基于MODIS的云量检测方法研究

Cloud Cover Detection Based on MODIS

云量对于光学遥感影像质量有着重要影响，在一定程度上制约了光学遥感影像的应用。传统云检测方法通常无法准确检查出冰雪与云的区别，对薄云、碎云和云边缘的识别率不高。针对上述问题，本文研究了基于先验地表反射率数据支持的云检测方法，在云检测动态阈值模型的构建过程中，使用MODIS（moderate-resolution imagingspec—troradiometer）地表反射率数据作为先验地表反射率数据，并基于辐射传输模型在多种条件下进行模拟，设置动态云检测阈值识别云像元。通过实验，验证了这种方法能够有效避开混合像元对云检测能力的影响，提高云量检测的准确率。

Cloud cover has an important effect on the quality of optical remote sensing images, and it restricts the applica- tion of optical images to a certain extent. Traditional cloud detection methods can hardly distinguish between snow and cloud, nei- ther identify the thin cloud, fractus and the cloud edge with high precision. In order to solve these problems, the cloud detection method based on the prior surface reflectivity data is studied in this paper. The MODIS surface reflectivity is used as prior surface reflectivity data in stimulating the dynamic threshold model of cloud detection, and the dynamic detection threshold is set to iden- tify the cloud pixel. The experiment resuh proves that the method can effectively avoid the effect of mixed pixel on cloud detection capability and improve the accuracy of cloud cover detection.