34 resultados para regional and rural

em CentAUR: Central Archive University of Reading - UK


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From the 1950s up to the early 1990s the All-India data show an ever-declining share of informal credit in the total outstanding debt of rural households. Contemporaneous micro-level studies, using more qualitative research methodologies, provide evidence that questions the strength of this trend, and more recent All-India credit surveys show, first, a levelling, and then a rise, in the share of rural informal credit in 1990/91 and 2000/01, respectively. By reference to findings of a study of village moneylenders in Rajasthan, the paper notes lessons to be drawn. First, informal financial agents have not disappeared from the rural financial landscape in India. Second, formal-sector financial institutions can learn much about rural financial service needs from the financial products and processes of their informal counterparts. Third, a national survey of informal agents, similar to that of the 1921 Census survey of indigenous bankers and moneylenders, would provide valuable pointers towards policy options for the sector. A recent Reserve Bank of India Report on Moneylender Legislation not only explores incentive mechanisms to better ensure fair practice, but also proposes provision for a new category of loan providers that would explicitly link the rural informal and formal financial sectors.

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The 2003 reform of the European Union's (EU) Common Agricultural Policy introduced a decoupled income support for farmers called the Single Farm Payment (SFP). Concerns were raised about possible future land use and production changes and their impact on rural communities. Here, such concerns are considered against the workings of the SFP in three EU Member States. Various quantitative studies that have determined the likely impact of the SFP within the EU and the study countries are reviewed. We present the results of a farm survey conducted in the study countries in which farmers' responses to a decoupling scenario similar to the SFP were sought. We found that little short-term change was proposed in the three, rather different, study countries with only 30% of the farmers stating that they would alter their mix of farm activities. Furthermore, less than 30% of all respondents in each country would idle any land under decoupling. Of those who would adopt a new activity, the most popular choices were forestry, woodland and non-food crops. (c) 2007 Elsevier Ltd. All rights reserved.

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Trees outside forests (TOF) in Nepal’s Terai have significantly increased over the past decade. The Chitwan District was one of the focus districts in the Terai Community Forestry Development Project that promoted a tree seedling distribution program. This paper examines the current position of tree integration on farmland and its contribution to livelihoods of rural households in this district. Interviews with local key informants, government and non-government agencies and woodbased industries, as well as an in-depth study of 32 households were used to describe the constraints faced by the households in management of trees on farmland. Most households cited disease, poor growth, lack of preferred tree species, lack of technical support, an uncertain tree market, and lack of financial support as constraints. Despite the important role of trees in subsistence and marketbased rural livelihood diversification, and the consequent reduction in pressure on national forests from on-farm trees, current government policies and practices fail to recognise the value of these trees. It is argued that there is substantial potential for improving on-farm trees to enhance rural livelihoods. A responsive service mechanism centred on tree growing households would help the management of tree resources on the farmland.

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A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover.

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A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy.

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A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18% respectively.