An Unsupervised Model Based on Convolutional Neural Network for Fusing Landsat-8 and Sentinel-2 Data-Reference-Cited by-同舟云学术

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An Unsupervised Model Based on Convolutional Neural Network for Fusing Landsat-8 and Sentinel-2 Data

Published:2024-07-07 Issue: Volume:63 Page:9214-9217
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Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Yu Shengnan¹,Deng Yong²,Li Yunfei³,Li Jun¹,Chen Jia¹,Zhang Shaoquan⁴

Affiliation:

1. China University of Geosciences,School of Computer Science,Wuhan,P. R. China,430074

2. Changjiang Institute of Survey, Planning, Design and Research,Wuhan,China,430010

3. Sun Yat-sen University,School of Geography and Planning,Guangzhou,China,510275

4. Nanchang Institute of Technology,Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing,Nanchang,China,330099

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10642772.pdf?arnumber=10642772

Reference11 articles.

1. Satellite remote sensing for applied ecologists: opportunities and challenges

2. Enhancing assessment of corn growth performance using unmanned aerial vehicles (UAVs) and deep learning

3. Fusing Sentinel-2 and Landsat-8 Surface Reflectance Data via Pixel-Wise Local Normalization

4. Fusing Landsat-7, Landsat-8 and Sentinel-2 surface reflectance to generate dense time series images with 10m spatial resolution

5. Fusing Sentinel-2 and Landsat 8 Satellite Images Using a Model-Based Method

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