Artificial Intelligence Techniques for Satellite Image Analysis PDF
Preview Artificial Intelligence Techniques for Satellite Image Analysis
Remote Sensing and Digital Image Processing D. Jude Hemanth Editor Artifi cial Intelligence Techniques for Satellite Image Analysis Remote Sensing and Digital Image Processing Volume 24 SeriesEditor FreekD.vanderMeer,FacultyofGeo-InformationScienceandEarthObservation (ITC),DepartmentofEarthSystemsAnalysis,UniversityofTwente,Enschede, TheNetherlands AnnaJarocin´ska,DepartmentofGeoinformatics,CartographyandRemote Sensing,UniversityofWarsaw,Warsaw,Poland Remote Sensing and Digital Image Processing book series. Remote sensing is the acquisitionofPhysicaldataofanobjectwithouttouchorcontact.Earthobservation satellites have been used for many decades in a wide field of applications. With the advancements in sensor technology, earth imaging is now possible at an unprecedented level of detail. Imaging spectrometers and thermal multispectral systems acquire detailed spectroscopic information of physical properties of the earth’s surface. Dynamic processes can now be studied with interferometric systems. SAR interferometry, laser altimetry and high-resolution imaging allow a very detailed, three-dimensional reconstruction of the earth surface. With the adventofmulti-sensormissioncomesaneweraofimaging,openingthepossibility ofintegratingdatefromvarioussensorsystems.Thebookspublishedintheseries explorethesetopicsinremotesensingandprovideaframeworkforrelatedadvanced digitalimageprocessingapproaches. RDIPEditorialAdvisoryBoard: MichaelAbrams,NASAJetPropulsionLaboratory,Pasadena,CA,USA PaulCurran,CityUniversityLondon,UK ArnoldDekker,CSIROLandandWaterDivision,Canberra,Australia StevenM.deJong,UtrechtUniversity,TheNetherlands MichaelSchaepman,UniversityofZurich,Switzerland EARSeL-RDIPEditorialAdvisoryBoard: MarioGomarasca,CNR-IREA,Milan,Italy MarttiHallikainen,HelsinkiUniversityofTechnology,Finland HåkanOlsson,SwedishUniversityofAgriculturalSciences,Sweden EberhardParlow,UniversityofBasel,Switzerland RainerReuter,UniversityofOldenburg,Germany. AcceptedforinclusioninScopus. Moreinformationaboutthisseriesathttp://www.springer.com/series/6477 D. Jude Hemanth Editor Artificial Intelligence Techniques for Satellite Image Analysis 123 Editor D.JudeHemanth ElectronicsandCommunicationEngineering KarunyaUniversity Coimbatore,TamilNadu,India ISSN1567-3200 ISSN2215-1842 (electronic) RemoteSensingandDigitalImageProcessing ISBN978-3-030-24177-3 ISBN978-3-030-24178-0 (eBook) https://doi.org/10.1007/978-3-030-24178-0 ©SpringerNatureSwitzerlandAG2020 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthors,andtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictional claimsinpublishedmapsandinstitutionalaffiliations. Coverillustration:Portland3DLandscapeViewSouth-NorthNaturalColor(©FrankRamspott/Getty Images/iStock) ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG. Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Preface The necessity for the application of artificial intelligence (AI) techniques in the field of remote sensing is exponentially increasing in today’s scenario. However, theliteraturescoveringthesetwobroadareassimultaneouslyarerelativelyscarce. Thisisoneofthesignificantmotivationsbehindtheoriginofthisbook.Thisbook ishighlyinterdisciplinarywhichcoversreadershipfromresearchers/scientistsinthe field of AI, remote sensing, and image processing. Different practical applications arecoveredinthisbookwhichwillcreateaninterestamongthebuddingengineers in these areas. On the other hand, in-depth analysis also has been carried out to attracttheexpertstofurtherexploreintheseareasofresearch.Thisbook,indeed,is awholesomeproductwhichwillcatertheneedsofthewidevarietyofacademicians, scientists,andresearchers.Abriefintroductionabouteachchapterisasfollows. Chapter 1 covers the application of augmented reality (AR) for satellite image analysis. The main objective of this work is to display the satellite image in a better way which will enhance the success of the subsequent image analysis methods. Chapter 2 deals with an intelligent method for clustering the satellite imagesintodifferentgroups.Thismethodhelpstoidentifythedifferentobjectsin anefficientway.Chapter3reportsabouttheapplicationofdeeplearningapproach foridentifyingthedifferentvegetationregionsinsatelliteimages.Thisapplication isverysignificantinthecontextofenhancingthecropproductionintheagriculture field. Chapter 4 illustrates the applications of artificial neural networks for detec- tion/tracking of ships via satellite images. These methods are highly useful for controlling the maritime traffic apart from the surveillance application. Chapter 5 covers the intelligent image enhancement techniques which are one of the focal areasofresearchinremotesensing.ArtificialBeeColony(ABC)approachisused for enhancing the quality of the images. The analyses of synthetic aperture radar (SAR)imagesarecarriedoutinChap.6.Noiseremovalisperformedinthiswork withthehelpofmathematicaltransform-basedapproaches. Chapter 7 deals with the application of fuzzy logic concepts for SAR image analysis. Fuzzy logic methods are used to detect the nutrition level of crops and subsequentplanningforimprovingthecropproduction.Naturalimagesandfeatures v vi Preface are detected from satellite images in Chap. 8. Convolutional neural networks are usedinthischapterforobjectdetectionapplication.Chapter9coverstheconceptsof change detection of tropical mangrove ecosystem using mathematical approaches. Thismethodishighlyusefultodetectthelevelofdeforestationinaspecificregion. The application of different AI-based classifiers for measuring the quality of vegetation land is explored in Chap. 10. The merits and demerits of different AI- basedclassifiersarealsoreportedinthischapter.Asurveyonthevariousmachine learning (ML) approaches for satellite image analysis is carried out in Chap. 11. The different applications of satellite image analysis are also dealt in this chapter. Water body extraction from satellite images is the emphasis of Chap. 12. Wavelet transformisusedinthisresearchworktocarryouttheextractionprocess. Wearegratefultotheauthorsandreviewersfortheirexcellentcontributionsfor makingthisbookpossible. OurspecialthanksgotoAnnaJaroscinska,VanDerMeer,andFreekD(Series Editors of Remote Sensing and Digital Image Processing) for the opportunity to organizethiseditedvolume. We are grateful to Springer, especially to Petra van Steenbergen (Executive Editor),fortheexcellentcollaboration. Thiseditedbookcoversthefundamentalconceptsandapplicationareasindetail whichisoneofthemainadvantagesofthisbook.Beinganinterdisciplinarybook, we hope it will be useful to a wide variety of readers and will provide useful informationtoprofessors,researchers,andstudents. Coimbatore,TamilNadu,India D.JudeHemanth January,2019 Contents 1 HeighteningSatelliteImageDisplayviaMobileAugmented Reality–ACutting-EdgePlanningModel .............................. 1 SagayaAurelia 2 Multithreading Approach for Clustering of Multiplane SatelliteImages ............................................................. 25 C.RashmiandG.HemanthaKumar 3 ClassificationofField-LevelCropTypeswithaTimeSeries SatelliteDataUsingDeepNeuralNetwork.............................. 49 J.Jayanth,V. S.Shalini,T.AshokKumar,andShivaprakashKoliwad 4 Detection of Ship from Satellite Images Using Deep ConvolutionalNeuralNetworkswithImprovedMedianFilter....... 69 S.IwinThanakumarJoseph,J.Sasikala,andD.SujithaJuliet 5 ArtificialBeeColony-OptimizedContrastEnhancementfor SatelliteImageFusion...................................................... 83 AnjuAsokanandJ.Anitha 6 EffectiveTransformDomainDenoisingofOceanographicSAR ImagesforImprovedTargetCharacterization.......................... 107 S. Arivazhagan, W. Sylvia Lilly Jebarani, R. Newlin Shebiah, S.VinethLigi,P. V.HareeshKumar,andK.Anilkumar 7 FusedSegmentationAlgorithmfortheDetectionofNutrient DeficiencyinCropsUsingSARImages.................................. 137 V.P.Ananthi 8 DetectionofNaturalFeaturesandObjectsinSatelliteImages bySemanticSegmentationUsingNeuralNetworks .................... 161 ViharKurama,SamhitaAlla,andSrideviTumula vii viii Contents 9 Change Detection of Tropical Mangrove Ecosystem with SubpixelClassificationofTimeSeriesHyperspectral Imagery...................................................................... 189 DipanwitaGhoshandSomdattaChakravortty 10 Crop Classification and Mapping for Agricultural Land fromSatelliteImages....................................................... 213 A.KalaivaniandRashmitaKhilar 11 Next-GenerationArtificialIntelligenceTechniquesforSatellite DataProcessing............................................................. 235 NehaSisodiya,NitantDube,andPriyankThakkar 12 AWaveletTransformAppliedSpectralIndexforEffective WaterBodyExtractionfromModerate-ResolutionSatellite Images........................................................................ 255 R.JeniceAromaandKumudhaRaimond Chapter 1 Heightening Satellite Image Display via Mobile Augmented Reality – A Cutting-Edge Planning Model SagayaAurelia Abstract This paper summarizes on object detection, classification, analysis, and display for optical satellite image. Initially, all the existing object detection and object viewing system based on AI techniques are introduced. Various optical imaginarymethodsandthepossibilityofimmersingopticaland3Ddatawithother data sources are also explained. The surveyed literatures show that in most of the case,thedetectedobjectsaretakenasresourceforplanning.Wealsoobservedthat theimageviewinganddisplayingmodelwasignoredbymanyauthorswhichisone ofthekeyconceptsfornextphase.SatelliteARplaysavitalroleindisplayingthe images.Overall,itcanbeseenthatopticalimageviewalongwithARdisplaycan beusedforbetterplanning,whichisoneofthepopularresearchtopicsandhasan excessiveoperationalpotentialwhichistheneedofthehourdealingwithanalyzing, predicting,andviewinglargeamountofdata. Keywords MAR · Objectdetection · SatelliteAR · Imageanalysis · AI · Satelliteview · Imagedisplay · Opticalsatellitedata · Objectrecognition · Tracking · Rendering · 3Ddata 1.1 Introduction Artificial intelligence is a field of academic study with its own vocabulary and specialistterms.Itisaprocesswhereacomputersolvesataskinawaythatmimics humanbehavior.Today,narrowAR—whenamachineistrainedtodooneparticular task—isbecomingmorewidelyusedfromvirtualassistancetoself-drivingcarsto automatictaggingyourfriendsinyourphotosonFacebook.Itmakestothinklike human,acthumanly,andthinkandactrationally. S.Aurelia((cid:2)) ChristUniversity,Bengaluru,Karnataka,India e-mail:[email protected] ©SpringerNatureSwitzerlandAG2020 1 D.J.Hemanth(ed.),ArtificialIntelligenceTechniquesforSatelliteImageAnalysis, RemoteSensingandDigitalImageProcessing24, https://doi.org/10.1007/978-3-030-24178-0_1
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