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Drought Mapping Using Two Shortwave Infrared Water Indices with MODIS Data under Vegetated Season

S. H. Zhao1, Q. Wang1, F. Zhang1*, Y. J. Yao2, Q. M. Qin3, L. You4, J. P. Li5, Z. J. Li6, Y. T. Wu1, S. H. Liu1 and Y. Li1

  1. Satellite Environment Center, Ministry of Environmental Protection, State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing 100094, China
  2. College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
  3. Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China
  4. Ningbo Planning and Geography Information Center, Ningbo 315042, China
  5. Ningxia Provincial Institute of Meteorology, Yinchuan 750002, China
  6. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China

*Corresponding author. Tel: +86-10-58311595 Fax: +86-10-58311501 Email:


Drought monitoring is a critical element for agricultural production, food security, water resource management, sustainable development, and a healthy environment. In this study, shortwave infrared (SWIR) bands with strong water absorption features were used to establish a physically significant water stress index. Two types of indices including SWIR water stress index (SIWSI) and SWIR perpendicular water stress index (SPSI) were constructed using near-infrared (NIR) and SWIR bands. A representative (semi) arid region in the Ningxia Plain of northwestern China, where droughts are frequent, was used to assess the state of dryness using the SIWSI and SPSI indices derived from NIR channel 2 (858 nm) and SWIR channel 6 (1640 nm) or channel 7 (2130 nm) of moderate-resolution imaging spectroradiometer (MODIS) sensor in combination with ground measurements. Fitted regressions indicate significant correlations (P < 0.01) among both indices with the in-situ measurements. Generally, larger indices indicate drier lands, and correlations in the 10-cm range were better than those in the 20-cm range. Although SIWSI6, 2 (r^2 = 0.75, 0.74) performs slightly better than SIWSI7, 2 (r^2 = 0.73, 0.71), SPSI6, 2 (r^2 = 0.70, 0.69) performs marginally weaker than SPSI7, 2 (r^2 = 0.76, 0.74). Ultimately, all four indices reflected dry state under clear sky conditions in the Ningxia Plain.

Keywords: SWIR, NIR, SIWSI, SPSI, Ningxia Plain

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