Improving the analysis of the soil-plant-atmosphere system thought earth observations in large monocrop cereal sequences

Crop yields of rainfed cereal are highly dependent of the soil-plant-atmosphere system, especially referred to the weather conditions and soil properties. The study of this interaction is feasible through the earth observations of historical data. Remote sensing data and agricultural survey work together identifying and analyzing plots with monocrop cereal sequences. In this research, we investigate the relation of the Normalized Difference Vegetation Index (NDVI) residual time series behavior relative to soil classes from Self-Organizing Maps (SOM) and the precipitation residual time series.

The midlands of Eresma-Adaja watershed (Dueros’ River basin, Spain) is historically depicted to rainfed cereal agriculture, some evidence of monocropping sequences are worrisome the water availability in the area. Within this area, two contrasting soil properties sites were selected to assess plots with at least 20 years of rainfed monocropping sequences but under similar weather regime. This allows analyzing the effect and relationships of this practice by soil type in time. For this, we treat the NDVI and precipitation time residual series as signals. The use of the Generalized Structure Function applied to these residual time series and the Hurst exponent, serve to confirm the soil properties differences from SOM and to reinforce the scaling properties of soil-climate interaction in semiarid regions for cereals in monocrop. As a result, the NDVI and precipitation series present an antipersistence behavior supporting that precipitation regime is influencing as the same manner the NDVI residual time series among complimentary factors.

ACKNOWLEDGEMENTS

Finding for this work was partially provided by Boosting agricultural Insurance based on Earth Observation data - BEACON project under agreement Nº 821964, funded under H2020_EU, DT-SPACE-01-EO-2018-2020. The authors also acknowledge support from Project No. PGC2018-093854-B-I00 of the Spanish Ministerio de Ciencia Innovación y Universidades of Spain. The data provided by ITACyL and AEMET is greatly appreciated.