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Van Asselen, Sanneke; Verburg, Peter H.; 2012. A L and S ystem representation for global assessments and land‐use modeling, Global Change Biology, 18, 3125–3148.
| Author(s)
|
Sanneke, Van Asselen; Peter H., Verburg;
|
| Title
|
A L and S ystem representation for global assessments and land‐use modeling
|
| Journal
|
Global Change Biology
|
| Journal Abbreviation
|
Global Change Biology
|
| Book title
|
|
| Volume
|
18
|
| Issue
|
10
|
| ISSN
|
1354-1013, 1365-2486
|
| URL
|
external URL
|
| DOI
|
10.1111/j.1365-2486.2012.02759.x
|
| Pages
|
3125–3148
|
| Date
|
2012-10
|
| Abstract
|
Abstract
Current global scale land‐change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land‐use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (
LS
) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map
LS
using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of
LS
. The analysis of the spatial determinants of
LS
indicates strong associations between
LS
and a range of socioeconomic and biophysical indicators of human‐environment interactions. The set of identified spatial determinants of a
LS
differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi‐)Natural
LS
have more similar spatial determinants across regions and scales. Using
LS
in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land‐use intensity and landscape composition. Because the set of most important spatial determinants of
LS
varies among regions and scales, land‐change models that include the human drivers of land change are best parameterized at sub‐global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions.
|
| Language
|
en
|
| Catalog
|
DOI.org (Crossref)
|
| Retrieve date
|
2026-02-12
|
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