Comparing Fully Deep Convolutional Neural Networks for Land Cover Classification with High-Spatial-Resolution Gaofen-2 Images

Comparing Fully Deep Convolutional Neural Networks for Land Cover Classification with High-Spatial-Resolution Gaofen-2 Images

Land cover is an important variable of the terrestrial ecosystem that provides information for natural resources management, urban sprawl detection, and environment research. To classify land cover with high-spatial-resolution multispectral remote sensing imagery is a difficult problem due to hetero...

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Bibliographic Details
Main Authors: Zemin Han, Yuanyong Dian, Hao Xia, Jingjing Zhou, Yongfeng Jian, Chonghuai Yao, Xiong Wang, Yuan Li
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:ISPRS International Journal of Geo-Information
Subjects:
deep learning
classification
land cover
full convolutional network
Unet
Segnet
Online Access:https://www.mdpi.com/2220-9964/9/8/478

Internet

https://www.mdpi.com/2220-9964/9/8/478

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