Automatic crop health change detection and alerting system
摘要
說明書
To mitigate potential differences in VI values from one image to the next, unrelated to changes in field conditions, the image processing module 123 may also compute normalized vegetation index products from the earlier calculated vegetation index images. These images normalize the individual pixel values within a given VI image based on a statistical measure of central tendency (i.e., the mean or median value). For example, a normalized NDVI image may be computed by the image processing module 123 as follows: NormNDVI=NDVIpixel?NDVImedian??(2) where NormNDVI is the normalized NDVI value for a given pixel, NDVIpixel is the original NDVI value for the pixel, and NDVImedian is the median NDVI value for the entire NDVI image.
The use of normalized VI images for the change detection phase can help to compensate for increases and decreases in the VI values between one image and the next due to issues including regular crop growth cycles, differences in atmospheric conditions, and differences in remote sensor calibration.
The final derivative that may be produced by the image processing module 123 is a classified normalized VI image. This makes use of a classification scheme to break the continuous normalized VI pixel values into discrete classes. In an example embodiment, the classification scheme may appear as in Table 1:
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