Messerli, Peter; Heinimann, Andreas; Epprecht, Michael (2009). Finding Homogeneity in Heterogeneity - A New Approach to Quantifying Landscape Mosaics Developed for the Lao PDR. Human ecology, 37(3), pp. 291-304. New-York, NY: Springer US; http://www.springer-ny.com 10.1007/s10745-009-9238-1
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A key challenge for land change science in general and research on swidden agriculture in particular, is linking land cover information to human–environment interactions over larger spatial areas. In Lao PDR, a country facing rapid and multi-level land change processes, this hinders informed policy- and decision-making. Crucial information on land use types and people involved is still lacking. This article proposes an alternative approach for the description of landscape mosaics. Instead of analyzing local land use combinations, we studied land cover mosaics at a meso-level of spatial scale and interpreted these in terms of human–environmental interactions. These landscape mosaics were then overlaid with population census data. Results showed that swidden agricultural landscapes, involving 17% of the population, dominate 29% of the country, while permanent agricultural landscapes involve 74% of the population in 29% of the territory. Forests still form an important component of these landscape mosaics.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
08 Faculty of Science > Institute of Geography > Geographies of Sustainability 08 Faculty of Science > Institute of Geography > NCCR North-South Management Centre [discontinued] 10 Strategic Research Centers > Centre for Development and Environment (CDE) |
UniBE Contributor: |
Messerli, Peter, Heinimann, Andreas, Epprecht, Michael |
Subjects: |
300 Social sciences, sociology & anthropology > 330 Economics |
ISSN: |
0300-7839 |
Publisher: |
Springer US; http://www.springer-ny.com |
Language: |
English |
Submitter: |
Factscience Import |
Date Deposited: |
04 Oct 2013 15:21 |
Last Modified: |
05 Dec 2022 14:25 |
Publisher DOI: |
10.1007/s10745-009-9238-1 |
Web of Science ID: |
000268007000005 |
BORIS DOI: |
10.7892/boris.36571 |
URI: |
https://boris.unibe.ch/id/eprint/36571 (FactScience: 205306) |