The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
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and meteorological observations are prior knowledge for renew 
SI model. 
Fire points are identified according to its temperature that is 
much higher than the background. Generally, the temperature of 
forest fire is around 600K. However, some points do not reveal 
such a higher temperature in remote sensing than that of in the 
reality because of the spatial resolution of the image. So we 
divided forest fire points into two types, which were higher 
temperature forest fire points and non-high temperature forest 
fire points. They were treated in different ways with different 
channels of MODIS. 
2. LST RETRIEVALTITLE 
Land surface temperature (LST) retrieval, which is one of the 
important parameter in environment remote sensing, is also a 
most difficult one in the field of remote sensing. Many scholars 
worked on this subject and achieved many researches results, 
such as thermal radiative transfer equation method, mono 
window algorithm, split-window algorithm, and multi-channels 
algorithm. (Price J C, 1984; Becker F, 1987; Cooper D I, 1989; 
Becker F, 1990; Sobrino J A, 1991; Prata A J, 1993; Wan Z, 
1997; Li Zhaoliang, 1999; Shunlin Liang, 2001; Ma X-L, 2000) 
Generally, these models are divided into two categories, 
physical models and statistical models. Our experiments in 
Chongqing show that the physical model has a better 
performance. Ma’s physical model is used in our experiments 
duo to its good LST retrieval performance (Ma X-L, 2000). It is 
an integrated inversion algorithm with land surface and 
atmosphere parameters retrieved together. 
For a cloud-free atmosphere under local thermodynamic 
equilibrium the RTE (Radiative Transfer Equation) in the 
thermal infrared region may be expressed as below. (Ma X-L, 
2000) 
r (Yj > M) = B{Vj,t s )£(yj,iu)T{Vj,ii,p s ) + R a (Vj, p) 
1 2 
(2-1) 
+ t (v■, p, -p G , 0)E 0 (v )f r (//; -p ', <j> ’) 
In this formula, ^ V J’^ j s the mean spectral radiance 
V 
measured in a band whose mean effective wave number is J 
and the cosine of local zenith angle ^ is ^ j»t s ) 
the Planck function of the surface skin temperature 
t e(v ,p) . 
s , 1 is the effective surface emissivity, and 
t(v p p ) 
J ’ ’ s/ is the transmittance from the surface pressure 
level ^ s to the top of the atmosphere along the observation 
angle @. The first term of Eq. (1) represents surface emission 
to space (less atmospheric absorption). - g ^ 
upwelling radiance contributed from atmosphere to space. 
R d( v j >№> №>0) deices t he atmospheric downwelling 
emissive radiance being reflected by the surface upward to 
space; its incident direction is represented by and 
^ (where the minus sign indicates that direction is always 
downward). (Ma X-L, 2000) 
Though we have improved Ma’s model and got a higher 
precision of the retrieved target parameter LST, the improved 
inversion method is not as efficient as needed. A significant 
disadvantage is its large quantity of calculation, which makes 
the method too complex to be widely used in operational 
application. Furthermore, Chongqing city has its own 
characteristics, mountainous terrain and cloudy climate. Ma’s 
model may not be applicable in such a reality, so it is better to 
develop a new linear statistical model as simple as it could. 
On the base of an intensive comprehension of the physical 
model, we deduced a linear experiential expression with both 
MODIS and observation data in July and August, 2006. 
LST = 2.7932(5^, - 57^)-0.178157;, +354.3806 
(2-2) 
j^j 1 ^32 
where 1 ~ ’ are the brightness temperatures of 
MODIS bands 31 and 32. 
LJ & Jl *<№cq„COimey «hf 
Figure 1-1 LST retrieval results on August 7 th , 2006 
Compared with the meteorological data through July and 
August, 2006, LST retrieved with the linear model matched 
quite well with the observation data in Fengjie, Youyang, 
Fuling, Liangping, Shapingba, and Wanzhou. Figure 1-1 is the 
LST inversion result on August 7 th , 2006 (The white area is 
covered with cloud). 
However, it is better to combine the physical model and 
statistical model together, so as to get a better retrieval precison 
of the target parameter in a practical way. We are working on 
this purpose now, and the result will be presented soon.