Matches in SemOpenAlex for { <https://semopenalex.org/work/W2046203484> ?p ?o ?g. }
Showing items 1 to 81 of
81
with 100 items per page.
- W2046203484 endingPage "498" @default.
- W2046203484 startingPage "493" @default.
- W2046203484 abstract "Coastal mapping is essential for a variety of applications such as coastal resource management, coastal environmental protection, and coastal development and planning. Various mapping techniques, like ground and aerial surveying, have been utilized in mapping coastal areas. Recently, multispectral and hyperspectral satellite images and elevation data from active sensors have also been used in coastal mapping. Integrating these datasets can provide more reliable coastal information. This paper presents a novel technique for coastal mapping from an airborne visible/infrared imaging spectrometer (AVIRIS) hyperspectral image and a light detection and ranging (LIDAR)-based digital elevation model (DEM). The DEM was used to detect and create a vector layer for building polygons. Subsequently, building pixels were removed from the AVIRIS image and the image was classified with a supervised classifier to discriminate road and water pixels. Two vector layers for the road network and the shoreline segments were vectorized from road pixels and water-body border pixels using several image-processing algorithms. The geometric accuracy and completeness of the results were evaluated. The average positional accuracies for the building, road network, and shoreline layers were 2.3, 5.7, and 7.2 m, respectively. The detection rates of the three layers were 93.2%, 91.3%, and 95.2%, respectively. Results confirmed that utilizing laser ranging data to detect and remove buildings from optical images before the classification process enhances the outcomes of this process. Consequently, integrating laser and optical data provides high-quality and more reliable coastal geospatial information." @default.
- W2046203484 created "2016-06-24" @default.
- W2046203484 creator A5012384560 @default.
- W2046203484 date "2008-07-01" @default.
- W2046203484 modified "2023-10-15" @default.
- W2046203484 title "Fusion of hyperspectral images and lidar-based dems for coastal mapping" @default.
- W2046203484 cites W1977428739 @default.
- W2046203484 cites W1980201470 @default.
- W2046203484 cites W1983752812 @default.
- W2046203484 cites W1984441870 @default.
- W2046203484 cites W2010221273 @default.
- W2046203484 cites W2092120745 @default.
- W2046203484 cites W2133029430 @default.
- W2046203484 doi "https://doi.org/10.1016/j.optlaseng.2008.01.012" @default.
- W2046203484 hasPublicationYear "2008" @default.
- W2046203484 type Work @default.
- W2046203484 sameAs 2046203484 @default.
- W2046203484 citedByCount "49" @default.
- W2046203484 countsByYear W20462034842012 @default.
- W2046203484 countsByYear W20462034842013 @default.
- W2046203484 countsByYear W20462034842014 @default.
- W2046203484 countsByYear W20462034842015 @default.
- W2046203484 countsByYear W20462034842016 @default.
- W2046203484 countsByYear W20462034842017 @default.
- W2046203484 countsByYear W20462034842018 @default.
- W2046203484 countsByYear W20462034842019 @default.
- W2046203484 countsByYear W20462034842020 @default.
- W2046203484 countsByYear W20462034842021 @default.
- W2046203484 countsByYear W20462034842022 @default.
- W2046203484 countsByYear W20462034842023 @default.
- W2046203484 crossrefType "journal-article" @default.
- W2046203484 hasAuthorship W2046203484A5012384560 @default.
- W2046203484 hasBestOaLocation W20462034842 @default.
- W2046203484 hasConcept C111368507 @default.
- W2046203484 hasConcept C115051666 @default.
- W2046203484 hasConcept C127313418 @default.
- W2046203484 hasConcept C152382732 @default.
- W2046203484 hasConcept C154945302 @default.
- W2046203484 hasConcept C159078339 @default.
- W2046203484 hasConcept C160633673 @default.
- W2046203484 hasConcept C173163844 @default.
- W2046203484 hasConcept C181843262 @default.
- W2046203484 hasConcept C41008148 @default.
- W2046203484 hasConcept C51399673 @default.
- W2046203484 hasConcept C62649853 @default.
- W2046203484 hasConcept C76155785 @default.
- W2046203484 hasConceptScore W2046203484C111368507 @default.
- W2046203484 hasConceptScore W2046203484C115051666 @default.
- W2046203484 hasConceptScore W2046203484C127313418 @default.
- W2046203484 hasConceptScore W2046203484C152382732 @default.
- W2046203484 hasConceptScore W2046203484C154945302 @default.
- W2046203484 hasConceptScore W2046203484C159078339 @default.
- W2046203484 hasConceptScore W2046203484C160633673 @default.
- W2046203484 hasConceptScore W2046203484C173163844 @default.
- W2046203484 hasConceptScore W2046203484C181843262 @default.
- W2046203484 hasConceptScore W2046203484C41008148 @default.
- W2046203484 hasConceptScore W2046203484C51399673 @default.
- W2046203484 hasConceptScore W2046203484C62649853 @default.
- W2046203484 hasConceptScore W2046203484C76155785 @default.
- W2046203484 hasIssue "7" @default.
- W2046203484 hasLocation W20462034841 @default.
- W2046203484 hasLocation W20462034842 @default.
- W2046203484 hasOpenAccess W2046203484 @default.
- W2046203484 hasPrimaryLocation W20462034841 @default.
- W2046203484 hasRelatedWork W2018850895 @default.
- W2046203484 hasRelatedWork W2022304901 @default.
- W2046203484 hasRelatedWork W2486104965 @default.
- W2046203484 hasRelatedWork W2594043982 @default.
- W2046203484 hasRelatedWork W2758145160 @default.
- W2046203484 hasRelatedWork W2988577871 @default.
- W2046203484 hasRelatedWork W3036493597 @default.
- W2046203484 hasRelatedWork W4205174160 @default.
- W2046203484 hasRelatedWork W4316465086 @default.
- W2046203484 hasRelatedWork W4320725409 @default.
- W2046203484 hasVolume "46" @default.
- W2046203484 isParatext "false" @default.
- W2046203484 isRetracted "false" @default.
- W2046203484 magId "2046203484" @default.
- W2046203484 workType "article" @default.