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

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 ob...

Full description

Bibliographic Details
Main Authors: Somayeh Talebiesfandarani, Tianjie Zhao, Jiancheng Shi, Paolo Ferrazzoli, Jean-Pierre Wigneron, Mehdi Zamani, Peejush Pani
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/11/6/730
Description
Summary: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 (<inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mrow> <mi>MVI</mi> </mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">P</mi> </msubsup> </mrow> </semantics> </math> </inline-formula>) and (ii) time invariant (<inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mrow> <mi>MVI</mi> </mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">T</mi> </msubsup> </mrow> </semantics> </math> </inline-formula>), based on model simulations at the L band. Results show that the <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mrow> <mi>MVI</mi> </mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">T</mi> </msubsup> </mrow> </semantics> </math> </inline-formula> has a stronger sensitivity to vegetation properties compared with <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mrow> <mi>MVI</mi> </mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">P</mi> </msubsup> </mrow> </semantics> </math> </inline-formula>. <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mrow> <mi>MVI</mi> </mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">T</mi> </msubsup> </mrow> </semantics> </math> </inline-formula> is used to retrieve VOD and VWC, and the results were compared to physical VOD and measured VWC. Comparisons indicated that <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mrow> <mi>MVI</mi> </mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">T</mi> </msubsup> </mrow> </semantics> </math> </inline-formula> 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.
ISSN:2072-4292