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Title: Modelling land-use decision-making in encroached forests, Copperbelt Province, Zambia
Author: Akombelwa, Mulemwa
ISNI:       0000 0004 2716 1680
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2011
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Natural resource management is an important issue around the world in the light of increased global population size and the subsequent demands arising from an increased need for food, clean water and other ecosystem services. This has often resulted in the encroachment of protected areas and the adoption and maintenance of unsustainable land use practices. This study is concerned with the development of tools that will help us understand the characteristics of land use decision-making by people who illegally settle in protected areas. The study has the main aim of developing a model of local stakeholder land-use decision-making for the encroached forest areas in the Copperbelt Province of Zambia. This will allow the modelling of the stakeholder land-use practices. This will help predict their effects on the environment of the Province. Soft Systems Methodology (SSM) was used to develop a conceptual model of land use decision making in the study area and the outputs from SSM were used to develop a Belief Network (BN) model of land use decision making in the study area. Decision trees were also used to model the land use decision-making characteristics of the local stakeholders in the area. The findings suggest that SSM is a useful tool for the modelling of the complex problem situation in the study area and the subsequent development of solutions to the problems identified through participatory approaches. The research also showed that BNs and decision trees were able to model land use decision-making by using the agricultural activity as a basis for analysis. The findings suggest that BNs and decision trees are complementary and have the potential for addressing applications in land-use decision-making in informal settlements where available information is more likely to be scant and disparate.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Q Science (General) ; HD Industries. Land use. Labor