微波植被光学厚度(Vegetation Optical Depth, VOD)能够定量表征地上植被总含水量,相比光学植被指数具有全天候观测、不易饱和等优势,是连接植被水分、结构与碳循环的重要遥感参数。本文在梳理微波辐射传输理论的基础上,综述了典型主、被动传感器VOD的反演框架及主要产品特征,并总结了VOD产品验证与评估的方法体系；进一步从模型病态反演、参数定标和数据输入等方面概括了当前VOD产品的主要不确定来源,归纳了VOD在植被水分监测、物候识别、地上碳储量估算及陆面模型约束中的应用与优势。在此基础上,围绕上述反演方法(产品研制)、产品验证评估和应用拓展三方面,讨论了现阶段存在的主要问题,并对各部分内容未来的发展方向进行了展望。

Microwave vegetation optical depth (VOD) quantitatively characterizes aboveground vegetation water content. Compared with optical vegetation indices, it provides all-weather observations and is less prone to saturation, making it a key remote-sensing variable linking vegetation water status, canopy structure and the terrestrial carbon cycle. Based on a review of microwave radiative transfer theory, this paper summarizes the retrieval frameworks and main product characteristics of representative active and passive VOD products, and reviews current approaches for VOD validation and evaluation. We further synthesize the major sources of uncertainty in existing VOD products from the perspectives of ill-posed inversion, parameter calibration and ancillary data/forcing inputs, and summarize the strengths of VOD in applications to vegetation water monitoring, phenology detection, aboveground carbon stock estimation and land surface model constraints. Building on this overview, we discuss the main challenges now facing VOD retrieval (product development), product validation and application expansion, and outline future research directions for each of these three aspects.