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Open AccessArticle

Urban Area Detection in Very High Resolution Remote Sensing Images Using Deep Convolutional Neural Networks

by Tian Tian 1, Chang Li 2, Jinkang Xu 3 and Jiayi Ma 4,*
1
Hubei Key Laboratory of Intelligent Geo-Information Processing, College of Computer Science, China University of Geosciences, Wuhan 430074, China
2
Department of Biomedical Engineering, Hefei University of Technology, Hefei 230009, China
3
School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China
4
Electronic Information School, Wuhan University, Wuhan 430072, China
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(3), 904; https://doi.org/10.3390/s18030904
Received: 8 March 2018 / Revised: 14 March 2018 / Accepted: 14 March 2018 / Published: 18 March 2018
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
Detecting urban areas from very high resolution (VHR) remote sensing images plays an important role in the field of Earth observation. The recently-developed deep convolutional neural networks (DCNNs), which can extract rich features from training data automatically, have achieved outstanding performance on many image classification databases. Motivated by this fact, we propose a new urban area detection method based on DCNNs in this paper. The proposed method mainly includes three steps: (i) a visual dictionary is obtained based on the deep features extracted by pre-trained DCNNs; (ii) urban words are learned from labeled images; (iii) the urban regions are detected in a new image based on the nearest dictionary word criterion. The qualitative and quantitative experiments on different datasets demonstrate that the proposed method can obtain a remarkable overall accuracy (OA) and kappa coefficient. Moreover, it can also strike a good balance between the true positive rate (TPR) and false positive rate (FPR). View Full-Text
Keywords: urban area detection; remote sensing; very high resolution; deep convolutional neural networks urban area detection; remote sensing; very high resolution; deep convolutional neural networks
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Tian, T.; Li, C.; Xu, J.; Ma, J. Urban Area Detection in Very High Resolution Remote Sensing Images Using Deep Convolutional Neural Networks. Sensors 2018, 18, 904.

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