A computer-implemented method for generating an improved map of field anomalies using digital images and machine learning models is disclosed. In an embodiment, a method comprises: obtaining a shapefile that defines boundaries of an agricultural plot and boundaries of the field containing the plot； obtaining a plurality of plot images within the field from one or more image capturing devices that are located within the boundaries of the field； calibrating and pre-processing the plurality of plot images to create a plot map of the agricultural plot at a plot level； based on the plot map of the agricultural plot, generating a plot grid； based on the plot grid and the plot map, generating a plurality of plot tiles； based on the plurality of plot tiles, generating, using a first machine learning model and a plurality of first image classifiers corresponding to one or more first anomalies, a set of classified plot images that depicts at least one anomaly； based on the set of classified plot images, generating a plot anomaly map for the agricultural plot； transmitting the plot anomaly map to one or more controllers that control one or more agricultural machines or database systems to perform agricultural functions on the agricultural plot.
