Comber, Alexis and Brunsdon, Chris and Charlton, Martin and Harris, Paul
(2016)
Geographically weighted correspondence matrices for
local error reporting and change analyses: mapping
the spatial distribution of errors and change.
Remote Sensing Letters, 8 (3).
ISSN 2150-7058
Abstract
This letter describes and applies generic methods for generating local measures from the correspondence
table. These were developed by integrating the functionality of two existing R packages: gwxtab and
diffeR. They demonstrate how spatially explicit accuracy and error measures can be generated from
local geographically weighted correspondence matrices, for example to compare classified and reference
data (predicted and observed) for error analyses, and classes at times t1 and t2 for change analyses. The
approaches in this letter extend earlier work that considered the measures derived from correspondence
matrices in the context of generalized linear models and probability. Here the methods compute local,
geographically weighted correspondence matrices, from which local statistics are directly calculated. In
this case a selection of the overall and categorical difference measures proposed by Pontius and Milones
(2011) and Pontius and Santacruz (2014), as well as spatially distributed estimates of kappa coefficients,
User and Producer accuracies. The discussion reflects on the use of the correspondence matrix in
remote sensing research, the philosophical underpinnings of local rather than global approaches for
modelling landscape processes and the potential for policy and scientific benefits that local approaches
support.
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