Recurrence techniques for the analysis of vegetation indices and climate anomalies: a study case in semiarid grasslands

Abstract

Semiarid grasslands are sensitive to drought and are one of the most threatened ecosystems by climate change. In this work, we proposed to assess the performance of two different vegetation indices (VIs) in two zones of a semiarid area with different agro-ecological characteristics. We calculated the VIs and climate anomalies and then attempted to identify and characterize their dynamics with recurrence techniques, a nonlinear method. In this study, the Normalised Difference vegetation index (NDVI) and the Modified Soil Adjusted Vegetation Index (MSAVI) were used. The minimum temperature and precipitation series in both areas were also extracted, as they are the key driving factors of the system. The original series was seasonally adjusted by subtracting the average per date to obtain the anomalies series. On this new set, recurrence plots (RPs), cross recurrence plots (CRPs), and recurrence quantification analysis (RQA) were computed to achieve this goal. RPs are proposed as a method to reveal the periodic or chaotic behaviour of a system. CRPs are a bivariate extension of RPs, and they are computed to analyse the relationships between two variables of the same system. Both are quantified by the RQA, obtaining measures of complexity. We have found that RPs allow visualising different VIs anomalies patterns in each zone. Furthermore, the CRPs revealed the VIs sensitivity to detect and differentiate local conditions. Overall, we have characterised and measured the dynamics of the VIs anomalies and we have shown that recurrence techniques are a valuable tool to explore drought events in semiarid areas.