Integration Study To Retrieve Vegetation Biomass And Soil Moisture Simultaneously Using Active And Passive Remote Sensing Data In Ecologically Vulnerable Area

The ecological environment condition characterized by growth status of the vegetation is restricted by soil moisture in ecologically vulnerable area. Vegetation biomass, which reflects the ability of the earth ecological system to obtain energy, is vitally important to the earth ecosystem structure and function, and is one of the key components of the ecosystems. Soil moisture is an important land surface parameter playing a crucial role on the global water cycle, energy balance and climate variation. The principal determinant of ecological processes in ecologically vulnerable area is water. There is the positive feedback effect between the vegetation biomass and water. Therefore, it is very important to develop an objective, dynamic, and timely method for monitoring the vegetation biomass and soil moisture.The purpose of this study was to develop a synergistic method for applying optical and microwave remote sensing data to retrieve the vegetation biomass and soil moisture in ecologically vulnerable area(Wutumeiren prairie and Ruoergai prairie) based on the space-borne SAR data and field measurements. The bare soil scattering theories and vegetation scattering models were used in this process. The major accomplishments of this dissertation are summarized as following:(1) The herbaceous vegetation scattering model was developed by eliminating the scattering component associated with ground-trunk scattering in the forest scattering model. Because of the strong influence from the underlying ground surface caused by the heterogeneous distribution of vegetation and sparse vegetation cover, the vegetation gap information was accounted for in the herbs vegetation scattering model. The scattering mechanism for the vegetation cover component and bare soil component in a pixel were separated by vegetation coverage. The strong effect from bare soil patches was minimized. Finally, the developed herbs vegetation scattering model was applied to retrieve the vegetation biomass information in ecologically vulnerable area.(2) Based on the different phenologies between shrubs and herbaceous vegetation, the total backscattering in a pixel was divided into the contributions from the surface covered by herbaceous vegetation, shrub and the fraction representing direct backscattering from bare soil surfaces using phenological subtraction methodology. In order to use the model from areas with density vegetation cover to relatively sparse cover, the percentage covers of the different vegetation types were combined in the Water Cloud Model(WCM) to separate the scattering mechanism for the different vegetation type. The vegetation biomass was retrieved using the active/passive remote sensing data in the mixed vegetation area based on the developed mixed vegetation scattering model. The accuracy of vegetation biomass retrieval was significantly improved in ecologically vulnerable area.(3) An active/passive synergistic model to retrieve the soil moisture from the vegetated surface was developed. The Integral Equation Method(IEM) was used to simulate the scattering from a bare soil surface, and the WCM was used to calculate the volume scattering and the two-way attenuation of microwave signal from the vegetation. In this method, the IEM model was used to replace the backscattering of soil in the WCM. This replacement allows for a more realistic soil contribution in the total backscattering. In addition, the synergistic model included usage of the vegetation cover fractions derived from optical remote sensing data for the vegetation gap information. The canopy descriptors were associated with LAI. The model can be used to simulate the vegetation backscattering at large scales. To retrieve the soil moisture using the IEM in a vegetated area, the vegetation contribution to the total backscattering was removed with the use of the WCM. Then, the developed method was applied to estimate soil moisture in a vegetated area.(4) The variable scattering mechanisms from different vegetation components was performed by applying the Envisat ASAR, Radarsat-2 SAR and TerraSAR-X data. In this paper, the vegetation cover was divided into two types, herbaceous vegetation area and mixed vegetation(including shrub and herbaceous vegetation) area. The variable effects from vegetation coverage, vegetation types and vegetation biomass on SAR backscattering coefficient was performed by using the developed the vegetation scattering model. Moreover, the effects of topography on backscattering and soil moisture retrieval were analyzed.