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Abstract:The objective of this study was to analyze land use/land cover (LULC) changes in the landscape of Munessa-Shashemene area of the Ethiopian highlands over a period of 39 years . Satellite images of Landsat MSS (1973), TM (1986), ETM+ (2000, and RapidEye (2012) were used. All images were classified using object-based image classification technique. Accuracy assessments were conducted for each reference year. Change analysis was carried out using post classification comparison in GIS. Nine LULCs were successfully captured with overall accuracies ranging from 85.7% to 93.2% and Kappa statistic of 0.822 to 0.924. The classification result revealed that grasslands (42.3%), natural forests (21%), and woodlands (11.4%) were dominant LULC types in 1973. In 2012, croplands (48.5%) were the major LULC types followed by others. The change result shows that a rapid reduction in woodland cover of 81.8%, 52.3%, and 36.1% occurred between the first (1973-1986), second (1986-2000), and third (2000-2012) study periods, respectively. Similarly, natural forests cover decreased by 26.1% during the first, 21.1% during the second, and 24.4% during the third periods. Grasslands also declined by 11.9, 17.5, and 21.1% during the three periods, respectively. On the contrary, croplands increased in all three periods by 131, 31.5, and 22.7%, respectively. Analysis of the 39-year change matrix revealed that about 60% of the land showed changes in LULC. Changes were OPEN ACCESS Remote Sens. 2013, 5 2412 also common along the slope gradient and agro-ecological zones with varying proportions. Further study is suggested to investigate detailed drivers and consequences of changes.

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Understanding drivers of changes in land use/land cover (LULC) is essential for modeling future dynamics or development of management strategies to ameliorate or prevent further decline of natural resources. In this study, an attempt has been made to identify the main drivers behind the LULC changes that had occurred in the past four decades in Munessa-Shashemene landscape of the south-central highlands of Ethiopia. The datasets required for the study were generated through both primary and secondary sources. Combination of techniques, including descriptive statistics, GIS-based processing, and regression analyses were employed for data analyses. Changes triggered by the interplay of more than 12 drivers were identified related to social, economic, environmental, policy/institutional, and technological factors. Specifically, population growth, expansion of cultivated lands and settlements, livestock ranching, cutting of woody species for fuelwood, and charcoal making were the top six important drivers of LULC change as viewed by the local people and confirmed by quantitative analyses. Differences in respondents' perceptions related to environmental (i.e., location specific) and socioeconomic determinants (e.g., age and literacy) about drivers were statically significant (P = 0.001). LULC changes were also determined by distances to major drivers (e.g., the further a pixel is from the road, the less likelihood of changes) as shown by the landscape level analyses. Further studies are suggested targeting these drivers to explore the consequences and future options and formulate intervention strategies for sustainable development in the studied landscape and elsewhere with similar geographic settings.

Human pressure on a rugged and fragile landscape can cause land use/cover changes that significantly alter the provision of ecosystem services. Estimating the multiple services, particularly those obtained from agroforestry systems, is seldom attempted. A combined approach of geospatial technology, cross-sectional field investigations, and economic valuation of natural capital was used to develop an ecosystem service valuation (ESV) model to estimate changes in ESV between 1986 and 2015 in southern Ethiopia. Over 120 values were sourced, mainly from an ecosystem service valuation database and allied sources, to establish value coefficients via benefit transfer method. Our 1848 km 2 study landscape, with eight land use categories, yielded an annual total ESV of $129 × 10 6 in 1986 and $147 × 10 6 in 2015, a 14.2% ($18.3 million) increase in three decades, showing its relative resilience. Yet we observed losses of natural vegetation classes whose area and/or value coefficients were too small to offset their increased value from expanding agroforestry and wetland/marshes, which have the largest cover share and highest economic value, respectively. Appreciating the unique features of agroforests, we strongly recommend that their economic value is studied as a separate ecosystem for further valuation accuracy improvement.