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Norwegian University of Life Sciences, Ås (2015)

Analysis of land use / land cover change dynamics and underlying driving forces in the Lake Hawassa Watershed, Ethiopia, based on satellite remote sensing, GIS and field investigations

Tedo, Nigatu Wondrade

Titre : Analysis of land use / land cover change dynamics and underlying driving forces in the Lake Hawassa Watershed, Ethiopia, based on satellite remote sensing, GIS and field investigations

Analyse av endringer i arealbruk/arealdekke og bakenforliggende mekanismer i nedslagsfeltet til Lake Hawassa i Etiopia, basert på satelittfjernmåling, GIS og feltundersøkelser

Auteur : Tedo, Nigatu Wondrade

Université de soutenance : Norwegian University of Life Sciences, Ås

Grade : Philosophiae Doctor (PhD) 2015

Résumé
Lake Hawassa Watershed, in the Central Rift Valley, is one of the most environmentally vulnerable areas in Ethiopia. The rapidly increasing population and vegetation clearance in search of farming and grazing land, firewood, and construction materials have exerted pressure on the natural resources of the region. To understand the ongoing resource degradation and formulate mitigation strategies, accurate and timely information about land use land cover (LULC) changes and the driving forces is indispensable. Remote sensing and GIS are important tools for monitoring, mapping, and modelling of LULC changes at different spatial and temporal scales in order to assess the extent, direction and causes of the changes.

The present research aimed at filling the biophysical data gap in the area underrepresented by existing literature and thereby contribute knowledge to support informed decision making in sustainable resource management. Specifically, the study intended to : (a) Classify multi-temporal image data to produce land cover (LC) maps and quantify changes that have occurred over the study period, (b) Classify image data sets in the urban environment and extract the magnitude of built-up areas in order to quantify the rate of urban growth, test the relationship between observed and expected growth, and examine the degree of urban sprawl, (c) Delineate forest cover using remotely sensed data for the base year 2011, estimate above ground biomass (AGB) and carbon stock using forest inventory data and allometric equations, and evaluate the diversity and dominance of species in the ecosystem, and (d) Quantify the spatial and temporal dimensions of LULC conversions from the classified Landsat images extending over the period of 38 years, conduct key informant interviews and identify the most prominent underlying driving forces (UDFs) of LULC changes, and analyze the identified driving forces with a particular focus on LULC conversion and deforestation.

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