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United States Department of Agriculture

Agricultural Research Service

Title: Detection of Agronomic Parameters from Remote Sensing and the Potential Application to Agricultural Management Decisions

Author
item Hatfield, Jerry

Submitted to: Photogrammetric Engineering and Remote Sensing
Publication Type: Abstract Only
Publication Acceptance Date: October 22, 2004
Publication Date: October 22, 2004
Citation: Hatfield, J.L. 2004. Detection of agronomic parameters from remote sensing and the potential application to agricultural management decisions [abstract]. 12th Australian Remote Sensing and Photogrammetry Conference, October 18-22, Fremantle, Western Australia. p. 23.

Technical Abstract: Detection of critical agronomic parameters, e.g., leaf area, light interception, biomass, ground cover, are achievable with remote sensing methods. Use of remote sensing methods offers the opportunity to evaluate field-scale responses and to quantify the changes in these patterns over time and among growing seasons. Information for agricultural decisions at the field scale requires an information base that accounts for both the spatial and temporal variability within fields. We have been conducting a series of field scale experiments across Iowa to quantify both the spatial and temporal variability using hyperspectral from an aircraft platform and broad-band data from either Landsat or SPOT (Systeme Probatione d'Observation del La Terra) platforms. The algorithms to relate spectral signatures to agronomic parameters have been developed using hand-held broad-band and hyperspectral radiometers. These experiments have been conducted since 1998 across a range of fields and management practices. These data are being developed into methods to help producers understand how improved management decisions can be applied to a given field that increases the profit across the field and reduces the risk associated with management decisions. Integration of multiple sources of data across a field populates a data base that enhances the information required for more effective decision-making by producers.

Last Modified: 8/30/2014
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