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Inversion of a canopy reflectance model using hyperspectral imagery for monitoring wheat growth and estimating yield

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Abstract

Applications of hyperspectral remote sensing data to derive relevant properties for precision agriculture are described. Green leaf area index, fraction of senescent material and grain yield are retrieved from the hyperspectral data. Two sensors were used to obtain these data; the airborne visible/infrared imaging spectrometer AVIS and the space-borne compact high-resolution imaging spectrometer CHRIS; they show the applicability of the methods to different spatial scales. In addition, the bi-directional observation capability of the CHRIS sensor is used to derive information about the average leaf angle of the canopies which are used to link canopy structure with phenological development. Derivation of the canopy properties, green leaf area index and fraction of senescent material was done with the radiative transfer model, SLC (soil–leaf–canopy). The results were used as input into the crop growth model PROMET-V to calculate grain yield. Two years of data from the German research project preagro are presented.

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Acknowledgments

This work was carried out through sub-project “Canopy status assessment using remote sensing for model based yield estimation “of pre agro, which is a collaborative research project funded by the German Federal Ministry of Education and Research (BMBF), under grant reference number FK0330679. The work was also supported by ESA and SSTL with provision of CHRIS PROBA data. Special thanks to W. Verhoef (NLR) for his support in surface reflectance modelling and SLC applications. The authors take full responsibility for the content of this paper.

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Authors and Affiliations

  1. Vista Remote Sensing in Geosciences GmbH, Gabelsbergerstr. 51, 80333, München, Germany

    Silke Migdall & Heike Bach

  2. Institute of Landscape Systems Analysis, Leibniz-Centre for Agricultural Research (ZALF) e.V, Eberswalder Str. 84, 15374, Müncheberg, Germany

    Jans Bobert

  3. Institute of Soil Landscape Research, Leibniz-Centre for Agricultural Research (ZALF) e.V, Eberswalder Str. 84, 15374, Müncheberg, Germany

    Marc Wehrhan

  4. Department of Geography, Ludwig-Maximilians-Universität München, Luisenstr. 37, 80333, München, Germany

    Wolfram Mauser

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  1. Silke Migdall
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  2. Heike Bach
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  4. Marc Wehrhan
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  5. Wolfram Mauser
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Correspondence to Silke Migdall.

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Migdall, S., Bach, H., Bobert, J. et al. Inversion of a canopy reflectance model using hyperspectral imagery for monitoring wheat growth and estimating yield. Precision Agric 10, 508–524 (2009). https://doi.org/10.1007/s11119-009-9104-6

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