FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2765587322> ?p ?o ?g. }

• W2765587322 endingPage "1104" @default.
• W2765587322 startingPage "1104" @default.
• W2765587322 abstract "The capability of acquiring accurate and dense three-dimensional geospatial information that covers large survey areas rapidly enables airborne light detection and ranging (LiDAR) has become a powerful technology in numerous fields of geospatial applications and analysis. LiDAR data filtering is the first and essential step for digital elevation model generation, land cover classification, and object reconstruction. The morphological filtering approaches have the advantages of simple concepts and easy implementation, which are able to filter non-ground points effectively. However, the filtering quality of morphological approaches is sensitive to the structuring elements that are the key factors for the filtering success of mathematical operations. Aiming to deal with the dependence on the selection of structuring elements, this paper proposes a novel filter of LiDAR point clouds based on geodesic transformations of mathematical morphology. In comparison to traditional morphological transformations, the geodesic transformations only use the elementary structuring element and converge after a finite number of iterations. Therefore, this algorithm makes it unnecessary to select different window sizes or determine the maximum window size, which can enhance the robustness and automation for unknown environments. Experimental results indicate that the new filtering method has promising and competitive performance for diverse landscapes, which can effectively preserve terrain details and filter non-ground points in various complicated environments." @default.
• W2765587322 created "2017-11-10" @default.
• W2765587322 creator A5014267835 @default.
• W2765587322 creator A5023528036 @default.
• W2765587322 creator A5026898422 @default.
• W2765587322 creator A5030670883 @default.
• W2765587322 creator A5048348204 @default.
• W2765587322 creator A5058888722 @default.
• W2765587322 creator A5073794558 @default.
• W2765587322 creator A5091467752 @default.
• W2765587322 date "2017-10-29" @default.
• W2765587322 modified "2023-10-18" @default.
• W2765587322 title "Airborne LiDAR Data Filtering Based on Geodesic Transformations of Mathematical Morphology" @default.
• W2765587322 cites W1968019867 @default.
• W2765587322 cites W1974696470 @default.
• W2765587322 cites W1977271893 @default.
• W2765587322 cites W1995807936 @default.
• W2765587322 cites W2001951615 @default.
• W2765587322 cites W2002529409 @default.
• W2765587322 cites W2008070546 @default.
• W2765587322 cites W2014091167 @default.
• W2765587322 cites W2016102955 @default.
• W2765587322 cites W2027781877 @default.
• W2765587322 cites W2030359906 @default.
• W2765587322 cites W2034546021 @default.
• W2765587322 cites W2056769281 @default.
• W2765587322 cites W2062751854 @default.
• W2765587322 cites W2064577520 @default.
• W2765587322 cites W2065438578 @default.
• W2765587322 cites W2069251347 @default.
• W2765587322 cites W2071997121 @default.
• W2765587322 cites W2083260484 @default.
• W2765587322 cites W2091168295 @default.
• W2765587322 cites W2127015718 @default.
• W2765587322 cites W2144650681 @default.
• W2765587322 cites W2158166073 @default.
• W2765587322 cites W2170193566 @default.
• W2765587322 cites W2218906635 @default.
• W2765587322 cites W2229319020 @default.
• W2765587322 cites W2259591523 @default.
• W2765587322 cites W2277555957 @default.
• W2765587322 cites W2313041257 @default.
• W2765587322 cites W2322716129 @default.
• W2765587322 cites W2335009182 @default.
• W2765587322 cites W2336835984 @default.
• W2765587322 cites W2353999256 @default.
• W2765587322 cites W2495599185 @default.
• W2765587322 cites W2593120185 @default.
• W2765587322 cites W2604749410 @default.
• W2765587322 doi "https://doi.org/10.3390/rs9111104" @default.
• W2765587322 hasPublicationYear "2017" @default.
• W2765587322 type Work @default.
• W2765587322 sameAs 2765587322 @default.
• W2765587322 citedByCount "23" @default.
• W2765587322 countsByYear W27655873222018 @default.
• W2765587322 countsByYear W27655873222019 @default.
• W2765587322 countsByYear W27655873222020 @default.
• W2765587322 countsByYear W27655873222021 @default.
• W2765587322 countsByYear W27655873222022 @default.
• W2765587322 countsByYear W27655873222023 @default.
• W2765587322 crossrefType "journal-article" @default.
• W2765587322 hasAuthorship W2765587322A5014267835 @default.
• W2765587322 hasAuthorship W2765587322A5023528036 @default.
• W2765587322 hasAuthorship W2765587322A5026898422 @default.
• W2765587322 hasAuthorship W2765587322A5030670883 @default.
• W2765587322 hasAuthorship W2765587322A5048348204 @default.
• W2765587322 hasAuthorship W2765587322A5058888722 @default.
• W2765587322 hasAuthorship W2765587322A5073794558 @default.
• W2765587322 hasAuthorship W2765587322A5091467752 @default.
• W2765587322 hasBestOaLocation W27655873221 @default.
• W2765587322 hasConcept C10138342 @default.
• W2765587322 hasConcept C104317684 @default.
• W2765587322 hasConcept C106131492 @default.
• W2765587322 hasConcept C115051666 @default.
• W2765587322 hasConcept C115961682 @default.
• W2765587322 hasConcept C124101348 @default.
• W2765587322 hasConcept C131979681 @default.
• W2765587322 hasConcept C161840515 @default.
• W2765587322 hasConcept C162324750 @default.
• W2765587322 hasConcept C165818556 @default.
• W2765587322 hasConcept C181843262 @default.
• W2765587322 hasConcept C181844469 @default.
• W2765587322 hasConcept C185568154 @default.
• W2765587322 hasConcept C185592680 @default.
• W2765587322 hasConcept C205649164 @default.
• W2765587322 hasConcept C2524010 @default.
• W2765587322 hasConcept C26517878 @default.
• W2765587322 hasConcept C2775945657 @default.
• W2765587322 hasConcept C31972630 @default.
• W2765587322 hasConcept C33923547 @default.
• W2765587322 hasConcept C38652104 @default.
• W2765587322 hasConcept C41008148 @default.
• W2765587322 hasConcept C51399673 @default.
• W2765587322 hasConcept C55493867 @default.
• W2765587322 hasConcept C58640448 @default.
• W2765587322 hasConcept C62649853 @default.
• W2765587322 hasConcept C63479239 @default.
• W2765587322 hasConcept C74032544 @default.

• next