Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images

Matthieu Molinier; Niko Reunanen; Arttu Lämsä; Heikki Astola; Tomi Räty

doi:10.1109/IGARSS.2018.8517484

Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images

Matthieu Molinier, Niko Reunanen, Arttu Lämsä, Heikki Astola, Tomi Räty

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

4 Citations (Scopus)

Abstract

Many cloud and shadow detection methods have been proposed already, but improvements can be made on accuracy or automation. In this study, we propose a Fully Convolutional Network model for the detection of clouds and shadows in optical satellite images. The proposed model was trained on 165 Landsat images in Finland, and tested on an independent set of images. The cloud and shadow detection accuracy reached 95%, outperforming both quantitatively and qualitatively a selection of other deep learning architectures.

Original language	English
Title of host publication	2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	2107-2110
Number of pages	4
ISBN (Electronic)	978-1-5386-7150-4 , 978-1-5386-7149-8
ISBN (Print)	978-1-5386-7151-1
DOIs	https://doi.org/10.1109/IGARSS.2018.8517484
Publication status	Published - 5 Nov 2018
MoE publication type	Not Eligible
Event	38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018

Conference

Conference	38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Abbreviated title	IGARSS
Country/Territory	Spain
City	Valencia
Period	22/07/18 → 27/07/18

Keywords

Remote sensing
Clouds
Satellites
Artificial satellites
Earth
Optical imaging
Cloud and shadow masking
optical images
deep learning
fully convolutional network
Landsat

Access to Document

10.1109/IGARSS.2018.8517484Licence: Unspecified

Cite this

Molinier, M., Reunanen, N., Lämsä, A., Astola, H., & Räty, T. (2018). Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings (pp. 2107-2110). Article 8517484 IEEE Institute of Electrical and Electronic Engineers. https://doi.org/10.1109/IGARSS.2018.8517484

@inproceedings{5e438abdd62d4fc18091324372dc11ac,

title = "Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images",

abstract = "Many cloud and shadow detection methods have been proposed already, but improvements can be made on accuracy or automation. In this study, we propose a Fully Convolutional Network model for the detection of clouds and shadows in optical satellite images. The proposed model was trained on 165 Landsat images in Finland, and tested on an independent set of images. The cloud and shadow detection accuracy reached 95%, outperforming both quantitatively and qualitatively a selection of other deep learning architectures.",

keywords = "Remote sensing, Clouds, Satellites, Artificial satellites, Earth, Optical imaging, Cloud and shadow masking, optical images, deep learning, fully convolutional network, Landsat",

author = "Matthieu Molinier and Niko Reunanen and Arttu L{\"a}ms{\"a} and Heikki Astola and Tomi R{\"a}ty",

note = "Funding Information: This study was carried out in the project DeepCloud funded by VTT Technical Research Centre of Finland Ltd, and Mega-Mart2 funded by the Electronic Component Systems for European Leadership (ECSEL) Joint Undertaking (grant agreement No. 737494) of the Horizon 2020 European Union funding programme. The authors would like to thank Dr Tuomo Tuikka for his support in the VTT DeepCloud project. Publisher Copyright: {\textcopyright} 2018 IEEE Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, IGARSS ; Conference date: 22-07-2018 Through 27-07-2018",

year = "2018",

month = nov,

day = "5",

doi = "10.1109/IGARSS.2018.8517484",

language = "English",

isbn = "978-1-5386-7151-1 ",

pages = "2107--2110",

booktitle = "2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

}

Molinier, M, Reunanen, N, Lämsä, A , Astola, H & Räty, T 2018, Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images. in 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings., 8517484, IEEE Institute of Electrical and Electronic Engineers, pp. 2107-2110, 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, 22/07/18. https://doi.org/10.1109/IGARSS.2018.8517484

Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images. / Molinier, Matthieu; Reunanen, Niko; Lämsä, Arttu et al.
2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. IEEE Institute of Electrical and Electronic Engineers, 2018. p. 2107-2110 8517484.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images

AU - Molinier, Matthieu

AU - Reunanen, Niko

AU - Lämsä, Arttu

AU - Astola, Heikki

AU - Räty, Tomi

N1 - Funding Information: This study was carried out in the project DeepCloud funded by VTT Technical Research Centre of Finland Ltd, and Mega-Mart2 funded by the Electronic Component Systems for European Leadership (ECSEL) Joint Undertaking (grant agreement No. 737494) of the Horizon 2020 European Union funding programme. The authors would like to thank Dr Tuomo Tuikka for his support in the VTT DeepCloud project. Publisher Copyright: © 2018 IEEE Copyright: Copyright 2019 Elsevier B.V., All rights reserved.

PY - 2018/11/5

Y1 - 2018/11/5

N2 - Many cloud and shadow detection methods have been proposed already, but improvements can be made on accuracy or automation. In this study, we propose a Fully Convolutional Network model for the detection of clouds and shadows in optical satellite images. The proposed model was trained on 165 Landsat images in Finland, and tested on an independent set of images. The cloud and shadow detection accuracy reached 95%, outperforming both quantitatively and qualitatively a selection of other deep learning architectures.

AB - Many cloud and shadow detection methods have been proposed already, but improvements can be made on accuracy or automation. In this study, we propose a Fully Convolutional Network model for the detection of clouds and shadows in optical satellite images. The proposed model was trained on 165 Landsat images in Finland, and tested on an independent set of images. The cloud and shadow detection accuracy reached 95%, outperforming both quantitatively and qualitatively a selection of other deep learning architectures.

KW - Remote sensing

KW - Clouds

KW - Satellites

KW - Artificial satellites

KW - Earth

KW - Optical imaging

KW - Cloud and shadow masking

KW - optical images

KW - deep learning

KW - fully convolutional network

KW - Landsat

UR - http://www.scopus.com/inward/record.url?scp=85063150877&partnerID=8YFLogxK

U2 - 10.1109/IGARSS.2018.8517484

DO - 10.1109/IGARSS.2018.8517484

M3 - Conference article in proceedings

SN - 978-1-5386-7151-1

SP - 2107

EP - 2110

BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018

Y2 - 22 July 2018 through 27 July 2018

ER -

Molinier M, Reunanen N, Lämsä A , Astola H, Räty T. Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. IEEE Institute of Electrical and Electronic Engineers. 2018. p. 2107-2110. 8517484 doi: 10.1109/IGARSS.2018.8517484

Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this