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(cest2017_00658) Drought risk assessment using GIS and remote sensing: A case study of District Khushab, Pakistan

机译:(CEST2017_00658)使用GIS和遥感的干旱风险评估:巴基斯坦小区Khushab的案例研究

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Drought is the most complex but least understood of all natural hazards. It is broadly defined as “sever water shortage”. In recent years, Geographic Information System (GIS) and Remote Sensing (RS) have played a key role in studying different types if hazards either natural or man-made. This study stresses upon the use of RS and GIS in the field of Drought Risk assessment. In this study an effort has been made to derive spatial-temporal drought risk areas facing agriculture as well as meteorological drought by use of temporal images from Landsat ETM based Normalize Difference Vegetation Index (NDVI) (2003, 2009 and 2015) and meteorological based Standardized Precipitation Index (SPI). Correlation analysis was performed between NDVI, SPI, and rainfall anomaly. SPI values were interpolated to get the spatial pattern of meteorological based drought. NDVI threshold was identified to get the agriculture drought risk. Similarly rainfall and NDVI were correlated and a spatial temporal drought risk maps were generated. Study area District Khushab was divided into three zones including no drought, slight drought and moderate drought. The results revealed that 41.43% are under no drought, 28.36% area under slight drought and 30.21% is the area under moderate drought. It was evident from the study that southern part of District Khushab was a rainfall deficit area with scarce vegetation and hence was the area with the highest drought prevalence. The results obtained can be helpful for drought management plans and will help in revealing true drought situation in the area.
机译:干旱是所有自然危害最复杂但最不理解的。它被广泛地定义为“缺水短缺”。近年来,如果天然或人为危害,地理信息系统(GIS)和遥感(RS)在研究不同类型时发挥了关键作用。这项研究强调在干旱风险评估领域使用RS和GIS。在这项研究中,已经努力通过使用来自Landsat ETM的标准化差异植被指数(NDVI)和基于气象的标准化的标准化,通过使用来自Landsat ETM的正常化差异差异差异差异的空间滴水以及气象干旱降水指数(SPI)。在NDVI,SPI和降雨异常之间进行相关分析。插值SPI值以获得气象流动的空间模式。确定了NDVI阈值以获得农业干旱风险。同样降雨和NDVI是相关的,并且产生了空间颞下干旱风险地图。学习区区卡墅分为三区,包括无干旱,轻微干旱和温和的干旱。结果表明,41.43%在没有干旱下,28.36%的面积在轻微干旱下,30.21%是温和干旱的面积。从研究中明显看出,Khushab区南部是一个缺乏植被的降雨赤字区域,因此是干旱盛行最高的地区。获得的结果可能有助于干旱管理计划,并有助于揭示该地区的真正干旱情况。

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