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There is no single correct or optimal scale for describing spatial landscape heterogeneity. However, since landscape patterns are scale-dependent, using different scales in the analysis may result in different outcomes, which can affect landscape management options. The main goal of our research was to identify the most adequate GIS solution for converting vector data to raster data while keeping the spatial continuity of most linear features and input land cover data as detailed as possible. In addition, to compare our database with the CORINE Land Cover data approach, we used 3 different rasterization methods and raster data with 100- and 50-m pixel sizes, first, to match the geometric accuracy of the CORINE Land Cover data and second, to compare the calculation results acquired with the higher-resolution rasterized BDOT10k data. We found that it was possible to compare these methods and assess how much data resolution and selection of rasterization methods affected the calculations of the landscape metrics. The calculation results of specific fragmentation metrics differed tremendously when higher data resolutions and rasterization methods were used, especially when using the custom priority rasterization method.
Kubacka et al. (Wed,) studied this question.