Using geographically weighted regression to predict the spatial distribution of frozen ground temperature: a case in the Qinghai–Tibet Plateau
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DOI: 10.1088/1748-9326/abd431
Abstract: This paper combines the use of principal component analysis (PCA) and the geographically weighted regression (GWR) model to predict the spatial distribution of frozen ground temperature. PCA is used to reduce the multicollinearity among covariates,… read more here.
Keywords: ground; frozen ground; distribution frozen; spatial distribution ... See more keywords