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

Berger [Richter], K., Atzberger, C., Danner, M., D’Urso, G., Mauser, W., Vuolo, F., Hank, T. (2018): Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study. - Remote Sensing, 10, 1, 85.
https://doi.org/10.3390/rs10010085

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Berger [Richter], Katja1, Autor              
Atzberger, Clement2, Autor
Danner, Martin2, Autor
D’Urso, Guido2, Autor
Mauser, Wolfram2, Autor
Vuolo, Francesco2, Autor
Hank, Tobias2, Autor
Affiliations:
10 Pre-GFZ, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146023              
2External Organizations, ou_persistent22              

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Schlagwörter: PROSAIL; biophysical and biochemical variables; EnMAP sensor; model inversion; hyperspectral; leaf area index (LAI); radiative transfer model
 Zusammenfassung: 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.

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Sprache(n): eng - Englisch
 Datum: 2018-01-102018
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.3390/rs10010085
 Art des Abschluß: -

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Titel: Remote Sensing
Genre der Quelle: Zeitschrift, SCI, Scopus, OA
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 10 (1) Artikelnummer: - Start- / Endseite: 85 Identifikator: CoNE: https://gfzpublic.gfz-potsdam.de/cone/journals/resource/journals426