Tag Archives: FY-2E

Rainfall Estimation Using Artificial Neuron Networks (ANNs) and FY-2E Satellite Image in Thailand

The objectives of this research were to estimate the brightness temperature from remotely sensed data as FY-2E satellite, and to evaluate rainfall amount by using Artificial Neural Networks (ANNs) model that require brightness temperature for assessment. The percentage error and root of the mean square error (RMSE) were employed to calibration and validation approach. The data were compiled during 1 ... Read More »