| Title | A cloud detection algorithm for AATSR data, optimized for daytime observations in Canada |
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| Author | Knudby, A; Latifovic, R; Pouliot, D |
| Source | Remote Sensing of Environment vol. 115, no. 12, 2011 p. 3153-3164, https://doi.org/10.1016/j.rse.2011.07.001 |
| Year | 2011 |
| Alt Series | Natural Resources Canada, Contribution Series 20181526 |
| Publisher | Elsevier BV |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | geophysics; remote sensing |
| Program | Canada Centre for Remote Sensing Divsion |
| Released | 2011 12 01 |
| Abstract | To extract information about the Earth's surface from Earth Observation data, a key processing step is the separation of pixels representing clear-sky observations of land or water surfaces from
observations substantially influenced by clouds. This paper presents an algorithm used for this purpose specifically for data from the AATSR sensor on ENVISAT. The algorithm is based on the structure of the SPARC cloud detection scheme developed at
CCRS for AVHRR data, then modified, calibrated and validated for AATSR data. It uses a series of weighted tests to calculate per-pixel cloud presence probability, and also produces an estimate of cloud top height and a cloud shadow flag. Algorithm
parameters have been optimized for daytime use in Canada, and evaluation shows good performance with a mean daytime kappa coefficient of 0.76 for the 'cloud'/'clear' classification when compared to independent validation data. Performance is
independent of season, and is a dramatic improvement over the existing AATSR L1B cloud flag for Canada. The algorithm will be used at CCRS for processing AATSR data, and will form the basis of similar processing for data from the SLSTR sensors on
Sentinel-3. |
| GEOSCAN ID | 311881 |
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