A Quantile Regression Approach to Areal Interpolation

摘要: Areal interpolation has been developed to provide attribute estimates whenever data compilation or an analysis requires a change in the measurement support. Over time numerous approaches have proposed solve problem of areal interpolation. Quantile regression is used this study as basis interpolator because it provides conditioned on local parameters rather than global ones. An empirical case provided using set northern New England. Land cover data, by National Oceanic Atmospheric Administration, derived from remotely sensed images for 2001 captured LANDSAT Thematic Mapper at resolution 30 × meters, are ancillary variables model. The utility quantile method evaluated against simple averages, weighting, dasymetric interpolation, and ordinary least squares spatial methods. For study, results ...