基于Spearman等级系数的植被变化趋势分析

doi:10.3969/j.issn.0255-8297.2019.04.009

Abstract

Abstract: Spearman rank correlation coefficient method is proposed and its feasibility and applicability are also investigated, in view of problems that Pearson correlation coefficient method suffers noise sensitivity and limited finding ability of linear relationship in the longterm trend analysis of vegetation cover changes. Firstly, the anti-noise ability of Spearman rank correlation coefficient method is studied by simulation. Secondly, based on SPOT vegetation normalized vegetation index (NDVI) data from 1998 to 2013, Pearson correlation coefficient, Mann-Kendall test and Spearman rank correlation coefficient method are used to detect the vegetation cover changes in Inner Mongolia, and the results are graphically presented. The differences of the three methods are compared. The experimental results show that Spearman rank correlation coefficient has better anti-noise performance. There is high consistency in spatial distribution of vegetation cover changes among the results of Spearman rank correlation coefficient, Pearson correlation coefficient, and Mann-Kendall test. The maximum difference in vegetation increase and decrease regions does not exceed 2% in three methods.

Key words: Spearman rank correlation coefficient, Mann-Kendal test, Pearson correlation coefficient, trend analysis of vegetation cover changes, normalized vegetation index (NDVI)

CLC Number:

TP311.52

WANG Dianlai, SU Aixia, LIU Wenping. Trend Analysis of Vegetation Cover Changes Based on Spearman Rank Correlation Coefficient[J]. Journal of Applied Sciences, 2019, 37(4): 519-528.

References

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Trend Analysis of Vegetation Cover Changes Based on Spearman Rank Correlation Coefficient

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