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ARS Home » Plains Area » College Station, Texas » Southern Plains Agricultural Research Center » Aerial Application Technology Research » Research » Publications at this Location » Publication #347614
Title: Creating prescription maps from satellite imagery for site-specific management of cotton root rot

Author
item Yang, Chenghai
item SONG, XIAOYU - Beijing Academy Of Agricultural Sciences
item WU, MINGQUAN - Chinese Academy Of Agricultural Sciences
item NICHOLS, ROBERT - Cotton, Inc

Submitted to: Asian Conference on Precision Agriculture
Publication Type: Proceedings
Publication Acceptance Date: 11/20/2017
Publication Date: 12/1/2017
Citation: Yang, C., Song, X., Wu, M., Nichols, R. 2017. Creating prescription maps from satellite imagery for site-specific management of cotton root rot. Proceedings of the Asian Conference on Precision Agriculture, October 16-18, 2017, Hamilton, New Zealand. 2017 CDROM.

Interpretive Summary: Cotton root rot can now be effectively controlled with a commercially-available fungicide. However, as this disease tends to occur in the same general areas within fields year after year, site-specific treatment can be more effective and economical. This study evaluated Sentinel-2 satellite imagery with 10-m spatial resolution for creating prescription maps for site-specific management of this disease. Airborne high resolution imagery was used to validate the classification accuracy of the satellite imagery. Although the Sentinel-2A image missed some small infested areas as compared with the airborne imagery, prescription maps created from both the satellite and airborne images were very similar. The results from this study indicate that satellite images with 10-m spatial resolution or finer can be used to create prescription maps for site-specific management of cotton root rot.

Technical Abstract: Cotton root rot is a century-old cotton disease that can now be controlled with Topguard Terra Fungicide. However, as this disease tends to occur in the same general areas within fields year after year, site-specific treatment can be more effective and economical. The objective of this study was to evaluate GeoEye-1 and Sentinel-2 satellite multispectral imagery for creating prescription maps for site-specific management of this disease. A GeoEye-1 2-m image acquired in 2009 and a Sentinel-2A 10-m image acquired in 2016 were used to map cotton root rot in two cotton fields, respectively. The multispectral images were classified into root rot-infested and non-infested areas using unsupervised classification. To accommodate the potential expansion and temporal variation of the disease, a 10-m buffer around the infested areas was added as part of the treatment areas in the prescription maps. The prescription map from the GeoEye-1 image for Field 1 was used for site-specific fungicide application in 2016 and the disease was effectively controlled. Airborne 1-m multispectral imagery acquired in 2016 was used to validate the classification accuracy of the Sentinel-2A image for mapping the disease in Field 2. Although the Sentinel-2A image missed some small infested areas as compared with the airborne imagery, prescription maps with the 10-m buffer from the Sentinel-2A and airborne images were very similar. The results from this study indicate that historical satellite images with 10-m spatial resolution or finer can be used to create prescription maps for site-specific management of cotton root rot.