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RESEARCH PRODUCT
Comparison of input data with different spatial resolution in landscape pattern analysis – A case study from northern Latvia
Aivars TēraudsOļģerts NikodemusGuntis BrumelisZigmārs Rendeniekssubject
0106 biological sciencesCartographic generalization010504 meteorology & atmospheric sciencesGeography Planning and DevelopmentForestryLand cover010603 evolutionary biology01 natural sciencesVariable (computer science)GeographyThematic mapHabitatTourism Leisure and Hospitality ManagementSpatial ecologyScale (map)CartographyImage resolution0105 earth and related environmental sciencesGeneral Environmental Sciencedescription
A suitable spatial scale needs to be selected in geographical and landscape ecological research, and this requires great consideration as different scales have profound effect on derived landscape spatial patterns. Numerous studies have investigated the effects of different scales on landscape metrics using simulated patterns, but few have been conducted to compare different data sources with variable scale for regional- and landscape-scale assessments. Possibly this has occurred because researchers have been prone to use the best available source, a well-known standard, and easiest to use. This study was conducted to assess the impact of input data resolution on values of landscape pattern metrics in four landscapes at scales 1:10 000, 1:50 000 and 1:100 000. The aim was to determine the applicability of three data sources for thematic models in landscape pattern analyses in the Eastern Baltic region. We found that the utility of CORINE Land Cover data for comprehensive structural assessment in mosaic-type landscapes was very limited, as the level of cartographic generalization excluded many small and linear landscape structure elements with potentially high importance for landscape functioning, such as habitat continuity. We also found that actual area harvested using clearcuts was considerably higher than shown in CORINE data, due to clearcuts size being much smaller than the minimum mapping unit. In the light of this, we suggest using data with spatial resolution corresponding to a cartographic scale of at least 1:50 000, in cases when spatial patches have size up to 25 ha.
year | journal | country | edition | language |
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2017-06-01 | Applied Geography |