辐射传输模型多尺度反演植被理化参数研究进展

植被是生态系统最重要的组成成分之一,许多与植被有关的物质能量交换过程都与植被的理化参数密切相关,因此定量估算植被的理化参数含量对监测植被生长状况、森林火灾预警以及研究全球碳氮循环过程等都具有重要意义.在众多定量反演植被理化参数的方法中,基于数学、物理学以及生物学的基本理论建立起来的辐射传输模型受到越来越多的关注.辐射传输模型描述了植被与入射辐射之间的相互作用过程和特征,相对于传统的经验/半经验方法,辐射传输模型物理意义明确,具有稳定性和可移植性强的特点.在分析国内外最新相关研究的基础上,首先从植被叶片、冠层和像元3个不同的尺度阐述反演植被理化参数的辐射传输模型.叶片尺度上主要介绍PROSPECT模型和LIBERTY模型；冠层尺度上主要介绍SAIL冠层辐射传输模型以及PROSPECT与SAIL耦合的PROSAIL叶片-冠层辐射传输模型；像元尺度的植被理化参数反演目前主要采用冠层尺度的辐射传输模型.其次,分析尺度变化下植被理化参数遥感反演所面临的主要问题,如不同尺度下模型参数敏感性的变化、辐射传输模型的选取以及混合像元的影响等.最后,总结展望植被理化参数反演多模型与多种数据源相互结合的研究趋势,以及将来具有高空间分辨率的高光谱遥感卫星升空后所带来的发展前景.

Review of inversing biophysical and biochemical vegetation parameters in various spatial scales using radiative transfer models

Vegetation is one of the most important components of the earth ecosystem, and its biophysical and biochemical parameters are closely correlated to many exchanges of energy and matter in natural environments. So estimation of the key biophysical and biochemical variables accurately is critical for many ecological, agronomic, and meteorological applications, such as monitoring the growth condition of vegetation, warning the forest fire and studying the global carbon-nitrogen cycle. Empirical-statistical approach and physically based canopy reflectance model are the two main methods to estimate vegetation characteristics. Since the vegetation reflectance is impacted by several internal and external factors, which are different both spatially and temporally according to the different vegetation types. There is a critical issue on the empirical-statistical approach due to its lacking of generality. And the empirical-statistical approach will be site-, time-and crop-specific because of the existed relationship of reflectance and its established biochemical and biophysical parameters. The vegetation radiative transfer models, as the most important physically based model, are established on fundamental theories of mathematics, physics and biology, and they describe the transfer and interaction of radiation inside the canopy based on physical laws. Many researchers have proved the radiative transfer models as an important tool to understand and quantify the relationship between vegetation object properties and remotely detected radiance signals, with their strong stability and good spatiotemporal transferability by comparing with the empirical-statistical approach. On the basis of different vegetation types and research objectives, a variety of radiative transfer models have been developed for different research purpose in the past two decades, and there are many reports on the application of these models. In this review, we focused on introducing the vegetation radiative transfer models used to estimate biophysical and biochemical parameters at different spatial scales, and we discussed the key issues with these models for estimating vegetation variables as the viewpoint of the changed scale. Firstly we overviewed vegetation radiavitive transfer models at three scales of leaf, canopy and pixel. At leaf scale, we primarily introduced the foundation and application of PROSPECT model and LIBERTY model. At canopy scale, the special emphasis is on the SAIL model and the coupled PROSAIL model. At pixel scale, the frequently-used radiative transfer models continue to be the models established at canopy scale, though some researchers have retrieved the biophysical and biochemical parameters at regional or global scale using a number of optical remote sensing sensors. Secondly, we discussed the critical issue of estimating the biophysical and biochemical parameters with remote sensing technique dealing as the scale changed. With the different spatial scales the sensitivity of vegetation reflectance to biochemical and biophysical variables can be changed, and it remains a key issue if dealing with how to choose a more proper model to the specific scale. The mixed pixel would be very critical to the retrieval accuracy when we use remote sensing images with medium and low resolution to estimate the biochemical and biophysical parameters. Finally, we discussed the possible future approaches to estimate the biochemical and biophysical parameters using radiative transfer models, both in terms of burning issues and development prospect.