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Proceedings Paper

Estimating corn nitrogen status using ground-based and satellite multispectral data
Author(s): Walter C. Bausch; Kenan Diker; Rajiv Khosla; Jack F. Paris
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Paper Abstract

In-season N management of irrigated corn requires frequent acquisition of plant N estimates to timely assess the onset of crop N deficiency and its spatial variability within a field. This study compared ground-based Exotech and QuickBird satellite multispectral data using the normalized GNDVI to produce N status maps of a study site on three days during the corn vegetative growth period. Scale factors to represent N sufficient and N deficient corn were determined for both systems from relationships between the normalized GNDVI and the NSI. A third classification was required for this study to classify areas that exhibited leaf chlorosis that was not caused by N deficiency, i.e., not N related. N status maps generated from normalized GNDVI values showed similar patterns between the two systems for the three corn growth stages (V10, V12, and V15) investigated. However, the extent of the pattern varied between systems. On 2 July (V10), six of six sample sites were correctly classified using leaf N content to indicate plant N status. On the other two days (7 July and 15 July), four of six sites were correctly classified. Two not N related areas were classified as N deficient when leaf N content was adequate.

Paper Details

Date Published: 9 November 2004
PDF: 10 pages
Proc. SPIE 5544, Remote Sensing and Modeling of Ecosystems for Sustainability, (9 November 2004);
Show Author Affiliations
Walter C. Bausch, USDA Agricultural Research Service (United States)
Kenan Diker, USDA Agricultural Research Service (United States)
Rajiv Khosla, Colorado State Univ. (United States)
Jack F. Paris, DigitalGlobe, Inc. (United States)

Published in SPIE Proceedings Vol. 5544:
Remote Sensing and Modeling of Ecosystems for Sustainability
Wei Gao; David R. Shaw, Editor(s)

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