ASSESSMENT OF CLOUD COVER IN SENTINEL-2 DATA USING RANDOM FOREST CLASSIFIER

被引：0
|
作者：
Nevavuori, P. [1 ]
Lipping, T. [2 ]
Narra, N. [2 ]
Linna, P. [2 ]
机构：
[1] Mtech Digital Solut Oy, Vantaa, Finland
[2] Tampere Univ, Tampere, Finland
来源：
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年
关键词：
Cloud coverage; Random Forest classifier; Crop monitoring;
D O I：
10.1109/IGARSS39084.2020.9323683
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：4661 / 4664
页数：4
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