Local Models for Spatial Analysis

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Spatially Weighted Interaction Models (SWIM) (2016, background): “The resulting global parameter estimates represent average interaction behavior across the entire study area (Lloyd 2011) and suggest that the number of commuters leaving an origin increases at a decreasing rate as the economically active population increases (a); the number of commuters arriving at”
Spatial non-stationarity and scale-dependency of prediction accuracy in the remote estimation of LAI over a tropical rainforest in Sulawesi, Indonesia. (2009, methodology): “These problemsmay be overcome or significantly reduced through implication of local regression techniques such as spatial expansion method, moving window regression (Lloyd, 2007) and geographically weighted regression (Fotheringham et al.”
Local regression models for spatial interpolation of urban heat island—an example from Wrocław, SW Poland (2012, methodology): “…location i can be expressed as (Cressie 1991; Wackernagel 2003): "i ¼ X k lk"k ð13Þ While GWR can be used for spatial interpolation of climate elements (Lloyd 2007), the novelty of this paper is the introduction of geostatistical (kriging, OK) interpolation of GWR residuals that has not been…”
Nonstationary models for exploring and mapping monthly precipitation in the United Kingdom (2009, neutral): “IDW was applied as it is such a widely used spatial interpolation procedure (see, e.g. Burrough and McDonnell, 1998; Lloyd, 2006, for summary and examples).”