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A Deep Convolution Neural Network Method for Land Cover Mapping: A Case Study of Qinhuangdao, China
2018
Remote Sensing
Land cover and its dynamic information is the basis for characterizing surface conditions, supporting land resource management and optimization, and assessing the impacts of climate change and human activities. In land cover information extraction, the traditional convolutional neural network (CNN) method has several problems, such as the inability to be applied to multispectral and hyperspectral satellite imagery, the weak generalization ability of the model and the difficulty of automating
doi:10.3390/rs10122053
fatcat:hyl2sfxiercq3mrpx5cfguy5d4