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The Indigo Ag Crop Health Index (IA CHI) and Normalized Difference Vegetation Index (NDVI) are satellite-based scores of plant condition and progress that can help commodities researchers understand the status of a given crop. In both cases, they are unitless measures, meaning that the number is valuable for comparisons (e.g. whether it is above or below average, what direction it is moving, etc.) but not in absolute terms (e.g. 10 kernels).
IA CHI is a score developed by Indigo Ag specifically for use in modelling crop yield. The formula for the index uses certain reflectance values picked up by NASA and European Space Agency (ESA) satellites. Indigo Ag generates scores on a daily basis and summarize for states or countries.
NDVI is a more widely used score for measuring vegetation from space. While not specific to agriculture, it has been increasingly used by the agricultural community as a proxy for the visible health of crops. While typical NDVI is calculated by looking at all pixels in a given area (e.g. all the pixels in Iowa or the United States), Indigo Ag’s NDVI is masked by crop.
CHI is calibrated specifically for agriculture and crop modelling, whereas NDVI is a more general plant health metric used for myriad academic purposes. NDVI is more generally known and some users may find it more familiar, though they have almost certainly not consumed NDVI in crop-masked form.
Because Indigo Ag has a map of where individual crops are grown, the metrics only look at pixels planted for a specific crop. So, IA CHI Corn for Iowa will only show the CHI for the corn pixels in that state. IA NDVI Soy for Córdoba, Argentina will only show the NDVI for soy pixels in Córdoba, Argentina.
Typical satellite-based indexes are produced every eight days. Indigo Ag sources its imagery from newer NASA products which allow it to provide CHI and NDVI values on a daily basis.
Agriculture markets have been using weather data for analysis since ancient Sumeria. Both data products are effective tools to aid researchers and traders seeking a satellite-based, or optical, complement to weather data in their analysis.