05257nam 2201201z- 450 991036774750332120231214132942.03-03921-757-7(CKB)4100000010106242(oapen)https://directory.doabooks.org/handle/20.500.12854/62022(EXLCZ)99410000001010624220202102d2019 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierVery High Resolution (VHR) Satellite Imagery: Processing and ApplicationsMDPI - Multidisciplinary Digital Publishing Institute20191 electronic resource (262 p.)3-03921-756-9 Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing.Very High Resolution very high-resolution Pléiades imagerysurface convergencedata augmentationacquisition geometrySVM classificationurban water mappingbeaver dam analogueagriculture parcel segmentationmorphological building indexairborne hypespectral imagerysunglint correctionwater indexover-segmentation index (OSI)High-resolution satellite imagerymulti-resolution segmentation (MRS)GaoFen-2 (GF-2)benthic mappingscene classificationgreenhouse extractionedge constraintDeformable CNNbuilt-up areas extractionultra-dense connectionseagrassbeaver mimicryforested mountainnatural hazardsremote sensingdimensionality reduction techniquesroad extractionlandslide monitoringSlumgullion landslidesynthetic aperture radarbuilding detectionWorldview-2saliency indexunder-segmentation index (USI)texture analysisfast marching methodvideo satelliteCNNcapsulesuper-resolutionfeature distillationshadow detectionPrimaryCapssemiautomaticcompensation unitsuperpixelsriparianQuickBirdsubmesoscalelinear unmixingaccuracy assessmentcomposite error index (CEI)cyanobacterialocal feature pointsFaster R-CNNoccluded object detectionerror index of total area (ETA)large displacementsthreshold stabilityremote sensing imagerywater column correctioncanopy height modelspiral eddysub-pixel offset trackingconsensusstream restorationwestern Baltic SeaWorldviewvery high-resolution imageCapsNetatmospheric correctionMarcello Javierauth1325066Eugenio FranciscoauthBOOK9910367747503321Very High Resolution (VHR) Satellite Imagery: Processing and Applications3036538UNINA