Spatial Feature Reconstruction of Cloud-Covered Areas in Daily MODIS Composites

Spatial Feature Reconstruction of Cloud-Covered Areas in Daily MODIS Composites

Blog Article

The 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 read more 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 weleda skin food 75ml best price 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%.