Potential of the sentinel-2 red edge spectral bands for estimation of eco-physiological plant parameters

0468585 - ÚVGZ 2017 RIV CZ eng C - Konferenční příspěvek (zahraniční konf.)
Malenovský, Zbyněk - Homolová, Lucie - Janoutová, Růžena - Landier, L. - Gastelluetchegorry, J-P. - Bertholt, B. - Huck, A.
Potential of the sentinel-2 red edge spectral bands for estimation of eco-physiological plant parameters.
Proceedings of Living Planet Symposium 2016. Vol. ESASP-740. Nordwijk: European Space Agency (ESA), 2016 - (Ouwehand, L.). ISBN 978-92-9221-305-3. ISSN 1609-042X.
[Living Planet Symposium 2016. Praha (CZ), 09.05.2016-13.05.2016]
Grant CEP: GA MŠMT(CZ) LO1415
Grant ostatní: Evropská vesmírná agentura(DE) AO/1-7600/13/NL/LvH
Program: ESA
Institucionální podpora: RVO:67179843
Klíčová slova: canopy chlorophyll * image acquisition * physiological models * high spatial resolution * vegetation cabioy * agricultural fields * leaf chlorophyll content * multispectral images * space-borne instruments * support vector regression (SVR) * vegetation canopy
Kód oboru RIV: EH - Ekologie - společenstva

In this study we investigated importance of the spaceborne instrument Sentinel-2 red edge spectral bands and reconstructed red edge position (REP) for retrieval of the three eco-physiological plant parameters, leaf and canopy chlorophyll content and leaf area index (LAI), in case of maize agricultural fields and beech and spruce forest stands. Sentinel-2 spectral bands and REP of the investigated vegetation canopies were simulated in the Discrete Anisotropic Radiative Transfer (DART) model. Their potential for estimation of the plant parameters was assessed through training support vector regressions (SVR) and examining their P-vector matrices indicatingsignificance of each input. The trained SVR were then applied on Sentinel-2 simulated images and the acquired
estimates were cross-compared with results from high spatial resolution airborne retrievals. Results showed that contribution of REP was significant for canopy chlorophyll content, but less significant for leaf chlorophyll content and insignificant for leaf area index estimations. However, the red edge spectral bands contributed strongly to the retrievals of all parameters, especially canopy and leaf chlorophyll content. Application of SVR on Sentinel-2 simulated images demonstrated, in general, an overestimation of leaf chlorophyll content and an underestimation of LAI when compared to the reciprocal airborne estimates. In the follow-up investigation, we will apply the trained SVR algorithms on real Sentinel-2 multispectral images acquired during vegetation seasons 2015 and 2016.
Trvalý link: http://hdl.handle.net/11104/0266398