Understanding the crop cycle shift across years using Image Processing and Remote Sensing…

Have you ever experienced using a particular year for crop signature analysis and the minute you extend that analysis to a different year, it fails to provide the same insights or you just cannot replicate the results you had derived from the above experiment? I have been working on a machine learning model for a specific Region of Interest, where pixel level annotated data of the crop corn was picked for the year 2019 for specific dates and a model was trained for the same. While doing this exercise, I was presented with a unique problem. While using a particular year for crop signature analysis, the moment I extended the analysis to a different year, the model failed to provide the same insights and I just could not replicate the results I had derived from the above experiment. When the single pixel classifier model was used to predict pixels for the same year, the f1 score for out of sample data was remarkable.