A synoptic land change assessment of Ethiopia's Rainfed Agricultural Area for evidence-based agricultural ecosystem management.

This paper demonstrates synoptic ways of presenting and characterizing land change processes across Ethiopia's large, complex Rainfed Agricultural Area (RAA). We translated pixel-level detected changes into neighbourhood-level changes that are useful to decision-makers. First, we identified pixel-level changes without and with type/direction of change, based on land cover maps from the years 1986 and 2010. For type-/direction-based characterization, we sorted observed transitions into four categories of prominent land change processes ("forest degradation", "deforestation", "afforestation", and "no change"). Adopting appropriate window sizes for identified ecoregions in the study area, we ran a focal statistics summation operator separately on the two change rasters (with/without consideration of direction of change). The results obtained by applying the approach can be described in relative terms as well as qualitative terms, using ranges of change values that can be further classified using qualitative terms, i.e. ranging from "no change" to "high/substantial change". Our non-directional change assessment result showed that approximately 6% of the RAA is characterized by substantial change, whereas 40% appears stable ("no change"). Based on the directional-change assessment results, 3% of deforestation, 4% of forest degradation, and 3% of revegetation processes were found to constitute "high/substantial change". The types and intensity of landscape transformations display distinct spatial patterns linked to agro-ecological belts and socio-economic dynamics. Minimal reverse changes were observed on some severely degraded lands in the highlands, but the overall per cent cover remains relatively small. Overall, vegetation degradation still exceeds regeneration by more than half a per cent. Relatively lower altitudes and middle altitudes exhibit higher transformation. The presented approach and resulting outputs can provide planners and decision-makers with a synoptic view of land change processes. It can support policy formulation of sustainable land management and rehabilitation activities of the agricultural ecosystem at national and regional scales.