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Remote Sens. 2018, 10(1), 85; https://doi.org/10.3390/rs10010085

Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study

1
Department of Geography, Ludwig-Maximilians-Universität München, Luisenstraße 37, D-80333 Munich, Germany
2
Institute of Surveying, Remote Sensing & Land Information (IVFL), University of Natural Resources and Life Sciences, Vienna (BOKU), Peter Jordan Str. 82, 1190 Vienna, Austria
3
Department of Agricultural Engineering and Agronomy, University of Naples Federico II, Via Università 100, 80055 Portici (Na), Italy
*
Author to whom correspondence should be addressed.
Received: 24 November 2017 / Revised: 20 December 2017 / Accepted: 8 January 2018 / Published: 10 January 2018
(This article belongs to the Special Issue Recent Progress and Developments in Imaging Spectroscopy)
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Abstract

Upcoming satellite hyperspectral sensors require powerful and robust methodologies for making optimum use of the rich spectral data. This paper reviews the widely applied coupled PROSPECT and SAIL radiative transfer models (PROSAIL), regarding their suitability for the retrieval of biophysical and biochemical variables in the context of agricultural crop monitoring. Evaluation was carried out using a systematic literature review of 281 scientific publications with regard to their (i) spectral exploitation, (ii) vegetation type analyzed, (iii) variables retrieved, and (iv) choice of retrieval methods. From the analysis, current trends were derived, and problems identified and discussed. Our analysis clearly shows that the PROSAIL model is well suited for the analysis of imaging spectrometer data from future satellite missions and that the model should be integrated in appropriate software tools that are being developed in this context for agricultural applications. The review supports the decision of potential users to employ PROSAIL for their specific data analysis and provides guidelines for choosing between the diverse retrieval techniques. View Full-Text
Keywords: PROSAIL; biophysical and biochemical variables; EnMAP sensor; model inversion; hyperspectral; leaf area index (LAI); radiative transfer model PROSAIL; biophysical and biochemical variables; EnMAP sensor; model inversion; hyperspectral; leaf area index (LAI); radiative transfer model
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Berger, K.; Atzberger, C.; Danner, M.; D’Urso, G.; Mauser, W.; Vuolo, F.; Hank, T. Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study. Remote Sens. 2018, 10, 85.

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