Assessing driving forces of land use and land cover change by a mixed-method approach in north-eastern Ghana, West Africa

被引:148
作者
Kleemann, Janina [1 ,2 ]
Baysal, Guelendam [2 ]
Bulley, Henry N. N. [3 ]
Fuerst, Christine [4 ]
机构
[1] Karlsruhe Inst Technol, Inst Meteorol & Climate Res, Atmospher Environm Res IMK IFU, Kreuzeckbahnstr 19, D-82467 Garmisch Partenkirchen, Germany
[2] Univ Bonn, Ctr Dev Res ZEF, Walter Flex Str 3, D-53113 Bonn, Germany
[3] CUNY, BMCC, Dept Social Sci Human Serv & CRJ, Geog & GISci, New York, NY 10007 USA
[4] Martin Luther Univ Halle Wittenberg, Inst Geosci & Geog, Sustainable Landscape Dev, Von Seckendorff Pl 4, D-06120 Halle, Germany
关键词
Land degradation; Population pressure; Remote sensing; Expert interviews; Agriculture; Upper East Region; CLIMATE-CHANGE; ADAPTATION STRATEGIES; EXPERT KNOWLEDGE; DYNAMICS; PERCEPTIONS; STRESSORS; MIGRATION; FRAMEWORK; SECURITY; DROUGHT;
D O I
10.1016/j.jenvman.2017.01.053
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Land use and land cover change (LULCC) is the result of complex human-environmental interactions. The high interdependencies in social-ecological systems make it difficult to identify the main drivers. However, knowledge of key drivers of LULCC, including indirect (underlying) drivers which cannot be easily determined by spatial or economic analyses, is essential for land use planning and especially important in developing countries. We used a mixed-method approach in order to detect drivers of LULCC in the Upper East Region of northern Ghana by different qualitative and quantitative methods which were compared in a confidence level analysis. Viewpoints from experts help to answer why the land use is changing, since many triggering effects, especially non-spatial and indirect drivers of LULCC, are not measurable by other methodological approaches. Geo-statistical or economic analyses add to validate the relevance of the expert-based results. First, we conducted in-depth interviews and developed a list of 34 direct and indirect drivers of LULCC. Subsequently, a group of experts was asked in a questionnaire to select the most important drivers by using a Likert scale. This information was complemented by remote sensing analysis. Finally, the driver analysis was compared to information from literature. Based on these analyses there is a very high confidence that population growth, especially in rural areas, is a major driver of LULCC. Further, current farming practice, bush fires, livestock, the road network and climate variability were the main direct drivers while the financial capital of farmers and customary norms regarding land tenure were listed as important indirect drivers with high confidence. Many of these driving forces, such as labour shortage and migration, are furthermore interdependent. Governmental laws, credits, the service by extension officers, conservational agriculture and foreign agricultural medium-scale investments are currently not driving land use changes. We conclude that the mixed-method approach improves the confidence of findings and the selection of most important drivers for modelling LULCC, especially in developing countries. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:411 / 442
页数:32
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