Abstract

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.

Highlights

  • Global land cover (GLC) maps are obtained by classifying pixels in a global mosaic of Earth observation (EO)images into several categories of Earth’s surface properties

  • (2) Using the newly created database, we demonstrated that the variance in spatial configurations of landscape mosaics worldwide is sufficiently captured (71%) by only two variables which we call complexity and aggregation

  • We use FRAGSTATS definitions to calculate a set of 39 landscape-level metrics, 22 of them are percentages of area covered by contributing land cover categories (PLANDs in the landscape metrics nomenclature) – they characterize the composition of the patterns, and 17 of them are configurational landscape metrics

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Summary

Introduction

Global land cover (GLC) maps are obtained by classifying pixels in a global mosaic of Earth observation (EO). Frequently it is a spatial pattern of land cover categories rather than a category itself that is of environmental or ecological interest This is because grid cells of GLC maps are too small units of an area to be used for analysis on regional, continental or global scale. At such coarse scales a landscape pattern (LP) – an area having discernibly cohesive spatial arrangement (mosaic) of land cover categories – is a more natural unit of analysis (Wickham and Norton, 1994; Riitters et al, 2000; Riitters, 2011; Omernik and Griffith, 2014). – the first step to a complete classification of land cover patterns

Methods
Regionalization of landscape patterns
Landscape metrics
Regionalization results
Finding latent variables of landscape configuration
C–A diagram
Mapping landscape configuration types
Findings
Conclusions and discussion
Full Text
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