Near Real Time Processing of NOAA AVHRR Satellite Data

This thesis describes near real time processing of NOAA AVHRR satellite raw data which includes automatic geocoding approach followed by cloud masking techniques and sea surface temperature extraction algorithm implemented over South China Sea. For geocoding of the images an orbital model has been used followed by Earth location determination algorithms. Different models have been implemented based on radiative transfer equations for extracting sea surface temperature fro m satellite data, namely single channel, split-window, spatiotemporal split-window technique and multichannel sea surface temperature. There are five cloud masking techn iques namely gross cloud check, spatial coherence method, dynamic visible and near infrared method, ratio of near infrared reflectance to visible reflectance and channel difference method have been implemented. The accuracy of the geocoding is within 2-10 km. Sea surface temperature from satellite data has been compared with ground truth data and standard deviation for sea surface temperature is within 0.1 - 0.75 degree Celsius. The cloud masking techniques are capable to produce non contaminated pixels in the imagery. All the works have been carried out by customization of EASI/PACE environment of PCI software and the developed techniques are fully automatic in nature. These developments can be used for fish forecasting and monitoring of oil spill over Malaysian sea water.

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