Indicators of landscape diversity derived from remote sensing based land cover maps – spatial and thematic aspects

Landscape is heterogeneous part of the Earth surface, forming mosaic of various habitats organized at different scales and levels (Johnson et al. 1992). The landscape pattern has important impact on ecological processes; hence its analysis through quantitative measures is essential for environmental studies. There are many indicators characterizing spatial structure of landscape at different level of detail; they enable analysis of landscape fragmentation at patch level, through studies at habitat level up to complex analyses at landscape level. Seven indicators, which are related to various levels of detail, were selected at the presented work. The following indicators have been studied: Patch Density, Edge Density, Patch Richness, Simpson Diversity Index, Natural Patch Richness, Percentage of Natural Landscape, Mean Natural Patch Area (McGarigal & Marks 1995). First two indicators were used for analysis of landscape fragmentation at patch level, next two at land cover level, while the last three were applied for studies of natural and semi-natural classes at both levels. The studies were performed at six test areas located in different regions of Europe (France, Germany, Poland, Latvia, Spain and Italy), using two different land cover maps. First map was based on Very High Resolution (VHR) Kompsat satellite images (4 m spatial resolution); it included 8 land cover categories with 0.25 ha Minimum Mapping Unit (MMU). CORINE Land Cover (CLC) map 2006 (25 ha MMU) was the second map used for analyses. Number of land cover classes in case of CLC map varied from 9 for Poland till 14 for France. All above mentioned indicators were calculated for grids with 100, 200, 500 and 1000 meter cell size, corresponding to 1, 4, 25 and 100 ha, respectively. The obtained results reveal high usefulness of land cover maps based on VHR satellite images for analysis of landscape fragmentation, even for grids with 100 m cell size. It was found that at patch level these materials are superior to CLC classifications, irrespective of cell area. In case of land cover level VHR data are better while using 100 and 200 m grid cells, whereas for larger cell sizes – 500 and 1000 m – results are not so evident, depending on degree of landscape fragmentation and spatial structure characteristic for individual land cover classes