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Introduces Geographically Weighted Regression, a spatially explicit approach to measure relationships between variables with location-specific outputs.
Explores spatially dense air and water quality monitoring in urban areas, emphasizing the importance of environmental monitoring and showcasing various sensor systems.
Explores spatial regression models, addressing spatial autocorrelation challenges and the concept of spatial lag models to correct biases and improve inference accuracy.
