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Remote Sensing and GIS Based Agricultural Drought Risk Assessment in East Shewa Zone, Central Rift Valley Region of Ethiopia

机译:埃塞俄比亚中部裂谷地区东谢瓦地区基于遥感和GIS的农业干旱风险评估

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Drought is one of the most complex naturally occurring disasters that results in serious human life, environmental, social and economic costs around the world. In order to monitor agricultural drought risk, GIS and remote sensing have a significant role. This research was conducted in East Shewa Zone of Oromia Region of Ethiopia with the objective of mapping agricultural drought risk using GIS and remote sensing. Ten years decadal SPOT NDVI datasets were downloaded from VITO website. In order to compute the Standardized Precipitation Index (SPI), rainfall data was obtained from meteorological stations of the study area. The result of drought severity index indicated that 2005 and 2009 were years of drought while 2013 identified as wet year. On the other hand based the result of SPI, 2005 and 2009 were years of droughts while 2012 wet year. The result also showed that there is good correlation (r = 0.7) between long term NDVI and seasonal rainfalls. The results were supported by the interviews and focus group discussions. Based on the result drought risk map, 5.1% of the zone are under extreme drought risk, 31.9% severe drought, 27.1% moderate drought and 32.5% are under mild drought. Thus, it is only the remaining 3% of the East Shewa Zone that are not vulnerable to drought. Our findings showed that we can use GIS and remote sensing for drought assessment in regions where there are scarce ground observation data. Future research may focus on camparson of ground observation data and sattellite derived data.
机译:干旱是最复杂的自然灾害之一,导致世界范围内严重的人类生命,环境,社会和经济损失。为了监视农业干旱风险,GIS和遥感具有重要作用。这项研究是在埃塞俄比亚奥罗米亚地区东谢瓦地区进行的,目的是使用GIS和遥感技术绘制农业干旱风险图。从VITO网站下载了十年的SPOT NDVI数据集。为了计算标准化降水指数(SPI),从研究区域的气象站获得了降雨数据。干旱严重程度指数的结果表明,2005年和2009年是干旱年份,而2013年被确定为湿润年份。另一方面,根据SPI的结果,2005年和2009年是干旱年份,而2012年是干旱年份。结果还表明,长期NDVI与季节性降雨之间存在良好的相关性(r = 0.7)。访谈和焦点小组讨论支持了结果。根据结果​​干旱风险图,该地区的5.1%处于极端干旱风险中,31.9%处于严重干旱中,27.1%处于中度干旱,32.5%处于轻度干旱。因此,只有东部谢瓦地区剩余的3%不受干旱影响。我们的发现表明,我们可以将GIS和遥感技术用于缺乏地面观测数据的地区进行干旱评估。未来的研究可能集中在地面观测数据和卫星衍生数据的反演。

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