XXII ISPRS Congress 2012: Technical Commission VII

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Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/1: PHYSICAL MODELLING AND SIGNATURES IN REMOTE SENSING]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: ATMOSPHERIC CORRECTION COMPARISON OF SPOT-5 IMAGE BASED ON MODEL FLAASH AND MODEL QUAC Yunkai GUO, Fan ZENG

Document type:: Multivolume work

Structure type:: Chapter

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

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