首都师范大学 三维信息获取与应用教育部重点实验室,首都师范大学 三维信息获取与应用教育部重点实验室,首都师范大学 三维信息获取与应用教育部重点实验室,首都师范大学 三维信息获取与应用教育部重点实验室
Key Lab of Three Dimension Information Acquisition and Application,Capital Normal University,Key Lab of Three Dimension Information Acquisition and Application,Capital Normal University,Key Lab of Three Dimension Information Acquisition and Application,Capital Normal University,Key Lab of Three Dimension Information Acquisition and Application,Capital Normal University
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.