Potential and limitations of spectral reflectance measurements for the estimation of the site-specific variability in crops

Stefan Erasmi; Eike S. Dobers

doi:10.1117/12.511163

24 February 2004 Potential and limitations of spectral reflectance measurements for the estimation of the site-specific variability in crops

Stefan Erasmi, Eike S. Dobers

Author Affiliations +

Proceedings Volume 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V; (2004) https://doi.org/10.1117/12.511163
Event: Remote Sensing, 2003, Barcelona, Spain

Abstract

The use of remote sensing data in site specific crop management aims at the prediction of soil and crop factors that have an impact on yield formation processes in agriculture. Numerous methods demonstrate the potential of spectral reflectance data for the detection of qualitative and quantitative crop features but there is, however, no established methodology for the implementation of these data in operational crop production processes. The paper describes the main aspects of remote sensing based site characterization, considering major site variables (yield, soil) and plant parameters (nitrogen uptake) as key features for the description of the site specific variability in crops. Spectral reflectance data of the VIS/NIR region are transformed into different spectral indices for statistical analysis. Analyzing these indices it is found that the determination of a prediction model depends on the relevance of the suggested data fitting method (causality) as well as on the statistical significance of the interrelationship. Results point out that remote sensing data are suitable predictors for crop vitality and site characterization. Hence, the application of these data in agricultural work routines is limited by their quality and availability as well as by the influence of environmental factors on yield formation processes.

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Stefan Erasmi and Eike S. Dobers "Potential and limitations of spectral reflectance measurements for the estimation of the site-specific variability in crops", Proc. SPIE 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V, (24 February 2004); https://doi.org/10.1117/12.511163

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