School of Computer Science and Technology, Remote Sensing and Climate Change, Qingdao University, Qingdao, 266071, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.
Environ Sci Pollut Res Int. 2019 Apr;26(11):11470-11481. doi: 10.1007/s11356-019-04512-8. Epub 2019 Feb 26.
Drought is the most complex climate-related disaster issue in South Asia, because of the various land-cover changes, vegetation dynamics, and climates. The aims of the current research work were to analyze the performance of AVHRR Normalized Difference Vegetation Index (NDVI) and spatiotemporal differences in vegetation dynamics on a seasonal basis by correlating the results with NASA's MERRA precipitation and air temperature for monitoring vegetation dynamics and drought over South Asia. Our approach is based on the use of AVHRR NDVI data and NASA's MERRA rainfall and air temperature data (1990-2011). Due to the low vegetation and dryness, the NDVI is more helpful in describing the drought condition in South Asia. There were rapid increases in NDVI, VHI, and VCI from April to October. Monthly NDVI, VHI, and VCI stabilize in September and improved once more in October and then show a declining trend in December. The monthly PCI, TCI, VHI, and VCI values showed that the South Asia goes through an extreme drought in 2000, which continues up to 2002, which lead the highest water stress. Spatial correlation maps among NDVI, precipitation, air temperature, VHI, and VCI on a seasonal basis. The correlation between NDVI and precipitation showed a significantly higher correlation value in JJA and SON seasons; the spatial correlation between NDVI and air temperature showed significant high values in DJF, JJA, and SON periods, while the correlation between VHI and TCI showed a significantly higher values in MAM and SON seasons, which indicated a good sign for dryness monitoring, mainly for farming regions during these seasons in South Asia. It was confirmed that these indexes are a comprehensive drought monitoring indicator and a step to monitoring the climate change in South Asia, which will play a relevant role ongoing studies on vegetation types, monitoring climate change, and drought over South Asia.
干旱是南亚最复杂的与气候有关的灾害问题,因为存在各种土地覆盖变化、植被动态和气候。本研究工作的目的是通过将结果与 NASA 的 MERRA 降水和气温相关联,分析基于 AVHRR 归一化差异植被指数 (NDVI) 的性能和基于季节的植被动态的时空差异,以监测南亚的植被动态和干旱。我们的方法基于使用 AVHRR NDVI 数据和 NASA 的 MERRA 降水和气温数据(1990-2011 年)。由于植被和干燥度低,NDVI 更有助于描述南亚的干旱状况。NDVI、VHI 和 VCI 从 4 月到 10 月迅速增加。9 月 NDVI、VHI 和 VCI 逐月稳定,并在 10 月再次提高,然后在 12 月呈下降趋势。每月 PCI、TCI、VHI 和 VCI 值表明,南亚在 2000 年经历了极端干旱,一直持续到 2002 年,导致了最高的水压力。基于季节的 NDVI、降水、气温、VHI 和 VCI 之间的空间相关图。NDVI 与降水之间的相关性在 JJA 和 SON 季节具有显著更高的相关值;NDVI 与气温之间的空间相关性在 DJF、JJA 和 SON 期间具有显著较高的值,而 VHI 与 TCI 之间的相关性在 MAM 和 SON 季节具有显著较高的值,这表明这些季节在南亚的干旱监测中是一个良好的迹象,主要适用于农业地区。这证实了这些指数是一个综合干旱监测指标,也是监测南亚气候变化的一个步骤,将在南亚的植被类型、监测气候变化和干旱的研究中发挥相关作用。