Land use / land cover (LULC) change assessment is getting more consideration by global environmental change studies as land use change is exposing dryland environments for transitions and higher rates of resource depletion. The semiarid regions of northwestern Ethiopia are not different as land use transition is the major problem of the region. However, there is no satisfactory study to quantify the change process of the region up to now. Hence, spatiotemporal change analysis is vital for understanding and identification of major threats and solicit solutions for sustainable management of the ecosystem. LULC change studies focus on understanding the patterns, processes and dynamics of land use transitions and driving forces of change. The change processes in dryland ecosystems can be either seasonal, gradual or abrupt changes of random or systematic change processes that result in a pattern or permanent transition in land use. Identification of these processes of change and their type supports adoption of monitoring options and indicate possible measures to be taken to safeguard this dynamic ecosystem. This study examines the spatiotemporal patterns of LULC change, temporal trends in climate variables and the insights of the communities on change patterns of ecosystems. Landsat imagery, MODIS NDVI, CRU temperature, TAMSAT rainfall and socio-ecological field data were used in order to identify change processes. LULC transformation was monitored using support vector machine (SVM) algorithm. A cross-tabulation matrix assessment was implemented in order to assess the total change of land use categories based on net change and swap change. In addition, the pattern of change was identified based on expected gain and loss under a random process of gain and loss, respectively. Breaks For Additive Seasonal and Trend (BFAST) analysis was employed for determining the time, direction and magnitude of seasonal, abrupt and trend changes within the time series datasets. In addition, Man Kendall test statistic and Sen’s slope estimator were used for assessing long term trends on detrended time series data components. Distributed lag (DL) model was also adopted in order to determine the time lag response of vegetation to the current and past rainfall distribution. Over the study period of 1972- 2014, there is a significant change in LULC as evidenced by a significant increase in size of cropland of about 53% and a net loss of over 61% of woodland area. The period 2000-2014 has shown a sharp increase of cropland and a sharp decline of woodland areas. Proximate causes include agricultural expansion and excessive wood harvesting; and underlying causes of demographic factor, economic factors and policy contributed the most to an overuse of existing natural resources. In both the observed and expected proportion of random process of change and of systematic changes, woodland has shown the highest loss compared to other land use types. The observed transition and expected transition under random process of gain of woodland to cropland is 1.7%, implies that cropland systematically gains to replace woodland. The comparison of the difference between observed and expected loss under random process of loss also showed that when woodland loses cropland systematically replaces it. The assessment of magnitude and time of breakpoints on climate data and NDVI showed different results. Accordingly, NDVI analysis demonstrated the existence of breakpoints that are statistically significant on the seasonal and long term trends. There is a positive trend, but no breakpoints on the long term precipitation data during the study period. The maximum temperature also showed a positive trend with two breakpoints which are not statistically significant. On the other hand, there is no seasonal and trend breakpoints in minimum temperature, though there is an overall positive trend along the study period. The Man-Kendall test statistic for long term average Tmin and Tmax showed significant variation where as there is no significant trend within the long term rainfall distribution. The lag regression between NDVI and precipitation indicated a lag of up to forty days. This proves that the vegetation growth in this area is not primarily determined by the current precipitation rather with the previous forty days rainfall. The combined analysis showed declining vegetation productivity and a loss of vegetation cover that contributed for an easy movement of dust clouds during the dry period of the year. This affects the land condition of the region, resulting in long term degradation of the environment

Technical complexities and the high cost of satellite images have hindered the adoption of remote sensing technology and tools for nature conservation works in Ethiopia as in many developing countries. The terrestrial and aquatic ecosystems in Abijjata Shala Lakes National Park (ASLNP) and the Important Bird Areas (IBAs) around the park are considered to be one of the most important home ranges for birds. However, little is known about the effect of land use/land cover (LULC) dynamics, due to lack of technical know how and logistical problems. However, it has been shown in this study that sophisticated image management works are not always relevant. Instead a simple method of utilizing the thermal band has been demonstrated. A new approach of long-term dynamics analysis method has also been suggested. A successful classification of images was achieved after such simple enhancement tests. It has been discovered that, there were more active LULC change processes in the area in the first study period (1973 to 1986) than during the second study period (1986-2000). In the first period nearly half of the landscape underwent land cover change processes with more than 26% of the entire landscape experiencing forest or land degradation. In the second period the extent of the change process was limited to only 1/3 of the total area with a smaller amount of degradation processes than before. During the entire study period, agriculture was responsible for the loss of more than 4/5 of the total terrestrial productive ecosystem. More than 37.6% of the total park area has been experiencing this loss for the past 3 decades. Only 1/5 of this area has a chance to revive, the remaining has undergone a permanent degradation. Lake Abijjata lost half of its size during the past 30 years. In the Zeway-Awassa basin 750 km², 2428km² and 3575km² of terrestrial lands and water bodies are within a distance of 10km, 20km and 30km from IBAs respectively. There are ecologically important areas where two or more IBAs overlap. In areas where more than two to five IBAs overlap, up to 85km² of areas have been recently degraded. High livestock density is one of the reasons for degradation. Using a monthly MODIS data from 2000-2005 and a series of interpolation techniques, the productivity of the area as well as the standing biomass were estimated. Moreover, a new method of spatially accurate livestock density assessment was developed in this study. Only 0.3% of the park area is found to be suitable for productive livestock development but nearly all inhabitants think the area is suitable. Feed availability in ASLNP is scarce even during rainy seasons. Especially the open woodlands are subject to overgrazing. Such shortage forces the inhabitants to cut trees for charcoal making to buy animal feed and non-food consumables. While more than 95% of the inhabitants in the park expanded their agriculture lands, only 13.3% of the farmers managed to produce cereals for market. The application of low cost remote sensing and GIS methods provided ample information that enables to conclude that low productivity and household food insecurity are the main driving forces behind land cover changes that are negatively affecting the natural and semi-natural ecosystems in the central and southern Rift Valley of Ethiopia. The restoration of natural ecosystems or conservation of biodiversity can be achieved only if those driving forces are tackled sustainably.