基于遙感影像對土壤水分反演的研究.pdf

1、西安科技大學(xué)碩士學(xué)位論文基于遙感影像對土壤水分反演的研究姓名：吳超申請學(xué)位級別：碩士專業(yè)：地圖學(xué)與地理信息系統(tǒng)指導(dǎo)教師：郭力宇2011Subject ：Soil Moisture Inversion based on Remote Sensing Image Specialty ：Cartography and Geographic Information System Name ：Wu Chao

2、 (Signature) Instructor ：Guo Liyu (Signature) ABSTRACT Soil moisture is an important index for monitoring land degradation, and is also a main parameter in climate,

3、hydrology, ecology, agriculture and other fields. It plays an important role in the exchange of water and energy in surface and atmosphere. At the same time, the condition of soil moisture can reflect the health status o

4、f ecological environment, which is also one sensitive indicative factor of natural disasters, such as drought and flood. Remote sensing is a method of retrieving soil moisture, which can not only overcome the shortcoming

5、s that are time-consuming, laborious, and point to an area in traditional monitoring, but also can achieve monitoring and evaluation fast, timely and dynamical. It is highly significant to monitor soil moisture by means

6、of remote sensing, which can provide information on large area quickly and easily. In this paper, we have collected related research materials which are using remote sensing retrieving soil moisture quantitatively at hom

7、e and abroad, remote sensing image data, DEM data and temperature data in the city of Baiyin in Gansu province. On the basis of above materials, taking the Baiyin city as research area, according to the geometric relatio

8、nship between the sun’s rays and terrain, using the DEM data and considering mountain influence of slope, aspect and shadings, we build an astronomical radiation distribution computing model under undulating terrain thro

9、ugh the geographic information system technology. Also, air temperature parameter is corrected by terrain factors, such as elevation, slope, aspect and terrain shadings, which reveals temperature diversity with terrain i

10、n detail. This model can accurately calculate mountain astronomical radiation spatial distribution. Combining with Landsat5 / TM6 remote sensing data and making use of mono-window algorithm, land surface temperature can

11、be obtained by retrieving. In line with land surface temperature, Temperature-Vegetation Dryness Index (TVDI) can be get further. By use of ENVI spatial modeling tool, we can retrieve a distribution map of TVDI, which ca