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University of Helsinki (2015)

Multi-scale assessment of land changes in Ethiopia understanding the impact of human activities on ecosystem services

Hailu, Binyam Tesfaw

Titre : Multi-scale assessment of land changes in Ethiopia understanding the impact of human activities on ecosystem services

Auteur : Hailu, Binyam Tesfaw

Université de soutenance : University of Helsinki

Grade : Doctroral Thesis 2015

Résumé
Remote sensing provides land-cover information on a variety of temporal and spatial scales. The increasing availability of remote sensing data is now a major factor in land-change analysis and in understanding its impact on ecosystem services and biodiversity. This wider accessibility is also leading to improvements in the methods used to integrate these data into land-cover modelling and change analysis. Despite these developments in current technology and data availability however, there are still questions to be addressed regarding the dynamics of land cover and its impact, particularly in areas such as Ethiopia where the human population is expanding and there is a need for improvement in the management of natural resources. Multi-scale approaches (from the national to the local) were used in this thesis to assess change in land cover and ecosystem services in Ethiopia, specifically in terms of provisioning (the production of food, i.e. cash crops) and regulating (climate control for vegetation cover). These assessments were based on multi-scale remote sensing (very high spatial resolution remote aerial sensing, high-resolution SPOT 5 satellite imaging and products of medium-resolution satellite remote sensing) and climate data (e.g., precipitation, temperature).
The main focus in this thesis is on mapping and modelling the spatial distribution of vegetation. This includes : (i) forest mapping (indigenous and exotic forests), (ii) modelling the probabilistic presence of understory coffee, (iii) Coffea arabica species distribution modelling and mapping and (iv) simulating pre-agricultural-expansion vegetation cover in Ethiopia.
The results of the applied predictive modelling were robust in terms of : (i) identifying and mapping past vegetation cover and (ii) mapping understory shrubs such as coffee plants that grow as understory. I present a reconstruction of earlier vegetation cover that mainly comprised broadleaved evergreen and deciduous forest but was replaced in the course of agricultural expansion. Given the spatial scale of the latter, the environmental modelling was complemented with high spatial resolution satellite (2.5m) and aerial images (0.5m). The results of the Object Based Image Analysis show that indigenous forests were separated from exotic forests. Current and future suitable locations that are environmentally favourable for the growth of understory coffee were identified and mapped in the coffee-growing areas of Ethiopia.
In conclusion, the information presented in this thesis, based on the multi-scale assessment of land changes, should lead to the better-informed management of natural resources and conservation, and the restoration of major areas affected by human population growth.

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