Global inventory of landscape patterns and latent variables of landscape spatial configuration

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Supplementary Files

Jakub Nowosad , Tomasz Stepinski


We present a regionalization of the entire Earth’s landmass into land units of homogeneous landscape patterns. The input to the regionalization is a high resolution Global Land Cover (GLC) dataset. The GLC is first divided into local landscapes – small non-overlapping square blocks of GLC cells. These blocks are agglomerated into much larger land units using a pattern-based segmentation algorithm. These units are tracts encompassing cohesive patterns of land cover and the procedure divides the entire landmass into tracts of land with discernibly different patterns. We characterize a pattern in each unit by a set of 39 landscape metrics. The resulting spatial database of land units is the major product of this study. We make this database freely available to the community in order to provide foundational information for studies aiming at explaining relationships between landscape pattern and ecological process and between the process and patterns and their controlling factors. The procedure of obtaining the database is described, the quality assessment of units delineation is given, and the statistics of the major properties of the units are presented. To showcase the utility of the new database we use it to demonstrate that a variability of geometric configurations of landscape patterns worldwide can be captured in terms of only two variables – complexity and aggregation – as they explain 70% of the variability. This allows for a meaningful, two-dimensional classification and mapping of landscape patterns on the basis of their geometry. Such mapping reveals that the majority of terrestrial landscapes are characterized by a simple, frequently monothematic, pattern of land cover. Thus, landscapes on Earth are mostly segregated by the land cover type and complex landscapes with a diverse mix of different land cover types are rare exceptions from the prevailing monothematic cover.



Biodiversity, Earth Sciences, Environmental Indicators and Impact Assessment, Environmental Sciences, Geographic Information Sciences, Geography, Life Sciences, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science


complexity, regionalization, aggregation, Global land cover, landscape metrics, spatial pattern


Published: 2018-02-15 19:20


CC BY Attribution 4.0 International