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Articles

Modelling the dynamics of landscape transformations and population growth in the highlands of Ethiopia using remote-sensing data

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Pages 5647-5667 | Received 14 Jul 2015, Accepted 28 Sep 2016, Published online: 31 Oct 2016
 

ABSTRACT

This study models landscape transformations and settlement dynamics in a highland area of Ethiopia over a 56 year period (1957–2013). The analyses were performed using aerial photographs, satellite images, and field data. The remotely sensed images were geometrically and radiometrically corrected. Visual interpretation of aerial photographs and supervised classification of multispectral satellite images using the maximum likelihood algorithm were chosen for land-cover mapping. The population size was estimated by counting the houses on the aerial photographs and on the high-resolution images, and by direct census. The overall trend showed an increase of cropland and a decrease of other types of land cover. Landscape transformation rates recently slowed down due to ownership and policy restrictions. The average cropland holding size per family has decreased from 2.6 to 1.1 ha due to the exponential growth of the population. The relationship between settlement and cropland expansion is statistically significant. Models of logistic growth were fitted to the cropland area, and models of exponential and logistic growth to the population development to estimate the carrying capacity. The concomitant increase of population and the decrease of cropland per head resulted in a shortage of food and energy, highlighting the importance of policy decisions on land management.

Acknowledgements

We gratefully acknowledge the Austrian Partnership Programme in Higher Education and Research for Development (APPEAR) for funding this PhD study. We extend our thanks to the Institute of Surveying, Land Information and Remote Sensing of the University of Natural Resources and Life Sciences (BOKU) for purchasing IKONOS and WorldView-2 data sets. Dr Thomas Bauer and Mag. Franz Suppan are highly acknowledged for their technical assistance during image processing. We thank Kalypso Schulmeister and Bradley Matthews for proofreading the manuscript. We acknowledge the two anonymous reviewers.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Austrian Partnership Programme in Higher Education and Research for Development (APPEAR).

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