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Spatial analysis of multispectral and thermal imagery from multiple platforms
Author(s): Gregory Rouze; Haly Neely; Cristine Morgan; Chenghai Yang
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Paper Abstract

Airborne and satellite remote sensing can potentially be used to model crop characteristics. However, satellite imagery usually exhibit low spatial and temporal resolutions, and manned aircraft imagery, despite improved resolutions, is not cost-effective. Recent developments in UAV remote sensing have allowed for imagery at improved spatial resolutions relative to satellites and at a fraction of the cost relative to manned aircraft. Furthermore, UAVs offer potential advantages over proximal soil sensors (i.e. EM-38) in terms of in-season decision making. However, it is unclear at this point whether these benefits translate to higher quality information. This question has relevance within fields that exhibit contrasting environments, such as soil spatial variability. Therefore, the objectives of this paper were twofold: 1) to quantify improvements in UAV-based plant (cotton) modelling relative to proximal sensing (i.e. EM-38), manned aircraft, and satellites (Landsat 8); and 2) to determine how such modeling can be affected by soil spatial variability. Results indicate that UAVs show higher nugget/sill ratios and larger ranges than manned aircraft and satellites. These results have implications for predicting agronomic variables (i.e. yield, plant height), as well as soil/plant sampling.

Paper Details

Date Published: 21 May 2018
PDF: 11 pages
Proc. SPIE 10664, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III, 106640T (21 May 2018); doi: 10.1117/12.2305896
Show Author Affiliations
Gregory Rouze, Texas A&M Univ. (United States)
Haly Neely, Texas A&M Univ. (United States)
Cristine Morgan, Texas A&M Univ. (United States)
Chenghai Yang, USDA-ARS (United States)

Published in SPIE Proceedings Vol. 10664:
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III
J. Alex Thomasson; Mac McKee; Robert J. Moorhead, Editor(s)

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