|
|
|
Poster Session
|
A study of Remote Sensing Information model of soil moisture
Ma Ai Nai Xue Young
Institute of Remote Sensing, Peking University
Peking 100871, P. R. China
Abstract
Soil moisture is an extremely important problem in monitoring of drought or water logging. Especially, soil moisture map is made with space remote sensing data automatically .In general, soil moisture will be expressed as thermal inertia. This paper discusses theoretical models of thermal inertia and soil moisture of remote sensing information model (RSIM).
Using NOAA satellite AVHRR digital tape data, the ATI and RTI will be made automatically from the thermal inherits model. Finally, using soil moisture model, the Apparent Soil Moisture (ASM) map of large region with no effects of topography and vegetative cover will be automatically finished by computer.
Analysis of soil moisture Remote Sensing Information
There is lots of paper about soil moisture measurement from VIS-Near IR, thermal IR to Microwave (1-4,6,7) (1972,1975,1986,1974,1976). Most scientists discovered that it not only has strong theoretical basis but also has practical values to apply the Remote Sensing Information model (5) (1990) of thermal inertia and soil moisture for timely large area monitoring.
Thermal inertia Remote Sensing Information model (4) (1986)
From above, we know that there are two steps for modeling remote sensing soil moisture. The first is the thermal inertia model and the second is soil moisture model.
- Thermal inerita remote sensing information model
Thermal inerita , P=(Kdc)½ (k is conductivity , d is density , and c is special heat capacity), is a physical variable precluding the variations of temperature of body. Thermal inerita is dorminant factor in week and day variations of temperature of soil. Thermal interia is the
characteristic of soil body. It can be obtained from week or day variation of temperature and albedo with thermal physical model .
From solution of thermal conduction equation with boundary condition expressed by Fourier series of day and night variation of temperature model, we can yield:
where A is albedo,Td-Tn is day and night difference of temperature, So is solar constant , Ct is the atmospheric transmissivity , A is the function of the solar declination and local latitude . w is the circular frequency of day and night , B is the constant of the ground state and atmosphere's and B may be constant under the condition of relative uniform meteorological condition and smooth terrain. In general,So,Ct,Solar declination and B is constant approximately for one digital image. Ai only have something with local latitude . So, ATI represents relative value of thermal inertia P, i.e., ATI direct proportion to P. ATI = (1-A)(Td-Tn) is apparent thermal inertia model.
- Soil moisture remote sensing information model
Theoretically, soil moisture have something to do with real thermal inertia P=(k d c )½ of ground . Then, we must evaluate real thermal inertia P. From formula (1), we have,
where a = 2 SoCtAi (ATI)
There are many factors to affect the soil thermal inertia. In addition to soil moisture, there are topography, vegetal cover, soil texture, organic matter and soild mineral matter , etc. The difference is the quantity of effective level. Topography and vegetal cover is relatively important. In order to elimate the effects of topography and vegetal cover, the plain region was chosen as the experiment ground and the time was in seeding stage. Soil texture, organic matter solid mineral matter etc. were approximately substituted in soil density.
It is well-known that, according to the definition of temperature conductivity a2 = k/d*c, p= k /(a2)½. The relation among k,d,c a2 and soil moisture has been investigated. But, there is no
theoretical formula. Most of them are experimental data (8) (1979). We substitute volume percentage of soil moisture for weight percentage of soil moisture, we have
where W is weight percentage of soil moisture , the density of water is d= 1(g/cm3) , ds is density of soil.
From formula (3), it is known that if ds is known, the relation between thermal inertia P and soil moisture W is one by one relation .
Then, a lookup table for RTI and W is built.
Formula (2) and (3) are soil moisture remote sensing information model, where ds is evaluated by false color composition or supervised classification and soil
property.
|
|
|
|
|
|
|
