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ARS Home » Research » Publications at this Location » Publication #91023
Title: INTEGRATION OF REMOTE SENSING AND CROP MODELS TO PROVIDE DECISION SUPPORT FOR PRECISION CROP MANAGEMENT

Author
item Barnes, Edward
item JONES, D - UNIV OF NEBRASKA
item BAKER, M - UNIV OF ARIZONA
item Pinter Jr, Paul

Submitted to: Geospatial Information in Agriculture and Forestry International Conference
Publication Type: Abstract Only
Publication Acceptance Date: 6/3/1998
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Precision crop management (PCM) has been defined as an agricultural management system to analyze and manage site-specific soil and crop variability within fields for optimum profitability, sustainability and protection of the environment. A framework will be presented that illustrates how remote sensing, crop models and decision support techniques can be integrated to meet the definition of PCM. Remotely- sensed data provides the means to spatially describe the within field variation in crop growth and development. This information is used with a crop model to conduct scenario testing of different management options. The results of the model's predictions and other ancillary data are then used with a decision model to rank the management options in terms of the PCM criteria of profitability, sustainability and environmental protection. The presentation will include a simple example of how this integration can occur.