AN INVESTIGATION OF LOCAL EFFECTS ON SURFACE WARMING WITH GEOGRAPHICALLY WEIGHTED REGRESSION (GWR)

Determining Effective Factors on Land Surface Temperature of Tehran Using LANDSAT Images And Integrating Geographically Weighted Regression With Genetic Algorithm

Due to urbanization and changes in the urban thermal environment and since the land surface temperature (LST) in urban areas are a few degrees higher than in surrounding non-urbanized areas, identifying spatial factors affecting on LST in urban areas is very important. Hence, by identifying these factors, preventing this phenomenon become possible using general education, inserting rules and al...

Spatial Modeling of Residential Crowding in Alexandria Governorate, Egypt: A Geographically Weighted Regression (GWR) Technique

Despite growing research for residential crowding effects on housing market and public health perspectives, relatively little attention has been paid to explore and model spatial patterns of residential crowding over space. This paper focuses upon analyzing the spatial relationships between residential crowding and socio-demographic variables in Alexandria neighborhoods, Egypt. Global and local...

Semiparametric geographically weighted generalised linear modelling in GWR 4.0

Mapping the results of local statistics: Using geographically weighted regression.

The application of geographically weighted regression (GWR) - a local spatial statistical technique used to test for spatial nonstationarity - has grown rapidly in the social, health and demographic sciences. GWR is a useful exploratory analytical tool that generates a set of location-specific parameter estimates which can be mapped and analysed to provide information on spatial nonstationarity...

An Extension of Geographically Weighted Regression with Flexible Bandwidths

Geographically weighted regression (GWR) (Brunsdon et al. 1996; Fotheringham et al. 2002) is a useful technique for modelling local spatial relationships between variables. The essential idea of GWR is that observations near to a model calibration point have more influence in the estimation of regression coefficients than observations farther away do. The standard GWR model employs a single ban...