Paper
12 September 2021 Estimation of olive groves cover crops net primary productivity using remote sensing data
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Abstract
Cover crop in olive orchards is an increasingly applied soil and water conservation strategy, supported by European policies due to its multiple environmental benefits. To quantify these benefits, supervise and encourage the adoption of this practice, robust and affordable monitoring indicators of the cover crop dynamic and its biomass are required. This work represents the first attempt to estimate the biomass produced by olive grove cover crops based on remotely sensed data and an adaptation of the Monteith efficiencies approach. Ten olive tree fields were selected, distributed in three zones of Southern Spain. They comprised a high environmental variability and differed in the herbaceous layer management: cover crop in strips; non-tillage without strips (full coverage); and conventional tillage. An adaptation of the LUE (Light Use Efficiency)- model was applied to estimate Net Primary Production (NPP) using meteorological and Sentinel-2 data and subtracting the contribution of the wooded vegetation from the ground spectral response. The results showed an uneven adjustment in different fields. RMSD was equal to 650 kg ha-1, with an MBD of -17 kg ha-1, indicating a moderately high error (around 39%) but not too much bias. This error suggests that the model requires further refining, including the adjustment of model parameters to better represent this agrosystem. However, the evolution of biomass accumulation throughout the cover crop growing season and the behaviour of the daily biomass production provided interesting keys about the cover crops’ phenology and management, supporting the discrimination between management practices.
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Á. Blázquez-Carrasco, P. J. Gómez-Giráldez, J. Castro-Rodríguez, S. Colombo, E. Carpintero, and M. P. González-Dugo "Estimation of olive groves cover crops net primary productivity using remote sensing data", Proc. SPIE 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII, 118560S (12 September 2021); https://doi.org/10.1117/12.2601181
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KEYWORDS
Vegetation

Remote sensing

Agriculture

Biological research

Satellites

Data modeling

Solar radiation models

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