Map projections for global and continental data sets and an analysis of pixel distortion caused by reprojection

Abstract

With growing emphasis on global monitoring, research using remotely sensed data and geographic information systems is increasingly focused on large regions studied at small scales. These global change studies require the integration of data sets from several sources that are reprojected to a common map base. In small-area, large-scale studies the choice of a map projection has little effect on data quality. In global change studies the effects of map projection properties on data quality are more apparent, and the choice of projection is more significant. To aid compilers of global and continental data sets, six equal-area projections were chosen : the interrupted Goode Homolosine, the interrupted Mollweide, the Wagner IV, and the Wagner VII for global maps ; the Lambert Azimuthal Equal-Area for hemisphere maps ; and the Oblated Equal-Area and the Lambert Azimuthal Equal-Area for continental maps. Distortions in small-scale maps caused by reprojection, and the additional distortions incurred when reprojecting raster images, were quantified and graphically depicted. For raster images, the errors caused by the usual resampling methods (pixel brightness level interpolation) were responsible for much of the additional error where the local resolution and scale change were the greatest.

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