基于随机森林分类器的Sentinel-2数据云量评估

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2020-09-26 DOI:10.1109/IGARSS39084.2020.9323683

Petteri Nevavuori, T. Lipping, Nathaniel G. Narra, Petri Linna

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引用次数: 1

摘要

提出了一种基于Sentinel-2卫星数据的云覆盖评估方法。该方法基于随机森林分类器，通过比较卫星数据和无人机数据计算的NDVI指标获得训练过程中使用的目标值。该方法在检测多云区域方面优于哨兵云概率掩模(CLDPRB)和场景分类(SCL)数据层。

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Assessment of Cloud Cover in Sentinel-2 Data Using Random Forest Classifier

In this paper, a novel cloud coverage assessment method for the Sentinel-2 data is presented. The method is based on the Random Forest classifier and the target values used in the training process are obtained by comparing the NDVI indexes calculated from the satellite and the UAV data. The developed method is shown to outperform the Sentinel Cloud Probability Mask (CLDPRB) and Scene Classification (SCL) data layers in detecting cloudy areas.

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IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium

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