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Characterization of drought monitoring events through MODIS- and TRMM-based DSI and TVDI over South Asia during 2001–2017

机译:2001-2017期间,通过基于修改和TRMM的DSI和TVDI在南亚的干旱监测事件的特征

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South Asia is susceptible to drought due to high variation in monthly precipitation. The drought indices deriving from remote sensing data have been used to monitor drought events. To secure agricultural land in South Asia, timely and effective drought monitoring is very important. In this study, TRMM data was utilized along with remote sensing techniques for reliable drought monitoring. The Drought Severity Index (DSI), Temperature Vegetation Drought Index (TVDI), NDVI, and Normalized Vegetation Supply Water Index (NVSWI) are more helpful in describing the drought events in South Asia due to the dryness and low vegetation. To categorize drought-affected areas, the spatial maps of TRMM were used to confirm MODIS-derived TVDI, DSI, and NVSWI. The DSI, TVDI, NVSWI, and Normalized Monthly Precipitation Anomaly Percentage (NAP) indices with an integrated use of MODIS-derived ET/PET and NDVI were selected as a tool for monitoring drought in South Asia. The seasonal DSI, TVDI, NVSWI, NAP, and NDVI values confirmed that South Asia suffered an extreme drought in 2001, which continued up to 2003. The correlation was generated among DSI, NAP, NVWSI, NDVI, TVDI, and TCI on a seasonal basis. The significantly positive correlation values of DSI, TVDI, and NVSWI were in DJF, MAM, and SON seasons, which were described as good drought monitoring indices during these seasons. During summer, the distribution values of drought indicated that more droughts occurred in the southwest regions as compared to the northeast region of South Asia. From 2001 to 2017, the change trend of drought was characterized; the difference of drought trend was obviously indicated among different regions. In South Asia, generally, the frequency of drought showed declining trends from 2001 to 2017. It was verified that these drought indices are a comprehensive drought monitoring indicator and would reduce drought risk in South Asia.
机译:由于每月降水量高,南亚易受干旱的影响。从遥感数据中导出的干旱指数已被用于监控干旱事件。为了确保南亚农业用地,及时,有效的干旱监测非常重要。在该研究中,利用TRMM数据以及遥感技术进行可靠的干旱监测。干旱严重程度指数(DSI),温度植被干旱指数(TVDI),NDVI和标准化植被供应水指数(NVSWI)更有助于由于干燥和低植被描述南亚的干旱事件。要对受干旱影响的区域进行分类,TRMM的空间地图用于确认Modis派生的TVDI,DSI和NVSWI。 DSI,TVDI,NVSWI和标准化每月降水异常百分比(NAP)指数具有综合使用MODIS-errived等/宠物和NDVI作为监测南亚干旱的工具。季节性DSI,TVDI,NVSWI,NAP和NDVI值证实,南亚于2001年遭遇了极端的干旱,该趋势持续了2003年。在季节性的DSI,NAP,NVWSI,NDVI,TVDI和TCI之间产生了相关性的相关性基础。 DSI,TVDI和NVSWI的显着正相关价值在DJF,MAM和儿子季节中,在这些季节中被描述为良好的干旱监测指数。夏季,干旱的分布价值表明,与南亚东北地区相比,西南地区发生了更多的干旱。从2001年到2017年,流动的变化趋势是特征;不同地区的干旱趋势的差异显然表明。一般而言,在南亚,干旱的频率从2001年到2017年的趋势表现出下降的趋势。核实这些干旱指标是一项综合性干旱监测指标,并会降低南亚的干旱风险。

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