Fine-Tuning Self-Organizing Maps for Sentinel-2 Imagery: Separating Clouds from Bright Surfaces
Removal of cloud interference is a crucial step for the exploitation of the spectral information stored in optical satellite images. Several cloud masking approaches have been developed through time, based on direct interpretation of the spectral and temporal properties of clouds through thresholds....
Main Authors: | Viktoria Kristollari, Vassilia Karathanassi |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-06-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/12/12/1923 |
Similar Items
-
Oil Spill Detection and Mapping Using Sentinel 2 Imagery
by: Polychronis Kolokoussis, et al.
Published: (2018-01-01) -
Comment on “Comparison of Cloud Cover Detection Algorithms on Sentinel-2 Images of the Amazon Tropical Forest”
by: Olivier Hagolle, et al.
Published: (2021-03-01) -
Comparison of cloud detection algorithms for Sentinel-2 imagery
by: Katelyn Tarrio, et al.
Published: (2020-12-01) -
Comparison of Masking Algorithms for Sentinel-2 Imagery
by: Viktoria Zekoll, et al.
Published: (2021-01-01) -
An automated system for program parameters fine tuning in the cloud
by: S. A. Smirnov, et al.
Published: (2015-06-01)