Zhang Jia-Hua, Li Li, Yao Feng-Mei
Laboratory for Remote Sensing and Climate Information Sciences, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2010 Jun;30(6):1638-42.
The present paper reviews the progress in the methods of retrieving vegetation water content using remote sensing spectral information, including vegetation spectral reflectance information (VIR, SWIR, and NIR) to directly extract vegetation water content and establish vegetation water indices (WI), i. e. NDWI = (R860 - R1 240)/(R860 + R1 240) and PWI = R970/R900; and using radiation transfer (RT) model such as PROSPAIL to detect plant water content information. The authors analyze the method of retrieving vegetation water content under low crop coverage condition. The plant water can be estimated by using canopy physiological parameters firstly, and using vegetation indices and radiation transfer model secondly, which can eliminate soil background effect. The estimated agricultural drought and vegetation water content by using multi-angle polarized reflectance and bi-directional reflectance (BRDF) was discussed in this paper. In the end, the possible development trend of retrieval methods for plant water information under plant low coverage conditions was discussed.
本文综述了利用遥感光谱信息反演植被含水量方法的进展，包括利用植被光谱反射率信息（可见光、短波红外和近红外）直接提取植被含水量并建立植被水分指数（WI），即归一化差异水分指数NDWI = (R860 - R1240)/(R860 + R1240) 和比值植被水分指数PWI = R970/R900；以及利用辐射传输（RT）模型如PROSPAIL来检测植物含水量信息。作者分析了低作物覆盖条件下反演植被含水量的方法。首先可以利用冠层生理参数估算植物水分，其次利用植被指数和辐射传输模型，这样可以消除土壤背景效应。本文还讨论了利用多角度偏振反射和双向反射分布函数（BRDF）估算农业干旱和植被含水量的情况。最后，探讨了低植被覆盖条件下植物水分信息反演方法可能的发展趋势。
