Wide-area agricultural monitoring and prediction
Ground-based measurements of agricultural metrics such as NDVI are used to calibrate wide-area aerial measurements of the same metrics. Calibrated wide-area data may then be used as an input to a field prescription processor.
1 . A method for calibrating agricultural measurements comprising:
obtaining aerial data representing relative measurements of an agricultural metric in a geographic area, the relative measurements having an unknown bias;
obtaining ground-based data representing absolute measurements of the agricultural metric within the geographic area; and,
using the absolute measurements to calibrate the relative measurements, thereby synthesizing absolute measurements of the agricultural metric in parts of the geographic area.
2 . The method of claim 1 , the aerial data obtained from a satellite.
3 . The method of claim 1 , the aerial data obtained from an airplane.
4 . The method of claim 1 , the agricultural metric being normalized difference vegetative index.
5 . The method of claim 1 , the agricultural metric being a reflectance-based vegetative index.
6 . The method of claim 1 further comprising: combining data representing the ground-based and synthesized absolute measurements with additional spatial agricultural data to generate a prescription for the application of chemicals to an agricultural field.
7 . The method of claim 6 , the additional spatial agricultural data being a soil data map.
8 . The method of claim 6 , the additional spatial agricultural data being a crop data map.
9 . The method of claim 6 , the additional spatial agricultural data being climate data.
10 . The method of claim 6 , the chemicals being fertilizers.
11 . The method of claim 6 , the chemicals being pesticides or herbicides.
12 . The method of claim 6 , the prescription based on an agricultural algorithm having an agricultural metric and climate data as inputs.
13 . The method of claim 12 , the agricultural metric being normalized difference vegetative index and the climate data including growing degree days since planting.
14 . The method of claim 1 , the synthesizing absolute measurements including using a plant growth model to propagate ground-based data forward or backward in time as needed to compare it with non-contemporaneous satellite data.
15 . The method of claim 14 , the plant growth model being a linear model.
16 . A system for making calibrate agricultural measurements comprising:
a source of aerial data representing relative measurements of an agricultural metric in a geographic area, the relative measurements having an unknown bias;
a source of ground-based data representing absolute measurements of the agricultural metric within the geographic area; and,
a database and processor that use the absolute measurements to calibrate the relative measurements, thereby synthesizing absolute measurements of the agricultural metric in parts of the geographic area.
17 . The system of claim 16 , the aerial data obtained from a satellite.
18 . The system of claim 16 , the aerial data obtained from an airplane.
19 . The system of claim 16 , the agricultural metric being normalized difference vegetative index.
20 . The system of claim 16 , the agricultural metric being a reflectance-based vegetative index.
21 . The system of claim 16 , the database and processor further combining data representing the ground-based and synthesized absolute measurements with additional spatial agricultural data to generate a prescription for the application of chemicals to an agricultural field.
22 . The system of claim 16 , the additional spatial agricultural data being a soil data map.
23 . The system of claim 15 , the additional spatial agricultural data being a crop data map.
24 . The system of claim 16 , the additional spatial agricultural data being climate data.
25 . The system of claim 16 , the chemicals being fertilizers.
26 . The system of claim 16 , the chemicals being pesticides or herbicides.
27 . The system of claim 16 , the prescription based on an agricultural algorithm having an agricultural metric and climate data as inputs.
28 . The system of claim 27 , the agricultural metric being normalized difference vegetative index and the climate data including growing degree days since planting.
29 . The system of claim 16 , the synthesizing absolute measurements including using a plant growth model to propagate ground-based data forward or backward in time as needed to compare it with non-contemporaneous satellite data.
30 . The system of claim 16 , the plant growth model being a linear model.