Abstract
Ecosystem is a prototypical complex system, exhibiting a non-stationary temporal dynamics and complicated spatial patterns, the characterization and description of which is riddled with challenges. In this paper recurrence quantification analysis (RQA), an extended branch of recurrence plots (RPs), was used to measure the determinism and predictability of Normalized Difference Vegetation Index (NDVI)series and its spatial patterns. After introducing the theoretical background of RPs and RQA indices, the implementation of this methodology was demonstrated using NDVI data of region around Beijing, China. The results show that the RQA indices can efficiently capture the nonlinear features of NDVI series and explicitly identify the spatial patterns. The temporal variation and dynamics of NDVI series shows significant spatial differences with the change of landuse and landcover types, characterizing by higher determinism and predictability in natural ecosystem and lower determinism and predictability in agricultural ecosystem. The research work indicates that combination of recurrence quantification analysis and geographical information system can offer an alternative approach to identifying the spatial pattern of temporal NDVI series dynamics.
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Li, S., Zhao, Z. & Liu, F. Identifying spatial pattern of NDVI series dynamics using recurrence quantification analysis. Eur. Phys. J. Spec. Top. 164, 127–139 (2008). https://doi.org/10.1140/epjst/e2008-00839-y
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DOI: https://doi.org/10.1140/epjst/e2008-00839-y