Predictive Crop Analytics for Global Agriculture


A weekly map series that monitors crop and vegetation conditions and change for the U.S.

GreenReport® map sets can be used like any crop report that describes regional crop conditions. The advantage of displaying crop information (derived from satellite data) in map form is that the precise locations of growing events can be identified. The GreenReport® combines current satellite data with historic data to present a more complete picture of crop condition and progress. GreenReport® map sets can accurately show areas were crops are progressing or doing poorly from one period to the next, and can compare crop progress and condition to the previous year and to average conditions. When used together, the map sets can be used as a tool for understanding crop development throughout the growing season and from year to year.

Much speculation about crop condition is based upon weather reports. Interpretations of weather events influence commodity prices and trading practices. Using the GreenReport®, we can actually “see” how plants respond to environmental conditions and changes. Satellite imagery shows plant condition and state of development (see the Greenness Map). When the current map is compared to the previous week (see Difference Map 1), vegetation changes can be observed. When the current map is compared to the map from last year for the same period (see Difference Map 2), the condition and state of development is known in relation to the previous year. When the current map is compared to an average (see Difference Map 3), the condition and state of development is known in relation to the average. When all four maps are viewed, a complete understanding of crop condition and development can be achieved. Instead of trying to “guess” what weather events will do to a crop, let the GreenReport® show you how the plants respond.

The GreenReport® uses the term “Greenness” in describing plant conditions. In these reports, greenness is directly related to the amount of green plant material (biomass) that is actively producing chlorophyll. The Vegetation Index Greenness Map assigns values to greenness depending on the amount of green biomass within the view of the satellite sensor. In the case of Difference Map 1, areas of increased greenness indicate areas where plants are growing and adding biomass. Decreased greenness indicates areas where plants are browning, or are producing less chlorophyll than during the previous period. Increased greenness in Difference Map 2 indicates areas where the plants are more developed during the time period this year when compared to the past year, as decreased greenness indicates that development is behind last years rate. DM3 is used in the same manner to determine what areas are behind, equal to, or ahead of the average in development.

Using Remote Sensing to Measure Biomass

NDVI (Normalized Difference Vegetation Index) is calculated from the visible and near-infrared light reflected by vegetation in the satellite images.   Healthy vegetation (left) absorbs most of the visible light that hits it and reflects a large portion of the near-infrared light. Unhealthy, senescing or sparse vegetation (right) reflects more visible light and less near-infrared light. The numbers on the figure to the right are representative of actual values, but real vegetation is much more varied.

The NDVI (“Greenness”) that can be computed for each 1 sq km map pixel is
highly correlated with photosynthetically active vegetation (Green biomass). 
Areas with higher NDVI values have greater amounts of green biomass.