基于多光谱与热红外数据融合的SDGSAT-1标准云检测算法*

doi:10.7523/j.ucas. 2025.053

中国科学院大学学报

• •

基于多光谱与热红外数据融合的SDGSAT-1标准云检测算法^*

李雪岩^1,2, 胡昌苗^1†

1.中国科学院空天信息创新研究院,北京,100094;
2.中国科学院大学电子电气与通信工程学院,北京,100049

收稿日期:2025-04-18 修回日期:2025-11-06 发布日期:2025-11-26
通讯作者: ^†E-mail: hucm@aircas.ac.cn
基金资助:
^*“十四五”民用航天技术预先研究项目（指南编号：D040404）; 中国科学院青年创新促进会（No. 2022127）; 中国科学院空天信息创新研究院“未来之星”人才计划（No. 2021KTYWLZX07）资助

Standardized cloud detection algorithm for SDGSAT-1 based on multispectral and thermal infrared data fusion

LI Xueyan^1,2, HU Changmiao¹

1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;
2. School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

Received:2025-04-18 Revised:2025-11-06 Published:2025-11-26

摘要/Abstract

摘要： 云层覆盖严重制约了遥感影像的观测与应用。包含云、云阴影、雪、水体、陆地5类地物的标准云检测作为遥感影像预处理的重要环节已在国内外主流卫星中广泛应用,然而SDGSAT-1作为可持续发展议程首发卫星,尚未提供标准的逐像素标记产品,限制了其数据的利用与共享。针对SDGSAT-1多光谱波段有限、易出现云雪混淆与云影水体混淆的问题,本文提出了一种多光谱与热红外数据融合的标准云检测方法,利用热红外波段中厚云低温特性提升云雪区分效果,融合GSWO与DEM数据辅助复杂背景识别,并结合形态学与导向滤波优化边界。实验结果表明,云检测IoU达74.33%,整体精度达85.09%。研究有效填补了SDGSAT-1标准云检测数据的空白,为后续数据的自动标注与高精度检测算法研发提供了重要支撑。

关键词: SDGSAT-1, 热红外影像, 标准云检测, 光谱阈值法

Abstract: Cloud cover seriously restricts the observation and application of remote sensing imagery. Standard cloud detection products, including five types of ground objects (clouds, cloud shadows, snow, water bodies, and land), are an important part of optical image preprocessing and have been widely used in mainstream satellites both domestically and internationally. However, SDGSAT-1, as the first satellite of the Sustainable Development Agenda (SDA), has not yet provided standard pixel-level labeled products, which restricts the utilization and sharing of its data. Aiming at the limitation that SDGSAT-1’s multispectral bands are few, making it prone to confusion between cloud-snow and cloud shadow-water, this paper proposes a standardized cloud detection method by fusing multispectral and thermal infrared (TIR) data. The method utilizes the low-temperature characteristics of thick clouds in the TIR band to enhance cloud-snow differentiation, incorporates GSWO and DEM data to assist in identifying complex backgrounds, and optimizes cloud mask boundaries using morphology and guided filtering. Experimental results show that the cloud detection IoU reaches 74.33% and the overall accuracy reaches 85.09%. The study effectively fills the gap in providing standard cloud detection products for SDGSAT-1 and provides important support for the development of automatic labeling and high-precision detection algorithms for subsequent data.

Key words: SDGSAT-1, TIR imagery, standardized cloud detection, spectral threshold method

中图分类号:

TP79

李雪岩, 胡昌苗. 基于多光谱与热红外数据融合的SDGSAT-1标准云检测算法^*[J]. 中国科学院大学学报, DOI: 10.7523/j.ucas. 2025.053.

LI Xueyan, HU Changmiao. Standardized cloud detection algorithm for SDGSAT-1 based on multispectral and thermal infrared data fusion[J]. Journal of University of Chinese Academy of Sciences, DOI: 10.7523/j.ucas. 2025.053.

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基于多光谱与热红外数据融合的SDGSAT-1标准云检测算法^*

Standardized cloud detection algorithm for SDGSAT-1 based on multispectral and thermal infrared data fusion

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