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Experimental evaluation of ALS point cloud ground extraction tools over different terrain slope and land-cover types

Experimental evaluation of ALS point cloud ground ...

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dc.contributor.author Korzeniowska, Karolina [USOS45672] pl
dc.contributor.author Pfeifer, Norbert pl
dc.contributor.author Mandlburger, Gottfried pl
dc.contributor.author Lugmayr, Agata pl
dc.date.accessioned 2015-03-31T10:29:14Z
dc.date.available 2015-03-31T10:29:14Z
dc.date.issued 2014 pl
dc.identifier.issn 0143-1161 pl
dc.identifier.uri http://ruj.uj.edu.pl/xmlui/handle/item/4408
dc.language eng pl
dc.rights Dodaję tylko opis bibliograficzny *
dc.rights.uri *
dc.title Experimental evaluation of ALS point cloud ground extraction tools over different terrain slope and land-cover types pl
dc.type JournalArticle pl
dc.description.physical 4673-4697 pl
dc.abstract.en The article presents an evaluation of different terrain point extraction algorithms for airborne laser scanning (ALS) point clouds. The research area covers eight test sites with varying point densities in the range 3–15 points m^−^2 and different surface topography as well as land-cover characteristics. In this article, existing implementations of algorithms were considered. Approaches that are based on mathematical morphology, progressive densification, robust surface interpolation, and segmentation are compared. The results are described based on qualitative and quantitative analyses. A quantification of the qualitative analyses is presented and applied to the data sets in this example. The achieved results show that the analysed algorithms give classification accuracy depending on the landscape and land cover. Although the results for flat and mountainous areas as well as for sparse and dense vegetation are in line with previous tests, this analysis provides an overview of situations in which the quantitative evaluation is not enough to correctly assess the classification results. pl
dc.description.volume 35 pl
dc.description.number 13 pl
dc.identifier.doi 10.1080/01431161.2014.919684 pl
dc.identifier.eissn 1366-5901 pl
dc.title.journal International Journal of Remote Sensing pl
dc.language.container eng pl
dc.affiliation Wydział Biologii i Nauk o Ziemi : Instytut Geografii i Gospodarki Przestrzennej pl
dc.subtype Article pl
dc.rights.original bez licencji pl
dc.pbn.affiliation USOS45672:UJ.WBl; pl
.pointsMNiSW [2014 A]: 30


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