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高分四号卫星数据云和云阴影检测算法

Cloud and Cloud Shadow Detection Algorithm for Gaofen-4 Satellite Data

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摘要

高分四号卫星(GF-4)是我国研制的首颗地球同步高分辨率光学成像卫星, 具有高时间分辨率和较高的空间分辨率。针对高分四号卫星数据的特点, 提出了一种光谱分析与几何算法相结合的云和云阴影检测算法。使用几何校正和辐射定标后的高分四号影像, 基于云与典型地表的光谱特征, 采用光谱差异分析技术识别出潜在云像元, 根据有云地物和无云地物的光谱变化率差异计算云概率; 由云和云阴影的几何关系, 并结合传感器参数识别云阴影的投影带, 然后根据阴影的光谱特征在投影带中设定基于影像的动态阈值, 用于检测云阴影。该算法能较好地识别薄云, 而且可以显著提高云阴影的检测精度。采用目视解译法对检测精度进行验证后发现, 不同区域类型的云像元识别位置准确, 形状完整; 将所提云阴影检测方法与云和云阴影匹配算法进行对比后发现, 前者识别的云阴影更为精确。

Abstract

Gaofen-4 (GF-4) satellite is the first geosynchronous high-resolution optical imaging satellite developed by China, and it has high temporal resolution and high spatial resolution. Aiming at the characteristics of GF-4 satellite data, we propose a cloud and cloud shadow detection algorithm combining spectral analysis and geometrical algorithms. Geometrically corrected and radiometrically calibrated GF-4 images are used to identify potential cloud pixels using spectral difference analysis techniques based on the spectral characteristics of clouds and typical land surfaces. The cloud probability is calculated according to the difference of spectral variability rate of clouds and cloudless features. The geometrical relationship between clouds and cloud shadows is combined with the sensor parameters to identify the projective regions of cloud shadows. Then the image-based dynamic thresholds are set in the projection regions based on the spectral characteristics of the shadows to detect cloud shadows. This algorithm can better identify thin clouds, and significantly improve the cloud shadow detection accuracy. The visual interpretation method is used to verify the detection accuracy. It finds that cloud pixels recognition in different regions are more accurate and the shapes are relatively complete. Compared with the method of cloud and cloud shadow matching, the dynamic-spectral-threshold algorithm proposed in this paper is more accurate in detecting cloud shadows.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TP701

DOI:10.3788/aos201939.0128001

所属栏目:遥感与传感器

基金项目:国家自然科学基金(41771408)、山东省自然科学基金(ZR201702210379)

收稿日期:2018-06-21

修改稿日期:2018-07-31

网络出版日期:2018-08-17

作者单位    点击查看

刘心燕:山东科技大学测绘科学与工程学院, 山东 青岛 266510
孙林:山东科技大学测绘科学与工程学院, 山东 青岛 266510
杨以坤:山东科技大学测绘科学与工程学院, 山东 青岛 266510
周雪莹:山东科技大学测绘科学与工程学院, 山东 青岛 266510
王权:山东科技大学测绘科学与工程学院, 山东 青岛 266510
陈婷婷:山东科技大学测绘科学与工程学院, 山东 青岛 266510

联系人作者:孙林(sunlin6@126.com)

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引用该论文

Liu Xinyan,Sun Lin,Yang Yikun,Zhou Xueying,Wang Quan,Chen Tingting. Cloud and Cloud Shadow Detection Algorithm for Gaofen-4 Satellite Data[J]. Acta Optica Sinica, 2019, 39(1): 0128001

刘心燕,孙林,杨以坤,周雪莹,王权,陈婷婷. 高分四号卫星数据云和云阴影检测算法[J]. 光学学报, 2019, 39(1): 0128001

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