Preservation of Spatial Information in Rasterization Processes: A Practical Approach Using Real Categorical Data and Landscape Metrics

Abstract

Rasterization (i.e., vector-to-raster conversion) is a common process in geographic information systems. As it implies redistribution of map information, it is important to know how much data are lost when a particular resolution is chosen, in order to use data successfully. This study explores the potential of landscape metrics to reflect sensitivity to rasterization processes. A vectorial land use map was rasterized to an array of cell sizes. Deviation from original data was estimated, and landscape metrics were calculated for each land cover class. Results allowed grouping of classes—with respect to how information was preserved—depending on their landscape characteristics.