Statistical analysis of auto-correlation and cross-correlation: a case of study inherent to the issue of water security
DOI:
https://doi.org/10.55761/abclima.v35i20.18891Keywords:
NDVI, EVI, Water Security, DFA, ρ_DCCAAbstract
The vegetation indexes, NDVI and EVI, used in the analysis of remote sensing data, assess the health and vigor of vegetation based on the reflectance measured by sensors on satellites. Based on these values (and its RGB spectral bands) as a function of time, this paper proposes a complete analysis of auto-correlation and cross-correlation, for more than six years of observation. For this purpose, an important environmental protection area was chosen, where energy generation and water security are crucial factors regarding the well-being of millions of inhabitants. For this analysis, the DFA method and the DCCA cross-correlation coefficient were applied. Initially, in the study of auto-correlations, a clear change of behavior in the auto-correlation function was identified around 30 observations, with different exponents values depending on the index applied. Subsequently, in the analysis of the mutual relationship between all indexes, through the DCCA cross-correlation coefficient, it was clear that the value of this coefficient can be negative or positive, with DCCA cross-correlation varying from a weak to a strong level, depending on its time scale.
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