Physical or geographic location proves to be an important feature in many data science models, because diverse natural and social phenomenon have a spatial component. Spatial autocorrelation measures the extent which locally adjacent observations of same are correlated. Although statistics like Moran’s I Geary’s C widely used measure autocorrelation, they slow: All popular methods run $$\Omega ...

Exploring the spatial variations and impact of social factors on commuting behavior is vital to promote cities’ sustainable development improve residents’ daily lives. Based 2015 1% Population Sample Survey data in Shanghai, this study constructs an improved accessibility index evaluate jobs–housing relationship compares duration distance at sub-district level by using autocorrelation analysis,...