By incorporating temporal effects into the geographically weighted regression (GWR) model,
an extended GWR model, geographically and temporally weighted regression (GTWR), has …

THE DICTIONARY OF HUMAN GEOGRAPHY 'Even better than before, the Dictionary is an
essential tool for all human geographers and over the years has provided an invaluable …

Spatial data contain locational information as well as attribute information. It is increasingly
recognized that most data sets are spatial in that the attribute being measured is typically …

Geographically weighted regression (GWR) is an important local technique for exploring
spatial heterogeneity in data relationships. In fitting with Tobler's first law of geography, each …

Present methodological research on geographically weighted regression (GWR) focuses
primarily on extensions of the basic GWR model, while ignoring well-established diagnostics …

In this study, we present a collection of local models, termed geographically weighted (GW)
models, which can be found within the GWmodel R package. A GW model suits situations …

In this chapter we review the concept of spatial autocorrelation and its attributes. Our
purpose is to outline the various formulations and measures of spatial autocorrelation and to …

Geographically weighted regression (GWR) was proposed in the geography literature to
allow relationships in a regression model to vary over space. In contrast to traditional linear …

The regression analyses undertaken commonly in remote sensing are aspatial, ignoring the
locational information associated with each sample site at which the variables under study …

Revealing spatially varying relationships between urban growth patterns and underlying
determinants is important for better understanding local dimensions of urban development …