Abstract
This study examines the relationship between summer season NDVI and local-level climate variables, consisting of precipitation and temperature, in Minnesota from 1990 to 1997 using Geographically Weighted Regression (GWR). In comparison to traditional global techniques of Ordinary Least Squared (OLS) regression, there is a substantial improvement in the analysis using GWR. The overall relationship among the different variables was broadly consistent for the diverse types of land uses across the state. The spatial patterns of the association in the form of regression coefficients were not very consistent over the years as a result of interannual variations in the local climate.
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