Raster images generalization in the context of research on the structure of landscape and geodiversity

Abstract

Generalization is one of the most important stages of work on cartographic data. It has a particular importance in the study of landscape structure, especially geodiversity. In raster images, it is based on modifying the structure of the image while maintaining its general characteristics. In ArcGIS software, the most important tools for generalization of raster images include: Boundary Clean and Majority Filter. Fragstat software was used for the analysis of structural modifications of the output images and assessment of the effects of generalization. Depending on the options used, both tools (Boundary Clean and Majority Filter) cause different types of modifications in rasters. Elimination of the so-called noise using one of the variants of Majority Filter is the most suitable if we wish to introduce only subtle modifications to the final image. If, however, we expect a greater level of interference in the structure of the source images, using Boundary Clean becomes necessary.