Remote sensing for nitrogen management

Nitrogen application often dramatically increases crop yields, but N needs vary spatially across fields and landscapes. Remote sensing collects spatially dense information that may contribute to, or provide feedback about, N management decisions. There is potential to accurately predict N fertilizer need at each point in the field. This would reduce surplus N in the crop production system without reducing crop yield, which would in turn reduce N losses to surface and ground waters. Soil spectral properties (color) are related to soil organic matter and soil moisture levels, factors that influence the N-supplying ability of the soil. Plant spectral properties reflect crop N status and soil N availability, and they can be useful for directing in- season variable-rate N applications. Plant color may also be useful for assessing the adequacy of crop nitrogen supply achieved with a given nitrogen management practice. We outline the current status of these approaches, offer examples, discuss several N management contexts in which these approaches might be used, and consider possible future directions for this technology.

[1]  J. Hanway How a corn plant develops , 1966 .

[2]  J. Hummel,et al.  Reflectance technique for predicting soil organic matter. , 1980 .

[3]  Remote sensing applications for resource management , 1981 .

[4]  J. S. Schepers,et al.  Predicting N fertilizer needs for corn in humid regions: using chlorophyll meters , 1992 .

[5]  M. M. Alley,et al.  Spring Nitrogen on Winter Wheat: I. Farmer-Field Validation of Tissue Test—Based Rate Recommendations , 1993 .

[6]  G. Randall,et al.  Developing a Soil Nitrogen Test for Improved Recommendations for Corn , 1994 .

[7]  Moon S. Kim,et al.  Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectance measurements , 1994 .

[8]  L. Bundy,et al.  An Alternative Rationale for Corn Nitrogen Fertilizer Recommendations , 1994 .

[9]  Larry G. Bundy,et al.  Soil Yield Potential Effects on Performance of Soil Nitrate Tests , 1995 .

[10]  H. R. Duke,et al.  Remote Sensing of Plant Nitrogen Status in Corn , 1996 .

[11]  J. Schepers,et al.  Analysis of Aerial Photography for Nitrogen Stress within Corn Fields , 1996 .

[12]  R. W. Whitney,et al.  Use of Spectral Radiance for Correcting In-season Fertilizer Nitrogen Deficiencies in Winter Wheat , 1996 .

[13]  A. Gitelson,et al.  Use of a green channel in remote sensing of global vegetation from EOS- MODIS , 1996 .

[14]  P. C. Robert,et al.  Spatial variability of profitability in site-specific N management , 1996 .

[15]  Frédéric Baret,et al.  Radiometric Estimates of Nitrogen Status of Leaves and Canopies , 1997 .

[16]  S. E. White,et al.  Using precision farming technologies to improve management of soil and fertiliser nitrogen , 1998 .

[17]  Moon S. Kim,et al.  Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .

[18]  In situ detection of leaf chlorophyll content and leaf nitrogen content in Zea mays L. using remote sensing. , 2000 .

[19]  L. West,et al.  Field-Scale Mapping of Surface Soil Organic Carbon Using Remotely Sensed Imagery , 2000 .

[20]  Randal K. Taylor,et al.  Corn Yield Response to Nitrogen at Multiple In-Field Locations , 2002 .

[21]  P. Scharf,et al.  Calibrating Corn Color from Aerial Photographs to Predict Sidedress Nitrogen Need , 2002 .