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SNOW AND CLOUD DISCRIMINATION USING CONVOLUTIONAL NEURAL NETWORKS
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
<p><strong>Abstract.</strong> Snow is an important feature on our planet, and measuring its extent has advantages in climate studies. Snow mapping through satellite remote sensing is often affected by cloud cover. This issue can be resolved by using short wave infrared (SWIR) sensors. In order to obtain an effective cloud mask, our study aims to use SWIR data of a ResourceSat-2 satellite. We employ Convolutional Neural Networks (CNN) to discriminate similar pixels of clouds and snow. Thedoi:10.5194/isprs-annals-iv-5-59-2018 fatcat:cjtzjjhoenb55g4lmj7je52u7y