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Technical Commission VII

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
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
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.
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
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