Reduction of atmospheric and topographic effect on Landsat TM data for forest classification
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International Journal of Remote Sensing
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Reduction of atmospheric and topographic effect on Landsat TM data for forest
classification
H. Huang ab; P. Gong ac; N. Clinton c; F. Hui aa State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote SensingApplications of the Chinese Academy of Sciences and Beijing Normal University, Beijing, China b GraduateSchool of the Chinese Academy of Sciences, Beijing, China c Division of Ecosystem Science, University ofCalifornia, Berkeley, USAFirst Published:October2008
To cite this Article Huang, H., Gong, P., Clinton, N. and Hui, F.(2008)'Reduction of atmospheric and topographic effect on Landsat TMdata for forest classification',International Journal of Remote Sensing,29:19,5623 — 5642
To link to this Article: DOI: 10.1080/01431160802082148
URL: http://dx.doi.org/10.1080/01431160802082148
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The publisher does not give any warranty express or implied or make any representation that the contentswill be complete or accurate or up to date. The accuracy of any instructions, formulae and drug dosesshould be independently verified with primary sources. The publisher shall not be liable for any loss,actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directlyor indirectly in connection with or arising out of the use of this material.ReductionofatmosphericandtopographiceffectonLandsatTMdata
forforestclassification
H.HUANG{{,P.GONG*{§,N.CLINTON§andF.HUI{
{StateKeyLaboratoryofRemoteSensingScience,jointlysponsoredbytheInstituteof
RemoteSensingApplicationsoftheChineseAcademyofSciencesandBeijingNormal
University,Beijing,100101,China
{GraduateSchooloftheChineseAcademyofSciences,Beijing,100049,China
§DivisionofEcosystemScience,UniversityofCalifornia,Berkeley,CA94720-3114,
USA
(Received4January2007;infinalform17August2007)
Theincidentradianceinforestedareaswithruggedterrainvariesgreatlywiththechangesinsolarelevationandazimuth,slopeandaspectoftheterrain,andtherelativepositionoftrees.Thegeotropicnaturemustbeconsideredinthecourseoftopographiccorrection.TheSun-Canopy-Sensor(SCS)modelisintroducedtosubstitutethecosinecorrectioninaphysicalmodel.Weusedanatmosphericsimulationcode,MODTRAN,andadigitalelevationmodel(DEM)tocalculatethepathradiance,downwardsdiffuseradianceandtwo-waytransmittanceofdirectanddiffuselightatdifferentaltitudes.BasedontheatmosphericparametersderivedaboveandtheLambertianassumption,surfacereflectanceinaforestedareawasretrievedfromLandsatThematicMapper(TM)imageryusingarevisedphysicalmodel.Meanwhile,asmoothedDEMwasusedtoassesstheeffectofnoiseontheDEMandmisregistrationbetweentheDEMandthesatelliteimagery.Correlationanalysis,spectralcomparisonbetweensunlitandshadedslopesandasupportvectormachine(SVM)classificationwereperformedtoassesstheeffectoftherevisedradiometriccorrectionalgorithm.ResultsindicatethattherevisedphysicalmodelwithsmoothedDEMismoreadequateforforestedterrainandmoreconsistentspectraforsimilarvegetationunderdifferentilluminationscanbeobtained.Finally,higherclassificationaccuracyofforestedlandcanbeachievedwiththerevisedcorrectionalgorithmcomparedwiththeSCScorrectionandtheoriginalphysicalcorrectionmodel.
1.Introduction
Quantitativeretrievalofforestparametersishighlydesirableinforestmanagement,
ecosystemmodellingandglobalchangestudies.However,theeffectofterrainseverely
influencesquantitativeremotesensinginforestedmountainareas.Howtoaccurately
retrievesurfacereflectancesinmountainousareasisoneofthemostimportantremote
sensingproblems(Civco1989,Meyeretal.1993,Reeder2002).Incidenceandexitance
angleschangewithdifferentslope,aspectandaltitudeoverruggedtopography.
Therefore,irradiationfromtheSunandenergyreflectedbythesurfacecapturedbythe
sensorareredistributedunevenly.Asaresult,thesunlitsurfacewillbebrighterthan
theslopefacingawayfromtheSun.Thisleadstothesamesurfacecovertypebeing
