Yield Mapping with Digital Aerial Color Infrared (CIR) Images

Paper #:
  • 1999-01-2847

Published:
  • 1999-09-14
Citation:
GopalaPillai, S., Tian, L., and Bullock, D., "Yield Mapping with Digital Aerial Color Infrared (CIR) Images," SAE Technical Paper 1999-01-2847, 1999, https://doi.org/10.4271/1999-01-2847.
Pages:
16
Abstract:
Yield potential was predicted and mapped for three corn fields in Central Illinois, using digital aerial color infrared images. Three methods, namely statistical (regression) modeling, genetic algorithm optimization and artificial neural networks, were used for developing yield models. Two image resolutions of 3 and 6 m/pixel were used for modeling. All the models were trained using July 31 image and tested using images from July 2 and August 31, all from 1998. Among the three models, artificial neural networks gave best performance, with a prediction error less than 30%. The statistical model resulted in prediction errors in the range of 23 to 54%. The lower resolution images resulted in better prediction accuracy compared to resolutions higher than or equal to the yield resolution. Images after pollination resulted in better accuracy compared to images before pollination.
Access
Now
SAE MOBILUS Subscriber? You may already have access.
Buy
Select
Price
List
Download
$27.00
Mail
$27.00
Members save up to 40% off list price.
Share
HTML for Linking to Page
Page URL

Related Items

Technical Paper / Journal Article
2011-04-12
Article
2017-02-22
Article
2017-03-13
Article
2017-01-03
Training / Education
2017-06-15
Article
2017-03-13
Book
2002-04-15