Wide-area agricultural monitoring and prediction

Abstract

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.