Intelinair Director of Machine Learning Jennifer Hobbs recently contributed to the ODSC Speakers’ blog in advance of the ODSC East 2022 conference on April 19 – 21. In the blog, Jennifer shares how deep learning and remote sensing are creating unprecedented opportunities for precision agriculture.
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Crop dry down detection analytics indicate the field has started to dry down based on Aerial RGB image turning brown.
Analytics show lower plant biomass compared to other parts of the field which may be indicative of crop health concerns. Causes may include, but not limited to, nutrient deficiency, pest pressure, or drought.
Analytics indicate low crop vigor and leaf discoloration which is an indicator of nutrient deficiency.
Thermal imagery and weather patterns detect potential disease risk in the field.
Thermal imagery detects elevated heat patterns which can be indicative of crop stress.
Analytics show lower plant biomass compared to other parts of the field which may be indicative of crop health concerns. Causes may include, but not limited to, nutrient deficiency, pest pressure, or drought.
Plant material believed to be weeds is marked according to density on the Weed Map. If a field has recently been sprayed with herbicide per available machine data and there are weeds detected, an alert will trigger a notification.
Plant material believed to be weeds is marked according to density on the Weed Map. If a field has recently been sprayed with herbicide per available machine data and there are weeds detected, an alert will trigger a notification.
Infrared imagery shows missing plants or low biomass, which may indicate poor emergence.
