Assessing crop response to simulated damage utilizing UAS imagery

Ryan C. Phillips; Jason K. Ward

doi:10.1117/12.2560702

21 April 2020 Assessing crop response to simulated damage utilizing UAS imagery

Ryan C. Phillips, Jason K. Ward

Proceedings Volume 11414, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V; 1141403 (2020) https://doi.org/10.1117/12.2560702
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

Crop assessment through the use of unmanned aerial systems (UAS) have increased over recent years. More farmers or their service providers have access to their own UAS, although advanced sensors and UAS platforms may not have been widely adopted. Severe tropical weather events, such as hurricanes, can have widespread negative impacts to late-season crops. The timely response necessary to detect and quantify crop damage, has led to the need for farmers and other parties to have a quick and quantifiable method to assess lodging. Most, if not all, UAS users have access to visual band color imagery. Extraction of data from this imagery as different indices and as a digital elevation model creates the opportunity to identify metrics that can detect and quantify crop lodging damage. The goal of this study was to compare multiple vegetative indices which can be calculated from RGB imagery for their ability to detect simulated crop damage. Six indices as well as a digital elevation model were extracted from UAS flights occurring over 4 weeks over a maize field. Lodging was simulated at the root and ear level with new plots being damaged at each week of treatment. Results indicated that none of the indices or extracted data examined in this study would provide information on significant differences among treatments so it would not be advised to use these metrics on their own for detecting or classifying late-season maize lodging.

Conference Presentation

Citation Download Citation

Ryan C. Phillips and Jason K. Ward "Assessing crop response to simulated damage utilizing UAS imagery", Proc. SPIE 11414, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V, 1141403 (21 April 2020); https://doi.org/10.1117/12.2560702

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available