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Curve Fit: a pixel‐level raster regression tool for mapping spatial patterns
Author(s) -
Jager Nathan R.,
Fox Timothy J.
Publication year - 2013
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12068
Subject(s) - raster graphics , pixel , range (aeronautics) , raster data , spatial analysis , computer science , sampling (signal processing) , inference , statistics , regression , data mining , mathematics , artificial intelligence , computer vision , materials science , filter (signal processing) , composite material
SummaryDespite the fact that pixels (i.e. picture elements) are the basic sampling units of maps, we are aware of no software package or tool that allows users to model changes that may occur at such fine spatial resolutions over broad geographic extents. Curve Fit is an extension to the application ArcMap that allows users to conduct linear or nonlinear regression analysis on the range of values found within input raster data sets (geo‐referenced images), independently for each pixel. Outputs consist of raster surfaces of regression model parameter estimates, standard errors, goodness‐of‐fit estimates and multimodel inference measures. Curve fit outputs characterize continuous spatial or temporal change across a series of raster data sets.