Integrated remote sensing tools for timely predictions of crop quality and yield

Abstract

A method includes receiving outside temperatures for a plurality of days and calculating growing degree units based on the received temperatures. Intensities for a plurality of wavelengths of light measured over at least one portion of a field containing a crop are received and are used with the growing degree units to predict a quality value for the crop. The predicted quality value for the crop is then displayed.

What is claimed is: 
     
         1 . A method comprising:
 receiving outside temperatures for a plurality of days;   calculating growing degree units based on the received temperatures;   receiving intensities for a plurality of wavelengths of light measured over at least one portion of a field containing a crop;   using the intensities and the growing degree units to predict a quality value for the crop; and   displaying the predicted quality value for the crop.   
     
     
         2 . The method of  claim 1  further comprising using the intensities and the growing degree units to predict a yield for the crop and displaying the yield for the crop. 
     
     
         3 . The method of  claim 1  wherein receiving outside temperatures for a plurality of days comprises receiving a maximum temperature for each day since a last harvest of the crop. 
     
     
         4 . The method of  claim 3  wherein receiving outside temperatures further comprises receiving a predicted maximum temperature for at least one day in the future. 
     
     
         5 . The method of  claim 1  wherein using the intensities for the plurality of wavelengths comprises grouping at least some of the wavelengths into a waveband and averaging intensities of wavelengths in the waveband to form an intensity for the waveband. 
     
     
         6 . The method of  claim 1  further comprising receiving images of the crop and using the images to determine a height of the crop and wherein using the intensities and the growing degree units to predict the quality value for the crop further comprises using the height of the crop with the intensities and the growing degree units to predict the quality value for the crop. 
     
     
         7 . The method of  claim 6  wherein using the images to determine the height of the crop comprises performing structure-from-motion processing on the images to determine the height. 
     
     
         8 . A computing device comprising:
 a memory containing instructions; and   a processor executing the instructions in the memory to perform steps comprising:   receiving a respective weather value for each of a plurality of days;   receiving intensity values for a plurality of wavebands of light detected over a field containing a crop; and   using the weather values and the intensity values to determine a predicted yield for the crop.   
     
     
         9 . The computing device of  claim 8  wherein receiving a weather value comprises receiving a combination of past weather values and future weather values. 
     
     
         10 . The computing device of  claim 9  wherein receiving a weather value comprises receiving a temperature for each of the plurality of days. 
     
     
         11 . The computing device of  claim 10  wherein using the weather values to determine the predicted yield comprises choosing a date and using the received temperatures for all days between a last harvest date and the chosen date to determine growing degree units between the two dates and using the growing degree units to determine the predicted yield on the chosen date. 
     
     
         12 . The computing device of  claim 11  wherein the chosen date is a future date. 
     
     
         13 . The computing device of  claim 8  further comprising receiving an indication of a height of the crop and wherein using the weather values and the intensity values to determine the predicted yield for the crop further comprises using the indication of the height with the weather values and the intensity values to determine the predicted yield for the crop. 
     
     
         14 . The computing device of  claim 8  further comprising using the weather values and the intensity values to determine a predicted quality measure for the crop. 
     
     
         15 . A method comprising:
 using an unmanned aerial vehicle having at least one light sensor to collect light intensity values for a plurality of wavelengths of light above a crop;   receiving weather values for a plurality of days;   using the collected intensity values and the weather values to predict at least one of a quality value and a yield for the crop.   
     
     
         16 . The method of  claim 15  further comprising using the unmanned aerial vehicle to capture pictures of the crop and using the pictures of the crop to estimate a height of the crop, wherein using the collected intensity values and the weather values to predict at least one of the quality value and the yield for the crop comprises using the estimated height of the crop with the collected intensity values and the weather values to predict at least one of the quality value and the yield for the crop. 
     
     
         17 . The method of  claim 16  wherein using the weather values to predict at least one of the quality value and the yield for the crop comprises using the weather values to determine growing degree units since a last harvest of the crop. 
     
     
         18 . The method of  claim 17  wherein determining a growing degree unit for a date comprises using a base temperature that is a function of the date. 
     
     
         19 . The method of  claim 15  wherein receiving the weather values for a plurality of days comprises receiving whether values measured for past days and predicted weather values predicted for future days. 
     
     
         20 . The method of  claim 15  wherein using the collected intensity values to predict at least one of the quality value and the yield for the crop comprises averaging intensity values for wavelengths in a waveband to form an average intensity for the waveband and using the average intensity for the waveband to predict at least one of the quality value and the yield for the crop.