Investigating spatial variation in the relationships between NDVI and environmental factors at multi-scales: a case study of Guizhou Karst Plateau,China

Knowing the spatial relationships between the normalized difference vegetation index (NDVI) and environmental variables is of great importance for monitoring rocky desertification. This article investigated the spatially non-stationary relationships between NDVI and environmental factors using geographically weighted regression (GWR) at multi-scales. The spatial scale-dependency of the relationships between NDVI and environmental factors was identified by scaling the bandwidth of the GWR model, and the appropriate bandwidth of the GWR model for each variable was determined. All GWR models represented significant improvements of model performance over their corresponding ordinary least squares (OLS) models. GWR models also successfully reduced the spatial autocorrelations of residuals. The spatial relationships between NDVI and environmental factors significantly varied over space, and clear spatial patterns of slope parameters and local coefficient of determination (R ²) were found from the results of the GWR models. The study revealed detailed site information on the different roles of related factors in different parts of the study area, and thus improved the model ability to explain the local situation of NDVI.