1. A method for detecting anomalies in agricultural land, the method comprising: computing first pixel statistics of pixels of a first hyperspectral image of agricultural land, the pixels within boundaries specified by field boundary data; generating a pixel mask using the first pixel statistics or historic anomalies; applying the pixel mask to the first hyperspectral image to generate a second hyperspectral image; forming groups of pixels of the second hyperspectral image using zone strata of the agricultural land; computing second pixel statistics using the groups of pixels of the second hyperspectral image; identifying a pixel clump within the second hyperspectral image using the second pixel statistics, the pixel clump representing an anomalous area within the agricultural land; predicting a source of anomaly of the pixel clump; and generating an anomaly map using the pixel clump and the predicted source of anomaly of the pixel clump.