Abstract: A. F. Almeida- Nauñay, R. M. Benito, M. Quemada, J. C. Losada, A. M. Tarquis (2022)

Grasslands in the Iberian Peninsula are some of the most valuable ecosystems in Europe and are vulnerable because of their location in arid-semiarid regions. Remote sensing techniques have the potential for monitoring grasslands using vegetation indices (VIs), which can reveal bare soil and non-photosynthetic vegetation reflectance in these regions. The temporal variability of the VI time-series is commonly measured as the standard deviation of the records, insufficient to study the system dynamics. Recurrence plots (RP) and recurrence quantification analysis (RQA) allow us to visualize and quantify system dynamics based on topology. These advanced analyses calculate stochasticity through determinism (DET) and predictability degree based on the average length of diagonal structures (LT). This study aims to evaluate RPs, Cross Recurrence Plots (CRP), and RQA to visualize and quantify VIs and climatic series and their anomalies responses dynamics. The approach was tested at two sites with different agro-climatic characteristics in Central Spain: Guadalix de la Sierra (ZGU) and Soto del Real (ZSO). The Normalized Difference Vegetation Index (NDVI) and the Modified Soil Adjusted Vegetation Index (MSAVI), which includes a soil factor, were calculated from MODIS images. Temperature (TEMP) and precipitation (PCP) series were acquired from two meteorological stations close to each site. All the anomalies series were obtained seasonally adjusted to the original ones. RPs showed the different VIs responses in both areas. The MSAVI patterns showed a clear structure, while NDVI presented a noisy pattern showing a higher random behaviour. To quantify these visual differences with RQA, four parameters were calculated, including DET and LT. The MSAVI series and the corresponding anomaly series presented higher DET and LT than the NDVI in both sites. CRPs of VIs with TMIN shows a higher DET in ZGU, suggesting that time synchronization is higher than in ZSO. When CRPs were applied over anomalies series, we could observe that precipitation is more synchronized with VIs anomalies, most likely because of the influence of soil moisture. LT of CRPs in all the cases was low and close to 2, indicating low predictability. Overall, our results suggest that VI time series show a more evident pattern and differentiate both sites better when a variable soil adjustment factor is included. Therefore, in arid-semiarid grasslands, a soil factor should be considered in VI calculations.

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Recurrence plots for quantifying the vegetation indices dynamics in a semi-arid grassland