Classification of Cloud Types Based on Spatial Textural Measures Using Noaa-Avhrr Data

The United States Navy has a requirement for real time cloud analysis and classification as part of a nowcasting capability. The use of texture me asures in addition to standard Advanced Very High Resolution Radiometer (AVHRR) channel radiances is explored to provide an improved cloud analysis. Nowcasting delivers a very short term (2 to 4 hours) weather forecast for operational use. Therefore, speed and accuracy of computation are both critical. This research effort resulted in the development of multi-spectral textural cloud type detection algorithm. Several statistical textural measures were investigated in order to select the most appropriate subset of textures suitable for cloud classification. The algorithm was tested on a NOAA-AVHRR data set over the Pacific ocean near the coast of California.

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