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Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission
Institute of Surveying, Remote Sensing and Land Information (IVFL), University of Natural Resources and Life Sciences (BOKU), Peter Jordan Str. 82, A-1190 Vienna, Austria
School of Geography, University of Southampton, Highfield, Southampton SO17 1BJ, UK
City University London, Northampton Square, London EC1V 0HB, UK
European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), Keplerlaan 1, P.O. Box 299, 2200 AG Noordwijk, The Netherlands
EUMETSAT, Eumetsat Allee 1, D-64295 Darmstadt, Germany
* Author to whom correspondence should be addressed.
Received: 15 March 2012; in revised form: 12 April 2012 / Accepted: 13 April 2012 / Published: 25 April 2012
Abstract: A methodology is described for the validation of Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) data over heterogeneous land surfaces in an agricultural region in Southern Italy. The approach involves the use inverse canopy reflectance modeling techniques to derive maps of canopy chlorophyll content (CCC) and leaf area index (LAI) at fine spatial resolution. Indirect field measurements are used for validation of the fine spatial resolution data. Subsequently, these maps are aggregated based on a regular grid at 1 km spatial resolution to validate MERIS Level 2 MTCI (300 m). RapidEye satellite sensor data with a pixel size of 6.5 m are used for this purpose. Based on a set of independent ground measurements, fine spatial resolution maps achieved an R2 = 0.78 and RMSE = 0.39 for CCC and R2 = 0.76 and RMSE = 0.64 for LAI. The relationship between MERIS L2 MTCI and CCC [g∙m−2] achieved a coefficient of determination of 0.74 and it resulted to be extremely statistically significant (p-value < 0.001). Additionally, a relative validation of two other satellite products at medium resolution spatial scale, namely MERIS leaf area index (LAI) and Moderate Resolution Imaging Spectrometer (MODIS) LAI was performed by comparison with the fine spatial resolution LAI map. Results indicated a better accuracy in LAI estimation of MERIS (RMSE = 0.33) compared to MODIS (RMSE = 0.81) data.
Keywords: Envisat-MERIS; MERIS Terrestrial Chlorophyll Index (MTCI); canopy chlorophyll content (CCC); leaf area index (LAI); Sentinel-3; OLCI Terrestrial Chlorophyll Index (OTCI)
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MDPI and ACS Style
Vuolo, F.; Dash, J.; Curran, P.J.; Lajas, D.; Kwiatkowska, E. Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission. Remote Sens. 2012, 4, 1112-1133.
Vuolo F, Dash J, Curran PJ, Lajas D, Kwiatkowska E. Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission. Remote Sensing. 2012; 4(5):1112-1133.
Vuolo, Francesco; Dash, Jadunandan; Curran, Paul J.; Lajas, Dulce; Kwiatkowska, Ewa. 2012. "Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission." Remote Sens. 4, no. 5: 1112-1133.