" @default.
- W4310346626 hasPublicationYear "2022" @default.
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