International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
ATMOSPHERIC CORRECTION COMPARISON OF SPOT-5 IMAGE 
BASED ON MODEL FLAASH AND MODEL QUAC 
Yunkai GUO *, Fan ZENG * 
* Changsha University of Science & Technology, School of Traffic & Transportation Engineering 
Changsha, Hunan, China, 410004, guoyunkai226(2)163.com 
KEY WORDS: Atmosphere, Comparison, Retrieval, Model, SPOT-5, RVI, Spectral 
ABSTRACT: 
Atmospheric correction of satellite remote sensing image is the precondition of quantitative remote sensing study, and also among 
the difficulties of it. There are various methods and models for atmospheric correction. The author makes the atmospheric correction 
of SPOT-5 multi-spectrum remote sensing image covering Changsha, Zhuzhou and Xiangtan by adopting Model FLAASH and 
Model QUAC in the trail, and then makes a contrastive analysis of the image before and after the correction from the point of sight, 
surface features spectral curve and RVI result. The results show that both models with their specific scope of application can both 
basically eliminate the atmospheric effects and can restore the typical characteristics of various surface features spectral better, 
emphasis the vegetation information; the one using Model FLASSH has higher accuracy than the one using Model QUAC; it is more 
convenient to use Model QUAL than Model FLASSH, because it has little dependence on input parameters and calibration accuracy 
of instruments. 
1. INTRODUCTION 
Electromagnetic waves need to pass through the atmosphere 
before being received by the sensor, in which process the 
atmosphere would absorb and scatter the sunshine and radiation 
from the targets, so the original remote sensing image includes 
both the surface information of physical body and the 
information of the sun and the atmosphere, and the correction 
process of eliminating these atmospheric effects is called 
atmospheric correction (c: Chen Shupeng etc, Study of 
Information Mechanism of Remote Sensing) With the 
increasing development of remote sensing technique, 
atmospheric correction of remote sensing images requires a 
gradual increase, and the research on its methods are being paid 
more and more attention (c: Zhao Yingshi etc, Applications of 
Remote Sensing Principles and Methods). The atmospheric 
correction of remote sensing images began in 1970s, and after 
years of development, the methods for atmospheric correction 
can be broadly divided into three kinds: the method based on 
radioactive transfer model, the method of relative correction 
based on image characteristics and the method based on ground 
linear regression model. Among them, the method based on 
radioactive transfer model is more used in satellite images with 
high precision of the calculated reflectivity, but it is vulnerable 
to the impact of access to real-time atmospheric parameters; the 
method of relative correction based on image features is to 
eliminate atmospheric effect directly of the image features itself, 
but it needs some known or assumed values of the reflectivity 
of the pixel; the key of the method based on ground linear 
regression model is to establish the linear regression equation 
between the ground target and the corresponding pixel of 
remote sensing image, and the advantage of this method is that 
the physical meaning is clear and the calculation is simple, the 
disadvantage is that it depends more on the field work with 
high cost (c: Yang Jiaojun etc, Effect on Atmospheric 
Correction by Inputting Parameters of Model). 
FLASSH based on atmospheric radioactive transfer model is 
commonly used among the atmospheric correction methods at 
present. It can make atmospheric correction on the hyper 
spectral and multispectral data, the atmospheric attribute 
properties inverted pixel by pixel, but it depends on the input 
atmospheric parameters and calibration precision of 
instruments. Model QUAC depends less on the atmospheric 
parameters, relatively easy to achieve, and it also has its 
specific application scope although its calibration accuracy is 
not as high as Model FLAASH. Many researchers have made 
atmospheric correction study on various images by using 
different methods of atmospheric correction, such as M.W. 
Matthew, S. M. Adler-Golden, who make atmospheric 
correction research on AVIRIS data by using Model FLAASH, 
Song Xiaoyu, Wu Bin, who evaluate Model FLAASH by using 
AVIRIS, Hyperion and other high spectral data, B.-C.Gao, M. J. 
Montes, who carry on research on rapid atmospheric correction 
algorithm based on hyperspectral remote sensing data, Yang 
Hang make a comparison between FLAASH and empirical line 
method on their application of OMIS- Il image atmospheric 
correction, etc, all these studies have achieved an ideal result. 
Nevertheless, the comparative study on atmospheric correction 
of SPOT-5 image by using Model FLAASH and Model QUAC 
is quite few at present. This paper mainly discusses the 
atmospheric correction of SPOT-5 image by using Model 
FLAASH and Model QUAC, and makes a contrastive analysis 
of the image in the aspects of sight and surface features spectral 
curve to obtain the actual correction effects of these two 
models. 
2. DATA SOURCE AND STUDY AREA 
Remote sensing data selected for research is SPOT-5 1A data 
after the first class radiation correction, and the spatial 
resolutions of its multi-spectral and panchromatic image are 
separately 10 meters and 5 meters. Study area is within 
Changsha, Zhuzhou and Xiangtan which are typically hilly 
areas in the southern China, and also includes the city and the 
surrounding areas. Date of data acquisition is November 2, 
2010, and due to the cloudless day, the data is of high quality 
and its band and wavelength range are shown in Table 1. In 
order to verify the effect of atmospheric correction better, this