An automatic cloud detection model for Sentinel-2 imagery based on Google Earth Engine-Reference-Cited by-同舟云学术

An automatic cloud detection model for Sentinel-2 imagery based on Google Earth Engine

Published:2021-12-17 Issue:2 Volume:13 Page:196-206
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Li Jianfeng¹²³,Wang Luyao⁴⁵,Liu Siqi⁴⁵,Peng Biao⁴⁵,Ye Huping²^ORCID

Affiliation:

1. Institute of Land Engineering and Technology, Shaanxi Provincial Land Engineering Construction Group Co., Ltd., Xi’an, China

2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

3. Shaanxi Provincial Land Engineering Construction Group Co., Ltd., Xi'an, China

4. Key Laboratory of Degraded and Unused Land Consolidation Engineering, the Ministry of Natural Resources, Ltd., Xi'an, China

5. Shaanxi Provincial Land Consolidation Engineering Technology Research Center, Ltd., Xi'an, China

Funder

National Key Research and Development Program of China

Strategic Priority Research Program of the Chinese Academy of Sciences

Innovation Capability Support Program of Shaanxi

Technology Innovation Center for Land Engineering and Human Settlements, Shaanxi Land Engineering Construction Group Co.,Ltd and Xi' an Jiaotong University

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2021.1988753

Reference20 articles.

1. A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran)

2. Validation of Copernicus Sentinel-2 Cloud Masks Obtained from MAJA, Sen2Cor, and FMask Processors Using Reference Cloud Masks Generated with a Supervised Active Learning Procedure

3. Baetens, L., and O. Hagolle 2018. “Sentinel-2 Reference Cloud Masks Generated by an Active Learning Method.” Type: Dataset. Accessed 23 August 2021. https://zenodo.org/record/1460961

4. Clerc, S., O. Devignot, and L. Pessiot 2015. “S2 MPC Data Quality Report.” Accessed 2 August 2020. https://earth.esa.int/documents/247904/3902831/Sentinel-2_L1C_Data_Quality_Report/adfff903-a337-4fc1-9439-558456bad0b1?version=1.1

5. A first assessment of the Sentinel-2 Level 1-C cloud mask product to support informed surface analyses

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