Cloud detection based on high resolution stereo pairs of the geostationary meteosat images
Creators: name: Dehnavi, Sahar
name: Maghsoudi, Yasser
name: Zakšek, Klemen
name: Zoej, Mohammad Javad Valadan
name: Seckmeyer, Gunther
name: Skripachev, Vladimir
Publisher: name: Basel : MDPI AG
Year: 2020
Subjects: subject: Cloud detection
subject: Geostationary satellites
subject: Photogrammetry and remote sensing
subject: Stereography
subject: Computational electromagnetics
subject: Earth atmosphere
subject: Geometrical optics
subject: Image enhancement
subject: Matched filters
subject: Neurosurgery
subject: Pattern matching
subject: Pixels
subject: Remote sensing
subject: Constrained Energy Minimization
subject: Geometric relationships
subject: High resolution visible
subject: Meteosat second generations
subject: Receiver operating characteristics
subject: Spinning Enhanced Visible and Infrared Imager
subject: Stereo image processing
subject: Dewey Decimal Classification::500 | Naturwissenschaften::551 | Geologie, Hydrologie, Meteorologie

description: Due to the considerable impact of clouds on the energy balance in the atmosphere and on the earth surface, they are of great importance for various applications in meteorology or remote sensing. An important aspect of the cloud research studies is the detection of cloudy pixels from the processing of satellite images. In this research, we investigated a stereographic method on a new set of Meteosat images, namely the combination of the high resolution visible (HRV) channel of the Meteosat-8 Indian Ocean Data Coverage (IODC) as a stereo pair with the HRV channel of the Meteosat Second Generation (MSG) Meteosat-10 image at 0° E. In addition, an approach based on the outputs from stereo analysis was proposed to detect cloudy pixels. This approach is introduced with a 2D-scatterplot based on the parallax value and the minimum intersection distance. The mentioned scatterplot was applied to determine/detect cloudy pixels in various image subsets with different amounts of cloud cover. Apart from the general advantage of the applied stereography method, which only depends on geometric relationships, the cloud detection results are also improved because: (1) The stereo pair is the HRV bands of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) sensor, with the highest spatial resolution available from the Meteosat geostationary platform; and (2) the time difference between the image pairs is nearly 5 s, which improves the matching results and also decreases the effect of cloud movements. In order to prove this improvement, the results of this stereo-based approach were compared with three different reflectance-based target detection techniques, including the adaptive coherent estimator (ACE), constrained energy minimization (CEM), and matched filter (MF). The comparison of the receiver operating characteristics (ROC) detection curves and the area under these curves (AUC) showed better detection results with the proposed method. The AUC value was 0.79, 0.90, 0.90, and 0.93 respectively for ACE, CEM, MF, and the proposed stereo-based detection approach. The results of this research shall enable a more realistic modelling of down-welling solar irradiance in the future.