Individual tree identification in airborne laser data by inverse search window

dc.creatorGorgens, Eric Bastos
dc.creatorRodriguez, Luiz Carlos Estraviz
dc.creatorSilva, André Gracioso Peres da
dc.creatorSilva, Carlos Alberto
dc.date2016-04-07
dc.date2017-08-01T20:19:38Z
dc.date2017-08-01T20:19:38Z
dc.date2017-08-01
dc.date.accessioned2023-09-28T19:55:51Z
dc.date.available2023-09-28T19:55:51Z
dc.identifierGORGENS, E. B. et al. Individual tree identification in airborne laser data by inverse search window. CERNE, Lavras, v. 21, n. 1, Jan./Mar. 2015. DOI: 10.1590/01047760201521011535.
dc.identifierhttp://repositorio.ufla.br/jspui/handle/1/14951
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9040408
dc.descriptionThe local maximum filtering performance is highly dependent of the window size definition. This paper proposes that the window size should be determined by an inverse relationship to the canopy height model, and test the hypothesis that a windowsize inversely proportional will have better performance than the window proportional to the canopy height model. The study area is located in the southeastern region of the State of British Columbia, Canada. The natural vegetation is the boreal type and is characterized by the dominance of two species Picea engelmannii Parry ex. Engelmann (Engelmann spruce) and Abies lasiocarpa (Hook.) Nutt. (sub-alpine fir). The relief is mountainous with altitudes ranging from 650-2400 meters. 62 plots with 256 square meters were measured in the field. The airborne LiDAR had discrete returns, 2 points per square meter density and small-footprint. The performance of the search windows was evaluated based on success percentage, absolute average error and also compared to the observed values of the field plots. The local maximum filter underestimated the number of trees per hectare for both window sizing methods. The use of the inverse proportional window size has resulted in superior results, particularly for regions with highest density of trees.
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languageeng
dc.publisherUniversidade Federal de Lavras (UFLA)
dc.rightsCopyright (c) 2016 CERNE
dc.rightshttp://creativecommons.org/licenses/by/4.0/
dc.rightsAttribution 4.0 International
dc.rightshttp://creativecommons.org/licenses/by/4.0/
dc.sourceCERNE; Vol 21 No 1 (2015); 91-96
dc.sourceCERNE; Vol 21 No 1 (2015); 91-96
dc.source2317-6342
dc.source0104-7760
dc.subjectLIDAR
dc.subjectMáximo local
dc.subjectModelo digital de alturas
dc.subjectLight detection and ranging
dc.subjectLocal maximum
dc.subjectCanopy height model
dc.subjectAirborne laser scanning
dc.titleIdentificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
dc.titleIndividual tree identification in airborne laser data by inverse search window
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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