Evaluating unsupervised and supervised image classification methods for mapping cotton root rot

Evaluating unsupervised and supervised image classification methods for mapping cotton root rot Cotton root rot, caused by the soilborne fungus Phymatotrichopsis omnivora, is one of the most destructive plant diseases occurring throughout the southwestern United States. This disease has plagued the cotton industry for over a century, but effective practices for its control are still lacking. Recent research has shown that a commercial fungicide, flutriafol, has potential for the control of cotton root rot. To effectively and economically control this disease, it is necessary to identify infected areas within fields so that site-specific technology can be used to apply fungicide only to the infected areas. The objectives of this study were to evaluate unsupervised classification applied to multispectral imagery, unsupervised classification applied to the normalized difference vegetation index (NDVI)and six supervised classification techniques, including minimum distance, Mahalanobis distance, maximum likelihood and spectral angle mapper (SAM), neural net and support vector machine (SVM),for mapping cotton root rot from airborne multispectral imagery. Two cotton fields with a history of root rot infection in Texas, USA were selected for this study. Airborne imagery with blue, green, red and near-infrared bands was taken from the fields shortly before harvest when infected areas were fully expressed in 2011. The four-band images were classified into infected and non-infected zones using the eight classification methods. Classification agreement index values for infected area estimation between any two methods ranged from 0.90 to 1.00 for both fields, indicating a high degree of agreement among the eight methods. Accuracy assessment showed that all eight methods accurately identified root rot-infected areas with overall accuracy values from 94.0 to 96.5 % for Field 1 and 93.0 to 95.0 % for Field 2. All eight methods appear to be equally effective and accurate for detection of cotton root rot for site-specific management of this disease, though the NDVI-based classification, minimum distance and SAM can be easily implemented without the need for complex image processing capability. These methods can be used by cotton producers and crop consultants to develop prescription maps for effective and economical control of cotton root rot. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Evaluating unsupervised and supervised image classification methods for mapping cotton root rot

Loading next page...
Springer US
Copyright © 2014 by Springer Science+Business Media New York
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
Publisher site
See Article on Publisher Site


You’re reading a free preview. Subscribe to read the entire article.

DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches


Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.



billed annually
Start Free Trial

14-day Free Trial