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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 #356570

Research Project: Aerial Application Technology for Sustainable Crop Production

Location: Aerial Application Technology Research

Title: Mapping cotton plant height using digital surface models derived from overlapped airborne imagery

Author
item Yang, Chenghai

Submitted to: Proceedings of the Annual Precision Ag Conference
Publication Type: Proceedings
Publication Acceptance Date: 9/10/2018
Publication Date: 10/25/2018
Citation: Yang, C. 2018. Mapping cotton plant height using digital surface models derived from overlapped airborne imagery. Proceedings of the Annual Precision Ag Conference. https://www.ispag.org/proceedings/?action=abstract&id=4778&search=authors.

Interpretive Summary: High resolution aerial images captured from unmanned aircraft systems are recently being used to measure plant height over small test plots for phenotyping, but airborne images from manned aircraft have the potential for mapping plant height more practically over large fields. This study evaluated the feasibility to measure cotton plant height from digital surface models derived from overlapped airborne imagery and compared the image-based estimates with the data from a tractor-mounted ultrasonic distance sensor. Results showed that there existed a significant relation between image-based and ground-based plant height estimates. The preliminary results from this study indicate that digital surface models derived from overlapped airborne imagery have the potential to estimate and map plant height for monitoring crop growth conditions.

Technical Abstract: High resolution aerial images captured from unmanned aircraft systems (UASs) are recently being used to measure plant height over small test plots for phenotyping, but airborne images from manned aircraft have the potential for mapping plant height more practically over large fields. The objectives of this study were to evaluate the feasibility to measure cotton plant height from digital surface models (DSMs) derived from overlapped airborne imagery and compare the image-based estimates with the data from a tractor-mounted ultrasonic distance sensor. An airborne imaging system consisting of a red-green-blue (RGB) camera and a modified near-infrared (NIR) camera mounted on a Cessna 206 aircraft was flown along six flight lines over a 27-ha field at peak cotton growth and again with tilled bare soil. Images were captured at 370 m above ground level to achieve a ground pixel size of 0.09 m and side/forward overlaps of about 85%. The ultrasonic distance sensor and a centimeter-grade GPS receiver were mounted on a high-clearance tractor to collect cotton plant height data from every 8th row at 1-s intervals. The images taken on the two dates were processed to create orthomosaics and DSMs. Plant height was estimated from the difference between the two DSMs. Results showed that a significant linear relation existed between image-based and ground-based plant height estimates with a R2 value of 0.657 and a standard error of 0.11 m. The preliminary results from this study indicate that DSMs derived from overlapped airborne imagery have the potential to estimate and map plant height for monitoring crop growth conditions.