Show simple item record

dc.contributor.authorNg’ang’a, Leah Muthoni
dc.date.accessioned2014-12-01T12:02:50Z
dc.date.available2014-12-01T12:02:50Z
dc.date.issued2014
dc.identifier.citationMaster of arts in Population studiesen_US
dc.identifier.urihttp://hdl.handle.net/11295/75795
dc.description.abstractForest resources in Kenya are valuable and need to be sustainably managed for present and future generations. Forests are important to our ecological, economic and social wellbeing. They offer a range of benefits and opportunities; they provide wood and non-wood products, recreational opportunities and other non-market goods and services such as water and clean air. But these resources are under serious threat, as a result of the rapidly expanding human population, which is constantly putting pressure on the natural resource base. Kenya continues to face the challenge of managing its natural resources which people use unsustainably. In the face of a rapidly growing population land cover in Kenya has been greatly transformed and in contemporary times, issues of sustainable development, environmental change and related issues of human-environment interaction have been a major concern. The aim of this study was to empirically establish how changes in population density have affected forest cover. The study provided an opportunity of linking environmental science with social science using Remote Sensing and Geographical Information System (GIS) techniques to integrate vegetation cover data with population data. Remote Sensing data extracted from Advanced Very High Resolution Radiometer (AVHRR) NOAA-series satellites was used as a remotely sensed measure of forest cover to determine NDVI trends for 24 years and also to establish the association between population density and NDVI. Remote Sensing data from Landsat 5 and 7 satellites was used to analyse forest cover changes at detailed scales based on the spatial models built in ArcGIS Software. Multiple regression analysis was conducted to determine the significance of rainfall and population density on NDVI and polynomial regression model was run to establish the relationship between population density and NDVI. NDVI trends revealed that there was a general increase in forest cover in all study counties but with some years showing forest decline. Narok and Machakos had significant decline from 1998 while in some counties NDVI increased with higher values than in others. The relationship between population density varied within counties with Nyeri, Nyandarua. Baringo and West Pokot showing a positive relationship while Narok and Machakos showed a negative relationship. Spatial analysis show large extent of forest decline in Narok and large extent of forest regeneration in Nyeri county. It was apparent from the study that population density is a key factor contributing to forest cover change in most counties, (either negatively or positively) depending on the activities that people are engaged in. Nevertheless there are other factors that also influence forest cover and these vary within counties. They vary from changes in rainfall, land ownership, land use policies, market economies, rangeland/grassland restoration, reforestation, deforestation and culture. The main concern in conserving forest therefore, should not necessarily be increase in population density but also, the activities that people engage in and that a detailed understanding of the complex set of factors affecting forest cover change in a given location is required prior to any intervention. The challenge of rapid population growth and natural resource degradation are not isolated from one another; they are intimately related and it is important for strategic planning and development programming to focus on them together taking into account their interrelationship.en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.titleExploring Population Density and Forest Cover Linkages: Evidence From Kenyaen_US
dc.typeThesisen_US
dc.type.materialen_USen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record