Real World Analysis

The cluster of fields in this image is in Andhra Pradesh, just north west of South of India It is believed to be growing rice. This application works accurately across a large variety of crops allowing for accurate results across the board!

Yield variation in these fields can clearly be seen and accurately measured. Through this image alone it is made clear which fields are the highest performing (green) and which are lowest (red). Using yield data from previous years this 0-1 scale can be turned into an accurately estimated yield for each field. Lagging fields can be identified and management practices can be improved to increase the nation wide food production. This analysis was done for 2019 in July, but in practice would be applied to crops as they are growing to predict yield and identify deficiencies.

In-Field Issue Detection

This image is using the Vegetation health algorithm which measures the chlorophyll content of crops and identifies in field variation. It is a good proxy for future yield and biomass in the area. This algorithm is also used to identify pests and disease that are affecting the canopy.

The field below from Andhra Pradesh clearly shows a lack of development in the middle of the field. This could be from pests or more likely a region with excessive water that was not properly removed after draining the field, i.e. drainage issue.

Composite shot of the geotagged field

AIS Analysis and reporting process

Monitor crop vitality in real time
  • NDVI that catches disease and pest outbreaks as they happen
  • Industry standard, yet directly linked to our other algorithms to create an unmatched synergy.