Pham Vu Dong, Bui Quang Thanh, Nguyen Quoc Huy, Vo Hong Anh, Pham Van Manh

Main Article Content


Cloud detection is a significant task in optical remote sensing to reconstruct the contaminated cloud area from multi-temporal satellite images. Besides, the rapid development of machine learning techniques, especially deep learning algorithms, can detect clouds over a large area in optical remote sensing data. In this study, the method based on the proposed deep-learning method called ODC-Cloud, which was built on convolutional blocks and integrating with the Open Data Cube (ODC) platform. The results showed that our proposed model achieved an overall 90% accuracy in detecting cloud in Landsat 8 OLI imagery and successfully integrated with the ODC to perform multi-scale and multi-temporal analysis. This is a pioneer study in techniques of storing and analyzing big optical remote sensing data.
Keywords: Optical Remote Sensing, Landsat 8 OLI, automatic cloud detection, deep-learning, Open Data Cube.


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