I'm doing an extraction of spectral trajectories for disturbed forest pixels using multitemporal (single scene for 20 years) Landsat Surface Reflectance products.
Usually, forest disturbances are detected using automated algorithms (mainly Landtrend for Landsat data) and statistic validation of the results is done using confusion matrix (overall accuracy ecc.), Kappa, Pearson correlation and similar methods.
In my case, the disturbed pixels are identified by visual interpretation (so they can be classified as ground truth data) and no predicting algorithm is used. I'm only extracting the pixel values and plotting them along the temporal series.
My question is: after noise removal (outliers detection, data cleaning filters ecc.), how can I tell how accurate the trajectories obtained from the pixel values are?