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001453439 001__ 1453439
001453439 003__ OCoLC
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001453439 019__ $$a1352795084
001453439 020__ $$a9783031162138$$q(electronic bk.)
001453439 020__ $$a3031162137$$q(electronic bk.)
001453439 020__ $$z3031162129
001453439 020__ $$z9783031162121
001453439 0247_ $$a10.1007/978-3-031-16213-8$$2doi
001453439 035__ $$aSP(OCoLC)1352969925
001453439 040__ $$aEBLCP$$beng$$epn$$cEBLCP$$dGW5XE$$dYDX$$dOCLCF$$dWAU
001453439 049__ $$aISEA
001453439 050_4 $$aQH541.5.C65
001453439 08204 $$a577.510284$$223/eng/20221219
001453439 1112_ $$aInternational Conference of European Spatial Data for Coastal and Marine Remote Sensing$$d(2022 :$$cSaint Malo, France)
001453439 24510 $$aEuropean spatial data for coastal and marine remote sensing :$$bproceedings of International Conference EUCOMARE 2022-Saint Malo, France /$$cSimona Niculescu, editor.
001453439 260__ $$aCham :$$bSpringer,$$c2023.
001453439 300__ $$a1 online resource (256 pages)
001453439 336__ $$atext$$btxt$$2rdacontent
001453439 337__ $$acomputer$$bc$$2rdamedia
001453439 338__ $$aonline resource$$bcr$$2rdacarrier
001453439 500__ $$a3.3.2 Image Segmentation
001453439 5050_ $$aIntro -- Editorial for Special Issue: European Spatial Data for Coastal and Marine Remote Sensing -- In the Category of Short Articles, There Are Six Articles -- References -- Contents -- Contributors -- Detection of Coccolithophore Bloom Episodes in Algiers Bay Using Satellite and In Situ Analysis -- 1 Introduction -- 2 Study Area -- 3 Materials and Methods -- 3.1 In Situ Data -- 3.2 Satellite Data Acquisition -- 3.3 Coccolithophore Bloom Index (Cocco-Index) -- 4 Results -- 4.1 Coccolithophore Bloom Episodes in the Algiers Bay from In Situ Observations
001453439 5058_ $$a4.2 Monitoring and Spectral Response of E1, E2, and E3 -- 4.3 Cocco-Index of E1, E2, and E3 -- 4.4 Coccolithophore Bloom Episodes in the Algiers Bay (from 2003 to 2018) -- 5 Discussion -- 6 Conclusion -- References -- Multiscale Spatiotemporal NDVI Mapping of Salt Marshes Using Sentinel-2, Dove, and UAV Imagery in the Bay of Mont-Saint-Michel, France -- 1 Introduction -- 2 Methodology -- 2.1 Study Area -- 2.2 Imagery Source and Processing -- 2.2.1 Satellite Sentinel-2 -- 2.2.2 Nanosatellite Dove -- 2.2.3 Unmanned Aerial Vehicle -- 2.3 Predicting the NIR at the UAV Scale
001453439 5058_ $$a2.3.1 Two-Scaled Spectral Datasets -- 2.3.2 Neural Network Regression -- 3 Results -- 3.1 Changes in the Normalized Difference Vegetation Index Values -- 3.1.1 Satellite Sentinel-2 -- 3.1.2 Nanosatellite Dove -- 3.2 Prediction of the Normalized Difference Vegetation Index Values -- 3.2.1 Unmanned Aerial Vehicle Near-Infrared -- 4 Discussion -- 4.1 Salt Marsh Spatiotemporal Patterns -- 4.1.1 Satellite-Based Salt Marsh Spatial Analysis -- 4.1.2 Satellite-Based Salt Marsh Temporal Change -- 4.2 Modelling the Extent of Salt Marsh at an Ultra-High Resolution
001453439 5058_ $$a4.2.1 Spectral Predictive Modelling at Ultra-High Resolution -- 4.2.2 Predictive Modelling of Vegetation Height at Ultra-High Resolution -- 5 Conclusion -- References -- Contribution of Near- and Mid-Infrared Wavebands to Mapping Fine-Scale Coastal Ecogeomorphological Features -- 1 Introduction -- 2 Methodology -- 2.1 Study Site -- 2.2 Imagery Data -- 2.3 Class Identification -- 2.4 Pixel-Based Supervised Classification -- 3 Results and Discussion -- 3.1 Identification of the Best Model Based on Overall Accuracy -- 3.2 Class-Level Accuracy
001453439 5058_ $$a3.2.1 Best Model for Classification of the Plant Features -- 3.2.2 Sedimentary Feature Classifications -- 4 Conclusion -- References -- Monitoring Land Cover Change in the Southeastern Baltic Sea Since the 1980s by Remote Sensing -- 1 Introduction -- 2 Context -- 2.1 The Soviet Period: Military Control and Economic Specialization -- 2.2 Liberalization and Gradual Coastalization of the Southeastern Baltic Countries -- 3 Methodology -- 3.1 Definition of the Coastal Zone Study Area -- 3.2 Data Acquisition -- 3.3 Method of Analysis of Land-Use Change -- 3.3.1 Pre-processing
001453439 506__ $$aAccess limited to authorized users.
001453439 520__ $$aThis volume presents full paper contributions from the International Conference of European Spatial Data for Coastal and Marine Remote Sensing (EUCOMARE) 2022, with the support of the ERASMUS+ Programme of the European Union, held in Saint Malo, France. EUCOMARE aims to promote academic and technical exchange on coastal related studies including coastal environmental and socio-economic issues, with the use of European remotely sensed data. The book is an excellent resource for scientists, engineers, and programme managers eager to learn about the recent developments and achievements in the field of remote sensing applications on marine and coastal areas. Readers will learn about recent advances in sensors' radiometric, spatial, temporal and spectral resolution, as well as new data processing approaches in remote sensing for monitoring and mapping the various characteristics of marine, coastal and aquatic systems.
001453439 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 19, 2022).
001453439 650_0 $$aCoastal ecology$$xRemote sensing$$vCongresses.
001453439 650_0 $$aMarine ecology$$xRemote sensing$$vCongresses.
001453439 650_0 $$aGeospatial data$$vCongresses.
001453439 650_0 $$aCoastal zone management$$vCongresses.
001453439 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001453439 655_0 $$aElectronic books.
001453439 7001_ $$aNiculescu, Simona.
001453439 77608 $$iPrint version:$$aNiculescu, Simona$$tEuropean Spatial Data for Coastal and Marine Remote Sensing$$dCham : Springer International Publishing AG,c2023$$z9783031162121
001453439 852__ $$bebk
001453439 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-16213-8$$zOnline Access$$91397441.1
001453439 909CO $$ooai:library.usi.edu:1453439$$pGLOBAL_SET
001453439 980__ $$aBIB
001453439 980__ $$aEBOOK
001453439 982__ $$aEbook
001453439 983__ $$aOnline
001453439 994__ $$a92$$bISE