Detecting Large-Scale Urban Land Cover Changes from Very High Resolution Remote Sensing Images Using CNN-Based Classification

Detecting Large-Scale Urban Land Cover Changes from Very High Resolution Remote Sensing Images Using CNN-Based Classification

The study investigates land use/cover classification and change detection of urban areas from very high resolution (VHR) remote sensing images using deep learning-based methods. Firstly, we introduce a fully Atrous convolutional neural network (FACNN) to learn the land cover classification. In the F...

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Bibliographic Details
Main Authors: Chi Zhang, Shiqing Wei, Shunping Ji, Meng Lu
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:ISPRS International Journal of Geo-Information
Subjects:
classification
change detection
convolutional neural networks
Atrous convolution
very-high-resolution remote sensing images
Online Access:https://www.mdpi.com/2220-9964/8/4/189

Internet

https://www.mdpi.com/2220-9964/8/4/189

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