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QuickBird satellite versus ground-based multi-spectral data for estimating nitrogen status of irrigated maize

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Abstract

In-season nitrogen (N) management of irrigated maize (Zea mays L.) requires frequent acquisition of plant N status estimates to timely assess the onset of crop N deficiency and its spatial variability within a field. This study compared ground-based Exotech nadir-view sensor data and QuickBird satellite multi-spectral data to evaluate several green waveband vegetation indices to assess the N status of irrigated maize. It also sought to determine if QuickBird multi-spectral imagery could be used to develop plant N status maps as accurately as those produced by ground-based sensor systems. The green normalized difference vegetation index normalized to a reference area (NGNDVI) clustered the data for three clear-day data acquisitions between QuickBird and Exotech data producing slopes and intercepts statistically not different from 1 and 0, respectively, for the individual days as well as for the combined data. Comparisons of NGNDVI and the N Sufficiency Index produced good correlation coefficients that ranged from 0.91 to 0.95 for the V12 and V15 maize growth stages and their combined data. Nitrogen sufficiency maps based on the NGNDVI to indicate N sufficient (≥0.96) or N deficient (<0.96) maize were similar for the two sensor systems. A quantitative assessment of these N sufficiency maps for the V10–V15 crop growth stages ranged from 79 to 83% similarity based on areal agreement and moderate to substantial agreement based on the kappa statistics. Results from our study indicate that QuickBird satellite multi-spectral data can be used to assess irrigated maize N status at the V12 and later growth stages and its variability within a field for in-season N management. The NGNDVI compensated for large off-nadir and changing target azimuth view angles associated with frequent QuickBird acquisitions.

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Acknowledgments

The authors thank DigitalGlobe for providing QuickBird satellite images for this study and Dr. Jack F. Paris for assistance in obtaining the images. Special thanks go to Kenan Diker, Bryan Brown and Mary Brodahl for the image and spatial data analysis required in this study.

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  1. USDA-ARS Water Management Research Unit, Fort Collins, CO, 80526, USA

    W. C. Bausch

  2. Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO, 80523, USA

    R. Khosla

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  1. W. C. Bausch
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  2. R. Khosla
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Correspondence to W. C. Bausch.

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Bausch, W.C., Khosla, R. QuickBird satellite versus ground-based multi-spectral data for estimating nitrogen status of irrigated maize. Precision Agric 11, 274–290 (2010). https://doi.org/10.1007/s11119-009-9133-1

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