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Title: ESTIMATING PLANT NITROGEN STATUS IN IRRIGATED CORN USING GROUND-BASED AND SATELLITE DATA

Author
item BAUSCH, WALTER
item DIKER, KENAN
item PARIS, JACK - DIGITALGLOBE
item KHOSLA, RAJIV - CSU

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/24/2004
Publication Date: 7/25/2004
Citation: Bausch, W.C., Diker, K., Paris, J.F., Khosla, R. 2004. Estimating plant nitrogen status in irrigated corn using ground-based and satellite data. International Conference on Precision Agriculture Abstracts & Proceedings. . In Proc. of the 7th Intern. Conf. on Precision Agriculture. CD-ROM. Minneapolis, MN: ASA, CSSA, SSSA. (Conference proceedings)

Interpretive Summary: Many satellite-based sensors have spatial resolutions too coarse for within field analysis and inadequate repeat coverage for intensive agricultural management. A cooperative study by the Water Management Research Unit and DigitalGlobe, Inc. compared high-resolution multispectral satellite data to ground-based multispectral data to determine if the QuickBird satellite could provide information on a crop's N status equivalent to the ground-based system. Satellite images and ground-based data were acquired five times on a center-pivot irrigated corn field in eastern Colorado from June 24 to July 25, 2003. Results from three clear days of the five attempts to acquire satellite images suggest that the QuickBird satellite can be used for within field estimation of corn canopy N status; however, cloud cover over the area of interest is a hindrance to satellite data acquisition.

Technical Abstract: In-season N management of irrigated corn requires frequent acquisition of plant N status estimates to timely assess the onset of crop N deficiency and its spatial variability within a field. Satellite-based sensors have not had adequate spatial resolution, repeat coverage, and image delivery time for intensive agricultural management. The high-resolution QuickBird satellite may potentially change these limitations. The objective of this study was to determine if high-resolution multispectral satellite data could detect corn N deficiencies comparable to that estimated from ground-based multispectral data. QuickBird satellite data and Exotech radiometer measurements from a mobile system were acquired in a center-pivot irrigated cornfield in eastern Colorado. Same day acquisitions occurred three times which corresponded to the V10, V12, and V15 corn growth stages. Vegetation indices calculated from the Exotech and QuickBird data showed disparities related to the satellite sensor viewing the dark side of the corn canopy one time and the bright side the next. This is a limitation of off-nadir viewing. However, the normalized GNDVI tended to cluster the data for the three acquisition dates for the two systems. Good correlations were produced between the normalized GNDVI and NSI calculated from SPAD data for individual dates. Based on the data presented QuickBird multispectral data can detect corn N deficiencies comparable to the ground-based system.