植被土壤水分状态的微小变化能引起短波红外光谱反射率的巨大变化。利用MODIS第6波段和第7波段构建短波红外光谱特征空间,依据不同土地利用类型分析不同地物在光谱特征空间中的分布规律,提出MODIS短波红外水分胁迫指数MSIWSI。利用实测20 cm土壤相对湿度验证MSIWSI、EVI以及MPDI与实测数据相关性关系并对比分析不同指数敏感性,利用不同物候期春小麦土壤墒情分析MSIWSI指数适用性。研究结果表明: 与其他指数相比,MSIWSI模型与实测土壤湿度的相关性更高; MSIWSI能够反映不同物候期春小麦土壤水分变化趋势,相关性都达到极显著性水平。

Drought is a natural hazard that arises from climate fluctuations and variations.It frequently triggers negative impacts on economies, societies, and environments.This paper presents a new remote sensing-based drought index called the MODIS Shortwave Infrared Water Stress Index (MSIWSI) for monitoring agricultural drought. Changes in the water content of plant tissues or soil have a large effect on the reflectance in several regions of the shortwave infrared spectrum. MSIWSI integrates relevant information from the shortwave infrared channels 6 and 7 from the MODIS satellite data based on the distribution of different land cover classes in the MODIS shortwave infrared spectral feature space. Correlation and regression analyses are performed on MSIWSI and two other well-known drought indexes—the Enhanced Vegetation Index (EVI) and Modified Perpendicular Drought Index (MPDI)—and on ground-measured soil moisture data to assess the capability of MSIWSI in arid regions in northwest China. Pearson correlation analyses were also performed on MSIWSI and ground-measured soil moisture data of spring wheat during different phonological phases. Results show that MSIWSI performed better than EVI and MPDI in soil moisture retrieval. MSIWSI can also reflect the probable soil moisture trends of spring wheat. This investigation indicates that MSIWSI has significant application potential in monitoring agricultural drought in arid regions.