Abstract
Grasslands in the Iberian Peninsula are valuable and susceptible ecosystems due to their location in arid-semiarid regions. Remote sensing techniques have potential for monitoring them through vegetation indices (VIs). The Modified Soil Adjusted Vegetation Index (MSAVI) is an improved version of classical VIs for arid and semiarid regions.
This work aims to analyse the relation among MSAVI, temperature (TMP) and precipitation (PCP) to understand the complexity of the vegetation-climate system. First, based on MSAVI pattern several phases through the year cycle are defined. Second, a cross-correlation between MSAVI and climatic variables series are performed for each phase at different lags to detect the highest correlation. Then, recurrence plots (RPs) and recurrence quantification analysis (RQA) are computed to characterize and quantify the underlying non-linear dynamics of the MSAVI series.
Our results suggest that five different phases can be defined, in this case study, in which TMP is the main driving factor. The correlation with TMP presents different signs depending on the phase. However, PCP plays a key role with a positive correlation regardless the phase. In the case of TMP, the correlations are higher and the lags shorter than PCP case. This explains the complexity of vegetation-climate dynamics.
RPs and RQA demonstrated to be a suitable tool to quantify this complexity. In our case, we have detected a high-dimensionality and a short-term predictability in the MSAVI series, characteristic of ecological systems.
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Acknowledgments
The authors acknowledge support from Project No. PGC2018-093854-B-I00 of the Spanish Ministerio de Ciencia Innovación y Universidades of Spain and the funding from the Comunidad de Madrid (Spain), Structural Funds 2014-2020 512 (ERDF and ESF), through project AGRISOST-CM S2018/BAA-4330 and the financial support from Boosting Agricultural Insurance based on Earth Observation data - BEACON project under agreement Nº 821964, funded under H2020_EU, DT-SPACE-01-EO-2018-2020.
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Almeida-Ñauñay, A.F., Benito, R.M., Quemada, M., Losada, J.C., Tarquis, A.M. (2021). Complexity of the Vegetation-Climate System Through Data Analysis. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications IX. COMPLEX NETWORKS 2020 2020. Studies in Computational Intelligence, vol 943. Springer, Cham. https://doi.org/10.1007/978-3-030-65347-7_50
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