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Doctorat
Pays-Bas
2004
Landscape change dynamics in a semi-arid part of Baringo District, Kenya, based on Landsat-TM-Data and GIS analysis
Titre : Landscape change dynamics in a semi-arid part of Baringo District, Kenya, based on Landsat-TM-Data and GIS analysis
Auteur : Benjamin Mwasi
Université de soutenance : Universiteit van Amsterdam
Grade : Doctor 2004
Résumé
Thee study area, a semi-arid area in the Baringo district of Kenya, is inhabited by
communitiess that mostly derive their livelihood directly from the environment, through
subsistencee agriculture and pastoralism. Consequently, the landscape in this area is
managedd with two major goals. The primary, and most compelling, goal being
maximisationn of the production function of the landscape. The second goal, which is
oftenn seen as secondary, is related to landscape’s information carrier function, where
conservationn of both biotic and abiotic resources for future use is considered to be
important.. Ideally, these objectives should be complementary for sustainability.
However,, in practice they tend to be competitive at best, otherwise conflicting. With
properr planning and management it is possible to approach this ideal situation. This study
investigatedd the possibilities of reducing conflicts between these objectives by increasing
thee understanding of the landscape change dynamics related to human exploitation of the
naturall resource base.
Thee study recognises the fact that landscape changes as a result of human
utilisationn of natural resources is inevitable. However, land degradation or continuous
loweringg of landscape quality, can be avoided through planning and management of
landscapee changes. Effective management requires, among other things, a) knowledge of
thee spatial distribution of resources, b) ability to monitor changes in quantity and quality
off these resources, c) knowledge of the factors causing or controlling these changes and,
d)) an understanding of how these factors interact to cause such changes. Satellite remote
sensingg and image processing software are capable of providing accurate and up-to-date
informationn relevant for locating and monitoring the quality of resources. By combining
temporallyy distributed land resource data with similar spatially referenced socio
economicc data in a geographic information system, the relationship between the two is
explored.. This relationship is analysed further using multivariate statistics to identify the
mostt important drives of land cover changes. Armed with this knowledge and appropriate
spatiall dynamic models the process of landscape change is modelled. The resultant
informationn can enable planners to predict future change patterns and also provide
managerss and policy makers a means for directing or controlling land cover changes
throughh deliberate introduction or elimination of specific change driver
Page publiée le 4 avril 2008, mise à jour le 2 juin 2022