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Free keywords:
Agriculture, Plants,Sensors, Table lookup, Measurement uncertainty
Abstract:
The present study aimed at testing the potential of the future E.O. mission Sentinel-2 (European GMES programme) for the operational estimation of the Leaf Area Index (LAI) of three contrasting agricultural crops (wheat, sugar beet, and maize). Retrieval of LAI was achieved by using a look-up table (LUT) based inversion of a radiative transfer model (SAILH+PROSPECT). Analyses were mainly carried out using hyperspectral data acquired by the optical airborne instrument CASI, simulating the future Sentinel-2 band setting. Estimated LAI was evaluated using measurements of effective Plant Area Index (PAI eff ) collected during the ESA AgriSAR 2006 campaign. Additionally, measurements from two other experiments were tested to enrich the validation database. The GMES targeted precision of 10% for green LAI estimation was met for sugar beet (8%), at the limit for wheat (11%) but not for maize (19%). For the three crops the RMSE was in the range 0.4-0.6. The results demonstrate the importance of using crop specific radiative transfer models. For row crops with incomplete coverage and strong leaf clumping, such as maize at early stage, the standard SAILH+PROSPECT model does not appear suitable. However, results must be taken cautiously in view of possible uncertainties of the PAI eff measurements. Within a future Sentinel-2 product validation framework, a standard protocol for reference measurements is required to assure consistency of validation data sets.
