NestNet: a multiscale convolutional neural network for remote sensing image change detection
文献类型：期刊论文
| 作者 | Yu, Xiao2; Fan, Junfu2; Chen, Jiahao2; Zhang, Peng2; Zhou, Yuke1; Han, Liusheng2 |
| 刊名 | INTERNATIONAL JOURNAL OF REMOTE SENSING
 |
| 出版日期 | 2021-07-03 |
| 卷号 | 42期号:13页码:4902-4925 |
| ISSN号 | 0143-1161 |
| DOI | 10.1080/01431161.2021.1906982 |
| 通讯作者 | Fan, Junfu(fanjf@sdut.edu.cn) ; Zhou, Yuke(zhouyk@igsnrr.ac.cn) |
| 英文摘要 | With the rapid development of remote sensing technologies, the frequency of observations of the same location is increasing, and many satellites and sensors produced a large amount of time series images. These images make long-term change detection and dynamic characteristic estimation of ground features possible. However, conventional remote sensing image change detection methods mostly rely on manual visual interpretation and supervised or unsupervised computer-aided classification. Traditional methods always face many bottlenecks when processing big and fast-growing datasets, such as low computational efficiency, low level of automation, and different identification standards and accuracies caused by different operators. With the rapid accumulation of remote sensing data, it has become an important but more challenging task to conduct change detection in a more precise, automated and standardized way. The development of geointelligent computing technologies provides a means of solving these problems and improve the accuracy and efficiency of remote sensing image change detection. In this paper, we presented a novel deep learning model called nest network(NestNet) based on a convolutional neural network to improve the accuracy of the automatic change detection task by using remotely sensed time series images. NestNet extracts the respective features of bi-temporal images using an encoding parallel module and subsequently employs absolute different operations to process the features of two images. Compared with change detection method based on U-Shaped network plus plus (UNet++), the parallel module improves the efficiency of NestNet. Finally, a decoding module is used to generate a predicted change image. This paper compares NestNet to traditional methods and state-of-the-art deep learning models on two datasets. The experimental results demonstrate that the accuracy of NestNet is better than that of state-of-the-art methods. It can be concluded that the NestNet model is a potential approach for change detection using high resolution remote sensing images. |
| 资助项目 | National Key Research and Development Program of China[2017YFB0503500] ; National Key Research and Development Program of China[2018YFB0505301] ; Shandong Provincial Natural Science Foundation[ZR2020MD015] ; Shandong Provincial Natural Science Foundation[ZR2020MD018] ; Major Science and Technology Innovation Project of Shandong Province[2019JZZY020103] ; Young Teacher Development Support Program of Shandong University of Technology[4072-115016] |
| WOS研究方向 | Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000637195700001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | National Key Research and Development Program of China ; Shandong Provincial Natural Science Foundation ; Major Science and Technology Innovation Project of Shandong Province ; Young Teacher Development Support Program of Shandong University of Technology |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/161868]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Fan, Junfu; Zhou, Yuke |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Ecol Observing Network & Modeling Lab, Beijing, Peoples R China 2.Shandong Univ Technol, Sch Civil & Architectural Engn, Zibo 255000, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Xiao,Fan, Junfu,Chen, Jiahao,et al. NestNet: a multiscale convolutional neural network for remote sensing image change detection[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2021,42(13):4902-4925. |
| APA | Yu, Xiao,Fan, Junfu,Chen, Jiahao,Zhang, Peng,Zhou, Yuke,&Han, Liusheng.(2021).NestNet: a multiscale convolutional neural network for remote sensing image change detection.INTERNATIONAL JOURNAL OF REMOTE SENSING,42(13),4902-4925. |
| MLA | Yu, Xiao,et al."NestNet: a multiscale convolutional neural network for remote sensing image change detection".INTERNATIONAL JOURNAL OF REMOTE SENSING 42.13(2021):4902-4925. |
入库方式： OAI收割
来源：地理科学与资源研究所
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