I'd like to smooth an NDVI image by regression analysis; response of time series NDVI image to Julian date to represent the seasonal changes in NDVI as a function of Julian day. The time series NDVI image has 26 bands (8-day images during April to October) and 12618/4144 col/row. I have chosen 30 point samples in each land cover (30 x 5 LC=150) from all band of time series NDVI image using stratified random sampling method. I need to discuss my further steps with you all.
Do I need to run the regression for each sample point (150 samples) and calculate regression equation extracted from step, 1 in each point sample (one by one) again to reproduce predicted NDVI image?
Is there any method to simplify these processes to save time?
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