Spatial Feature Reconstruction of Cloud-Covered Areas in Daily MODIS Composites
AbstractThe opacity of clouds is the main problem for optical and thermal space-borne sensors, like the Moderate-Resolution Imaging Spectroradiometer (MODIS). Especially during polar nighttime, the low thermal contrast between clouds and the underlying snow/ice results in deficiencies of the MODIS cloud mask and affected products. There are different approaches to retrieve information about frequently cloud-covered areas, which often operate with large amounts of days aggregated into single composites for a long period of time. These approaches are well suited for static-nature, slow changing surface features (e.g., fast-ice extent). However, this is not applicable to fast-changing features, like sea-ice polynyas. Therefore, we developed a spatial feature reconstruction to derive information for cloud-covered sea-ice areas based on the surrounding days weighted directly proportional with their temporal proximity to the initial day of interest. Its performance is tested based on manually-screened and artificially cloud-covered case studies of MODIS-derived polynya area data for the polynya in the Brunt Ice Shelf region of Antarctica. On average, we are able to completely restore the artificially cloud-covered test areas with a spatial correlation of 0.83 and a mean absolute spatial deviation of 21%. View Full-Text
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Paul, S.; Willmes, S.; Gutjahr, O.; Preußer, A.; Heinemann, G. Spatial Feature Reconstruction of Cloud-Covered Areas in Daily MODIS Composites. Remote Sens. 2015, 7, 5042-5056.
Paul S, Willmes S, Gutjahr O, Preußer A, Heinemann G. Spatial Feature Reconstruction of Cloud-Covered Areas in Daily MODIS Composites. Remote Sensing. 2015; 7(5):5042-5056.Chicago/Turabian Style
Paul, Stephan; Willmes, Sascha; Gutjahr, Oliver; Preußer, Andreas; Heinemann, Günther. 2015. "Spatial Feature Reconstruction of Cloud-Covered Areas in Daily MODIS Composites." Remote Sens. 7, no. 5: 5042-5056.