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Journal of Applied Remote Sensing • Open Access

Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment
Author(s): Carly Stanton; Michael J. Starek; Norman Elliott; Michael Brewer; Murilo M. Maeda; Tianxing Chu

Paper Abstract

A small, fixed-wing unmanned aircraft system (UAS) was used to survey a replicated small plot field experiment designed to estimate sorghum damage caused by an invasive aphid. Plant stress varied among 40 plots through manipulation of aphid densities. Equipped with a consumer-grade near-infrared camera, the UAS was flown on a recurring basis over the growing season. The raw imagery was processed using structure-from-motion to generate normalized difference vegetation index (NDVI) maps of the fields and three-dimensional point clouds. NDVI and plant height metrics were averaged on a per plot basis and evaluated for their ability to identify aphid-induced plant stress. Experimental soil signal filtering was performed on both metrics, and a method filtering low near-infrared values before NDVI calculation was found to be the most effective. UAS NDVI was compared with NDVI from sensors onboard a manned aircraft and a tractor. The correlation results showed dependence on the growth stage. Plot averages of NDVI and canopy height values were compared with per-plot yield at 14% moisture and aphid density. The UAS measures of plant height and NDVI were correlated to plot averages of yield and insect density. Negative correlations between aphid density and NDVI were seen near the end of the season in the most damaged crops.

Paper Details

Date Published: 22 June 2017
PDF: 20 pages
J. Appl. Rem. Sens. 11(2) 026035 doi: 10.1117/1.JRS.11.026035
Published in: Journal of Applied Remote Sensing Volume 11, Issue 2
Show Author Affiliations
Carly Stanton, Texas A&M Univ. Corpus Christi (United States)
Michael J. Starek, Texas A&M Univ. Corpus Christi (United States)
Norman Elliott, USDA/ARS (United States)
Michael Brewer, Texas A&M AgriLife Research and Extension Ctr. (United States)
Murilo M. Maeda, Texas A&M AgriLife Research and Extension Ctr. (United States)
Tianxing Chu, Texas A&M Univ. Corpus Christi (United States)

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