An automated method for mapping physical soil and water conservation structures on cultivated land using GIS and remote sensing techniques

An efficient and reliable automated model that can map physical Soil and Water Conservation（SWC） structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and Arc GIS？ERDAS IMAGINE？and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures：（1） a high-pass spatial filter algorithm was applied to detect linear features,（2） morphological processing was used to remove unwanted linear features,（3） the raster format was vectorized,（4） the vectorized linear features were split per hectare（ha） and each line was then classified according to its compass directionand（5） the sum of all vector lengths per class of direction per ha was calculated. Finallythe direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Thereforethe model is useful for predicting and mapping physical SWC structures areas across diverse areas.

Factors influencing the adoption of physical soil and water conservation practices in the Ethiopian highlands

Soil and Water Conservation (SWC) structures have been constructed on cultivated land for nearly 40 years to reduce soil loss and improve crop yields and people's livelihoods in the Ethiopian highlands. However, the success of this huge effort has been mixed, and the main constraints have not been investigated in detail. This study was undertaken to identify the factors determining the adoption of SWC structures in the Ethiopian Highlands. Case study areas were selected from high-potential and low-potential areas. Data were collected from 269 farmers using face-to-face interviews, and through focus group discussions, key informant interviews and field observations. Binary logistic regression model and descriptive statistics were used to analyze the data. The result showed that the majority (87%) of the farmers interviewed were using SWC structures. Regionally, nearly all farmers in the low-potential areas and 56% of farmers in the high-potential areas constructed and were maintaining the structures properly. This disparity is due to the fact that in the low-potential areas there have been strong governmental involvement and technical and financial support, and hence the farmers there have a better understanding of the multiple uses of physical SWC structures than do farmers in the high-potential areas. In addition, off-farm activities and free grazing plays a substantial role. We can conclude that clear understanding of the benefits of SWC structures by farmers, active involvement and technical support from the government, and genuine participation of farmers in SWC practices were found to be main factors in the adoption of SWC measures.

Remote sensing of land use/cover changes in South and Southeast Asian Countries

Land-Use/Cover Changes(LU/CC)are occurring rapidly in South/Southeast Asian(S/SEA)countries,generally associated with population growth,economic development and competing demands for land.In the region,the most common LU/CC changes include urban expansion,agricultural land loss,land abandonment,deforestation,logging,reforestation,agricultural expansion,etc.Specific to South Asia,forest cover has been increasing in countries like India,Nepal,and Bhutan due to sustainable afforestation measures;whereas,large-scale deforestation in Southeast Asian countries is continuing,for example,due to oil palm plantation expansion driven by the international market demand in Malaysia and Indonesia.Small-scale deforestation in most of the Southeast Asian countries is due to slash-and-burn agriculture by indigenous people,driven by poverty and population growth.Logging activities are common in Myanmar and Cambodia.In terms of urbanization,South and Southeast Asian countries contain 23 megacities,each with more than 10 million people.Megacities in these countries started as urban clusters which grow rapidly,merging into conurbations.Rapid urbanization is driving agricultural land loss,and agricultural intensification has been increasing due to less availability of land for growing food crops as,for example,in India,Vietnam,and Thailand.The drivers of LU/CC vary widely in the region and include such factors as land tenure,local economic development,government policies,inappropriate land management,land speculation,improved road networks,etc.Also,variability in the weather,climate,and socioeconomic factors drive LU/CC resulting in disruptions of biogeochemical cycles,radiation and surface energy balance.