{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:38:17Z","timestamp":1760150297491,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T00:00:00Z","timestamp":1698969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971396","2019YFE0197800"],"award-info":[{"award-number":["41971396","2019YFE0197800"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["41971396","2019YFE0197800"],"award-info":[{"award-number":["41971396","2019YFE0197800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>We have developed an algorithm for cloud detection in Chinese GF-1\/6 satellite multispectral images, allowing us to generate cloud masks at the pixel level. Due to the lack of shortwave infrared and thermal infrared bands in the Chinese GF-1\/6 satellite, bright land surfaces and snow are frequently misclassified as clouds. To mitigate this issue, we utilized MODIS standard snow data products for reference data to determine the presence of snow cover in the images. Subsequently, our algorithm was utilized to correct misclassifications in snow-covered mountainous regions. The experimental area selected was the perpetually snow-covered Western mountains in the United States. The results indicate the accurate labeling of extensive snow-covered areas, achieving an overall cloud detection accuracy of over 91%. Our algorithm enables users to easily determine whether pixels are affected by cloud contamination, effectively improving accuracy in annotating data quality and greatly facilitating subsequent data retrieval and utilization.<\/jats:p>","DOI":"10.3390\/rs15215229","type":"journal-article","created":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T10:59:54Z","timestamp":1699009194000},"page":"5229","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Improving Cloud Detection in WFV Images Onboard Chinese GF-1\/6 Satellite"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-3976-0234","authenticated-orcid":false,"given":"Hao","family":"Chang","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Xin","family":"Fan","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Lianzhi","family":"Huo","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Changmiao","family":"Hu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/JPROC.2023.3238524","article-title":"Object Detection in 20 Years: A Survey","volume":"111","author":"Zou","year":"2023","journal-title":"Proc. IEEE"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"5832","DOI":"10.1109\/TGRS.2016.2572736","article-title":"Ship Detection in Spaceborne Optical Image with SVD Networks","volume":"54","author":"Zou","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","first-page":"5606216","article-title":"FactSeg: Foreground Activation-Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery","volume":"60","author":"Ma","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_4","first-page":"5603216","article-title":"Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images","volume":"60","author":"Chen","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3826","DOI":"10.1109\/TGRS.2012.2227333","article-title":"Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites","volume":"51","author":"King","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.14358\/PERS.72.10.1179","article-title":"Characterization of the Landsat-7 ETM+ automated cloud-cover assessment (ACCA) algorithm","volume":"72","author":"Irish","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.rse.2011.10.028","article-title":"Object-based cloud and cloud shadow detection in Landsat imagery","volume":"118","author":"Zhu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1628001","DOI":"10.3788\/AOS202040.1628001","article-title":"CDAG-Improved Algorithm and Its Application to GF-6 WFV Data Cloud Detection","volume":"40","author":"Dong","year":"2020","journal-title":"Acta Opt. Sin."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.isprsjprs.2016.12.005","article-title":"A cloud detection algorithm-generating method for remote sensing data at visible to short-wave infrared wavelengths","volume":"124","author":"Sun","year":"2017","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_10","first-page":"760","article-title":"Stream-computing Based High Accuracy On-board Real-time Cloud Detection for High Resolution Optical Satellite Imagery","volume":"47","author":"Wang","year":"2018","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1016\/j.rse.2017.01.026","article-title":"Multi-feature combined cloud and cloud shadow detection in GaoFen-1 wide field of view imagery","volume":"191","author":"Li","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_12","first-page":"623","article-title":"Research on multispectral satellite image cloud and cloud shadow detection algorithm of domestic satellite","volume":"27","author":"Hu","year":"2023","journal-title":"J. Remote Sens."},{"key":"ref_13","first-page":"6","article-title":"A review of cloud detection methods in remote sensing images","volume":"29","author":"Liu","year":"2017","journal-title":"Remote Sens. Land Resour."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4062","DOI":"10.1109\/TGRS.2018.2889677","article-title":"Cloud Detection in Remote Sensing Images Based on Multiscale Features-Convolutional Neural Network","volume":"57","author":"Shao","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1016\/j.neunet.2021.08.008","article-title":"Refined UNet v3: Efficient end-to-end patch-wise network for cloud and shadow segmentation with multi-channel spectral features","volume":"143","author":"Jiao","year":"2021","journal-title":"Neural Netw."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.isprsjprs.2019.02.017","article-title":"Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors","volume":"150","author":"Li","year":"2019","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1600","DOI":"10.1109\/LGRS.2018.2846802","article-title":"Cloud and Cloud Shadow Detection Using Multilevel Feature Fused Segmentation Network","volume":"15","author":"Yan","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"doi-asserted-by":"crossref","unstructured":"Yu, J., Li, Y., Zheng, X., Zhong, Y., and He, P. (2020). An Effective Cloud Detection Method for Gaofen-5 Images via Deep Learning. Remote Sens., 12.","key":"ref_18","DOI":"10.3390\/rs12132106"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0034-4257(02)00034-2","article-title":"An image transform to characterize and compensate for spatial variations in thin cloud contamination of Landsat images","volume":"82","author":"Zhang","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.1109\/TPAMI.2012.213","article-title":"Guided Image Filtering","volume":"35","author":"He","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"unstructured":"Viola, P., and Jones, M. (2001, January 8\u201314). Rapid object detection using a boosted cascade of simple features. Proceedings of the Conference on Computer Vision and Pattern Recognition, Kauai, HI, USA.","key":"ref_21"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"084689","DOI":"10.1117\/1.JRS.8.084689","article-title":"Extraction and assessment of snowline altitude over the Tibetan plateau using MODIS fractional snow cover data (2001 to 2013)","volume":"8","author":"Tang","year":"2014","journal-title":"J. Appl. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1007\/s12524-016-0617-y","article-title":"Spatial and Temporal Variation Analysis of Snow Cover Using MODIS over Qinghai-Tibetan Plateau during 2003\u20132014","volume":"45","author":"Zhang","year":"2017","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1534","DOI":"10.1002\/hyp.6715","article-title":"Accuracy assessment of the MODIS snow products","volume":"21","author":"Hall","year":"2007","journal-title":"Hydrol. Process."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.rse.2003.10.016","article-title":"Estimating fractional snow cover from MODIS using the normalized difference snow index","volume":"89","author":"Salomonson","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1497","DOI":"10.1016\/j.rse.2007.05.016","article-title":"Evaluation of MODIS snow cover and cloud mask and its application in Northern Xinjiang, China","volume":"112","author":"Wang","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/S0034-4257(02)00095-0","article-title":"MODIS snow-cover products","volume":"83","author":"Hall","year":"2002","journal-title":"Remote Sens. Environ. Interdiscip. J."},{"unstructured":"He, L., Qin, Q.M., Meng, Q.Y., and Du, C. (2012, January 1\u20132). Simulation of Remote Sensing Images Using High-Resolution Data and Spectral Libraries. Proceedings of the 4th International Conference on Environmental Science and Information Application Technology (ESIAT 2012), Bali, Indonesia.","key":"ref_28"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"S19","DOI":"10.1175\/BAMS-D-16-0154.1","article-title":"The 2014\/15 snowpack drought in washington state and its climate forcing","volume":"97","author":"Fosu","year":"2016","journal-title":"Bull. Am. Meteorol. Soc."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/21\/5229\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:16:39Z","timestamp":1760130999000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/21\/5229"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,3]]},"references-count":29,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["rs15215229"],"URL":"https:\/\/doi.org\/10.3390\/rs15215229","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,11,3]]}}}