The Soil Moisture Detection For Different Vegetation Coverage Based On The MODIS Data And The Influence Analysis Of The Thermal Radiant Directionality

Soil moisture is not only one of the most important environmental factors, which is closely related to the agriculture, meteorology, ecology, and hydrology, but also an important indicator in soil degradation monitoring and environment detection. Remote sensing is an great support for the large-scale surface information deriving, so it's significant to monitor the soil moisture with the method of remote sensing.Thermal inertia is the main method to detect the soil moisture by thermal infrared remote sensing. A lot of work had been done in the thermal inertia model, however, most of them were focused on the bare land or the low vegetation coverage areas. In the Huabei plain of China, the drought detection in spring is through the crop growth period, during which the vegetation coverage increases. In the other hand, thermal infrared sensor observes in the different view zenith angle. So it's significance to study the thermal inertia method for the moisture retrieval, with the consideration of the vegetation coverage and the thermal radiant directionality. The main contests of this thesis are as follows:(1) The paper discusses the thermal inertia model for soil moisture detection from two aspects, there are different vegetation coverage and the thermal radiant directionality. The synchronization surveys have been done in corn field in Huailai experiment station in 2005 and 2006 for the study, including the soil moisture survey and the thermal radiance data measured by thermal camera. And related parameters in the model are retrieved by the synchronous MODIS data.(2) According to the character of the survey area, apparent thermal inertia model is adopted in the paper. Analyses have been done: (I) Good correlation between apparent thermal inertia and the soil moisture can not be established without taking the vegetation into account. Different vegetation coverage has different impact on the correlation analysis. (II) Considering the vegetation coverage, NDVI is add to do the binary correlation analysis. A new parameter, which is the product of NDVI and...