Land-use and land-cover change processes in the Upper Uruguay Basin: linking environmental and socioeconomic variables

• Published in: Landscape ecology Vol. 28; no. 2; pp. 311 - 327
• Main Authors: de Freitas, Marcos Wellausen Dias, Santos, João Roberto dos, Alves, Diógenes Salas
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-02-2013; Springer; Springer Nature B.V
• Subjects: Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Biomedical and Life Sciences; Ecology; Environmental Management; Freshwater; Fundamental and applied biological sciences. Psychology; General aspects; Land use; Landsat; Landscape; Landscape Ecology; Landscape/Regional and Urban Planning; Life Sciences; Nature Conservation; Remote sensing; Research Article; River basins; Silviculture; Socioeconomic factors; Socioeconomics; Spatial analysis; Sustainable Development; Urbanization; South America; Uruguay; America; Argentina, Uruguay R. basin; Spatial clustering; Nature and society; Landscape structure; Canonical correspondence analysis; Geographically weighted regression; Land use and cover change; Landscape; Regression; Environmental factor; Socioeconomics; Land use; Canonical analysis; Correspondence analysis; Plant cover
• ISSN: 0921-2973; 1572-9761
• DOI: 10.1007/s10980-012-9838-9

Land-use and land-cover change affects both ecological and socioeconomic processes, motivating the integration of environmental and socioeconomic data to help understand this change. In this study, we propose a method for the characterisation and spatial analysis of land use and cover change in the Upper Uruguay River Basin (Brazil) based on (i) the characterisation of six LUCC processes—degradation, regeneration, intensification, extensification, silviculture expansion and urbanisation—by the combination of 2002 and 2008 land-use and land-cover classifications of Landsat/TM imagery and on (ii) the investigation of the relationships between the LUCC processes and environmental and socioeconomic variables via the combination of canonical correspondence analysis, linear and local spatial regression models (OLS and GWR) and spatial clustering procedures (SKATER), using environmental data, including geomorphometric data, landscape metrics and census socioeconomic statistics. The LUCC processes could be explained in terms of the associations between the selected physical, ecological and social variables that allowed the terrain, landscape fragmentation and socioeconomic characteristics to be related to various LUCC processes.