Integration of remote sensing and bioclimatic data for prediction of invasive species distribution in data-poor regions: a review on challenges and opportunities

Environmental Systems Research

Table 2 Variable selection techniques used in the integration of remote sensing and bioclimatic based variables

S.no	Variable selection methods	References
1	Correlation (Pearson, Kendall, Spearman)	Buermann et al. (2008); Engler et al. (2013); Gormley et al. (2011); Ng et al. (2018); Saatchi et al. (2008); Truong et al. (2017); Wakie et al. (2014); West et al. (2014); Zimmermann et al. (2007)
2	Principal component analysis	Deblauwe et al. (2016); Feilhauer et al. 2012; Jensen et al. (2020)
3	Variance inflation factor	Ahmadi et al. (2020); Ng et al. (2018); Shiferaw et al. (2019c)
4	Weighted mean fitted analysis approach	Shiferaw et al. (2019a)
5	Permutation importance	Wilson et al. (2013)
6	Expert knowledge	Beaumont et al. (2005); Jones (2012); Ng et al. (2018)