Reinke, Donald L., authorAzimi-Sadjadi, Mahmood R., authorSaitwal, Kishor, authorIEEE, publisher2007-01-032007-01-032003Saitwal, Kishor, Mahmood R. Azimi-Sadjadi, and Donald Reinke, A Multichannel Temporally Adaptive System for Continuous Cloud Classification from Satellite Imagery, IEEE Transactions on Geoscience and Remote Sensing 41, no. 5 (May 2003): 1098-1104.http://hdl.handle.net/10217/845A two-channel temporal updating system is presented, which accounts for feature changes in the visible and infrared satellite images. The system uses two probabilistic neural network classifiers and a context-based predictor to perform continuous cloud classification during the day and night. Test results for 27 h of continuous classification and updating are presented on a sequence of Geostationary Operational Environmental Satellite 8 images. Further test results of the system on two new sets of data with 1-2 weeks time difference are also presented that show the potential of this system as an operational continuous cloud classification system.born digitalarticleseng©2003 IEEE.Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.probabilistic neural networksmultispectral satellite imagingcloud classificationText