XXII ISPRS Congress 2012: Technical Commission VII

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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 study used wild spectroradiometer ISI921VF for wild spectral measurements; the band range, which is fitted within the band range of SPOT-5 satellite through spectral resampling, is 380~1050nm of visible light and near infrared light. Band Wavelength Range(um) Panchromatic 0.48~0.71 B1(Green) 0.50~0.59 B2(Red) 0.61~0.68 B3(Near infrared) 0.78~0.89 B4(Short wave infrared) 1.58~1.75 Table 1. Bands and wavelength range of SPOT-5 satellite Before the atmospheric correction, first make the geometric correction on the SPOT-5 image by using the coordinate data of the known control point, and then transform the DN value of i : : —2 -l -l SPOT-5 into radiance (Unit: uw-em ^ :nm -sr ) and apparent reflectance. The transformation process can be finished through the Modeler of ERDAS IMAGINE? 2. 3. ANALYSIS OF APPLICATION AND EFFECT OF ATMOSPHERIC CORRECTION 3.1 Model FLAASH atmospheric correction FLASSH is developed by both Spectral Science, Inc. (SSI), the leader of the research on atmospheric correction algorithm, and Air Force Research Labs(AFRL). It combines radioactive transfer code of MODTRAN4+ and has been modified on this basis. FLAASH is the tool for first-principle atmospheric correction, which is able to correct from the visible light, near infrared light to shortwave infrared light and can also eliminate most of the influence which the air and light and other factors have on clutter reflectance to obtain more accurate parameters of reflectivity, emissivity, surface temperature and other real physical models of surface features. FLAASH begins with a standard equation of spectral radiance of the single pixel received by a standard planar lambertian (or nearly a planar lambertian), which is based on the sun spectrum (not including thermal radiation), by the sensor. | A B : Lebe i. (1) 1-554 das Thereinto, L’ is the radiance for the single pixel received by the sensor; P is the surface reflectance for the pixel; pis the average surface reflectance for this pixel and surrounding pixels; S is the spherical albedo for the atmosphere; L,’ is the radiance when atmosphere radiation enters into the sensor, A,B is the coefficient determined by the atmospheric conditions and the geometric conditions of underlying surface with nothing to do with surface reflectance. (A 9 /(1- e , S)) indicates the radiation energy entering into the sensor directly from the target surface features, which implies two cases: the reflection happening when the sun irradiates on the target surface features; the neighboring surface features scatter through the atmosphere and then irradiate on the surface features for reflection again U (Bo J(1-o, S)) indicates the amount of radiation which enters into the sensor through the atmosphere from the surface. The difference between P and P , explains "proximity effect" (mixed radiation close to pixel) caused by the atmospheric scattering, in order to ignore this proximity effect, so p _p .. However, there will be significant errors when there is mist or a strong contrast between the surfaces. According to the Formula (1), surface reflectance can be calculated pixel by pixel. FLAASH uses spatial average radiancy, ignoring the “proximity effect”, to get approximate equation (2) and to estimate the spatial average reflectance. Thereinto, L, is the spatial average radiation image generated by convolution with the radiation image and spatial weighting function. B , [8:2 2). Q) 1-p 3S Most of the atmospheric correction parameters used in this trial are from the header file of image data, and the specific parameter data is shown in Table 2. After obtaining the required parameter, the true surface reflectance of the whole image can be calculated pixel by pixel by using Equation 1 and Equation 2. Date of Time of Height of ; ; Sensor Imaging Imaging Sensor 2010.11.2 3:28:14 SPOT-5 800km Atmospheric ^ Aerosol Center Center Model Type Longitude/(^ ) Latitude/(^ ) MLW Rural 113.1001 28.0001 Elevation Angle of ~~ Azimuth of the : bay the Sun/(° ) Sun/(° ) Altitude — Visibility 46.192779 164.892501 0.037km 35km Note: Imaging time is GMT with a difference of 8 hours between GMT and Beijing Time. Table 2. Input parameters of FLAASH atmospheric correction 3.2 Model QUAC atmospheric correction Model QUAC is the method of atmospheric correction for hyper spectral and multispectral images from the visible light, near infrared light to shout-wave infrared light. QUAC is different from the first-principle atmospheric correction, because it obtains atmospheric compensating parameters directly from the image (observe pixel spectral) without complete information to achieve the atmospheric correction more approximate than FLAASH. p =(p,+p,+—+p,)/n (3) As shown in Equation (3) below, QUAC is based on experience to collect the average reflectance of different substances, such as the end member spectrum in the field of vision. n indicates the number of end members, essentially independent field of vision, which means a faster operating rate than the

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