Microwave Vegetation Index from Multi-Angular Observations and Its Application in Vegetation Properties Retrieval: Theoretical Modelling

Remote Sensing

Paolo Ferrazzoli¹  Jean-Pierre Wigneron²  Tianjie Zhao³  Jiancheng Shi³  Somayeh Talebiesfandarani⁴  Mehdi Zamani⁴  Peejush Pani⁴ 

[1] Department of Civil Engineering and Computer Science Engineering, Tor Vergata University of Rome, Via del Politecnico 1, I-00133 Rome, Italy;INRA, Centre INRA Bordeaux Aquitaine, URM1391 ISPA, F-33140 Villenave d’Ornon, France;State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100049, China;

关键词: microwave vegetation index;    Tor Vergata model;    vegetation optical depth;    vegetation water content;   

DOI  :  10.3390/rs11060730

来源: DOAJ

【 摘 要 】

Monitoring global vegetation dynamics is of great importance for many environmental applications. The vegetation optical depth (VOD), derived from passive microwave observation, is sensitive to the water content in all aboveground vegetation and could serve as complementary information to optical observations for global vegetation monitoring. The microwave vegetation index (MVI), which is originally derived from the zero-order model, is a potential approach to derive VOD and vegetation water content (VWC), however, it has limited application at dense vegetation in the global scale. In this study, we preferred to use a more complex vegetation model, the Tor Vergata model, which takes into account multi-scattering effects inside the vegetation and between the vegetation and soil layer. Validation with ground-based measurements proved this model is an efficient tool to describe the microwave emissions of corn and wheat. The MVI has been derived through two methods: (i) polarization independent ( ${\mathrm{MVI}}_{\mathrm{B}}^{\mathrm{P}}$ ) and (ii) time invariant ( ${\mathrm{MVI}}_{\mathrm{B}}^{\mathrm{T}}$ ), based on model simulations at the L band. Results show that the ${\mathrm{MVI}}_{\mathrm{B}}^{\mathrm{T}}$ has a stronger sensitivity to vegetation properties compared with ${\mathrm{MVI}}_{\mathrm{B}}^{\mathrm{P}}$ . ${\mathrm{MVI}}_{\mathrm{B}}^{\mathrm{T}}$ is used to retrieve VOD and VWC, and the results were compared to physical VOD and measured VWC. Comparisons indicated that ${\mathrm{MVI}}_{\mathrm{B}}^{\mathrm{T}}$ has a great potential to retrieve VOD and VWC. By using L band time-series information, the performance of MVIs could be enhanced and its application in a global scale could be improved while paying attention to vegetation structure and saturation effects.

【 授权许可】

Unknown