Improving Urban Land Cover/Use Mapping by Integrating A Hybrid Convolutional Neural Network and An Automatic Training Sample Expanding Strategy

Improving Urban Land Cover/Use Mapping by Integrating A Hybrid Convolutional Neural Network and An Automatic Training Sample Expanding Strategy

Moderate spatial resolution (MSR) satellite images, which hold a trade-off among radiometric, spectral, spatial and temporal characteristics, are extremely popular data for acquiring land cover information. However, the low accuracy of existing classification methods for MSR images is still a fundam...

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Bibliographic Details
Main Authors: Xin Luo, Xiaohua Tong, Zhongwen Hu, Guofeng Wu
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Remote Sensing
Subjects:
remote sensing
land cover classification
spectral feature
context feature
convolutional neural networks
Online Access:https://www.mdpi.com/2072-4292/12/14/2292

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