Matches in SemOpenAlex for { <https://semopenalex.org/work/W2015280663> ?p ?o ?g. }
- W2015280663 endingPage "678" @default.
- W2015280663 startingPage "665" @default.
- W2015280663 abstract "Airborne small-footprint LiDAR is replacing field measurements in regional-level forest inventories, but auxiliary fieldwork is still required for the optimal management of young stands. Waveform (WF) -recording sensors can provide a more detailed description of the vegetation than discrete return (DR) systems through accurate characterization of the backscattered signal. Furthermore, knowing the signal shape facilitates comparisons between real data and those obtained with simulation tools. We performed calibration and quantitative validation of a Monte Carlo ray tracing (MCRT) -based LiDAR simulator against real data, and used simulations and real data to study small-footprint WF-recording LiDAR for the classification of juvenile boreal forest vegetation. The simulations were based on geometric-optical models of three species: birch ( Betula pendula Roth), raspberry ( Rubus idaeus L.), and fireweed ( Chamerion angustifolium (L.) Holub). Simulated WF features were in good agreement with the real data (differences of − 19% to 11% in radiometric features, − 0.23 m to 0.45 m in mean height), and relative interspecies differences were preserved. We used simulated data to study the effects of sensor parameters on the classification among the three species. An increase in footprint size improved the classification accuracy up to 0.30–0.36 m in diameter, while the emitted pulse width and the WF sampling rate showed minor effects. Finally, we used real data to classify four silviculturally important vegetation functional groups (conifers, broad-leaved trees, low vegetation (green), low vegetation (barren) + abiotic material). Classification accuracies of 68.1–86.7% (kappa 0.50–0.80) showed slight improvement compared with existing studies on DR LiDAR and passive optical data. The results of simulator validation serve as a basis for the future use of simulation models, e.g. in LiDAR survey planning or in the simulation of synthetic training data, while the other findings clarify the potential of small-footprint WF data for characterizing vegetation in intensively managed forest stands at seedling and sapling stages in the boreal region. • Calibration of a Monte Carlo ray tracing LiDAR simulator with reference targets. • Quantitative comparison of simulated waveforms against real in several acquisitions. • Simulated effects of sensor parameters on vegetation classification accuracy. • Real data analysis of waveform features for classification." @default.
- W2015280663 created "2016-06-24" @default.
- W2015280663 creator A5006010089 @default.
- W2015280663 creator A5016914950 @default.
- W2015280663 date "2014-01-01" @default.
- W2015280663 modified "2023-09-29" @default.
- W2015280663 title "Real and simulated waveform-recording LiDAR data in juvenile boreal forest vegetation" @default.
- W2015280663 cites W1965597456 @default.
- W2015280663 cites W1969607685 @default.
- W2015280663 cites W1976624114 @default.
- W2015280663 cites W1977428739 @default.
- W2015280663 cites W1983142039 @default.
- W2015280663 cites W1987610258 @default.
- W2015280663 cites W1991576283 @default.
- W2015280663 cites W1995869471 @default.
- W2015280663 cites W1996263757 @default.
- W2015280663 cites W1998846529 @default.
- W2015280663 cites W2004453108 @default.
- W2015280663 cites W2004729818 @default.
- W2015280663 cites W2018746476 @default.
- W2015280663 cites W2020860387 @default.
- W2015280663 cites W2025401351 @default.
- W2015280663 cites W2025478789 @default.
- W2015280663 cites W2028413465 @default.
- W2015280663 cites W2029319256 @default.
- W2015280663 cites W2031419936 @default.
- W2015280663 cites W2033908379 @default.
- W2015280663 cites W2034009752 @default.
- W2015280663 cites W2039998113 @default.
- W2015280663 cites W2048017101 @default.
- W2015280663 cites W2053373080 @default.
- W2015280663 cites W2053579473 @default.
- W2015280663 cites W2054440081 @default.
- W2015280663 cites W2058214432 @default.
- W2015280663 cites W2059495078 @default.
- W2015280663 cites W2062983247 @default.
- W2015280663 cites W2071695248 @default.
- W2015280663 cites W2074706991 @default.
- W2015280663 cites W2080157231 @default.
- W2015280663 cites W2082750454 @default.
- W2015280663 cites W2088783667 @default.
- W2015280663 cites W2094605604 @default.
- W2015280663 cites W2097337758 @default.
- W2015280663 cites W2097688980 @default.
- W2015280663 cites W2101365296 @default.
- W2015280663 cites W2106488983 @default.
- W2015280663 cites W2111672757 @default.
- W2015280663 cites W2113748593 @default.
- W2015280663 cites W2119232332 @default.
- W2015280663 cites W2128135560 @default.
- W2015280663 cites W2138060511 @default.
- W2015280663 cites W2138624212 @default.
- W2015280663 cites W2143680202 @default.
- W2015280663 cites W2150279355 @default.
- W2015280663 cites W2151843635 @default.
- W2015280663 cites W2153555508 @default.
- W2015280663 cites W2162832400 @default.
- W2015280663 cites W2167248655 @default.
- W2015280663 cites W2170591795 @default.
- W2015280663 cites W2330739253 @default.
- W2015280663 cites W3085118739 @default.
- W2015280663 doi "https://doi.org/10.1016/j.rse.2013.10.003" @default.
- W2015280663 hasPublicationYear "2014" @default.
- W2015280663 type Work @default.
- W2015280663 sameAs 2015280663 @default.
- W2015280663 citedByCount "26" @default.
- W2015280663 countsByYear W20152806632015 @default.
- W2015280663 countsByYear W20152806632016 @default.
- W2015280663 countsByYear W20152806632017 @default.
- W2015280663 countsByYear W20152806632018 @default.
- W2015280663 countsByYear W20152806632019 @default.
- W2015280663 countsByYear W20152806632020 @default.
- W2015280663 countsByYear W20152806632021 @default.
- W2015280663 countsByYear W20152806632022 @default.
- W2015280663 countsByYear W20152806632023 @default.
- W2015280663 crossrefType "journal-article" @default.
- W2015280663 hasAuthorship W2015280663A5006010089 @default.
- W2015280663 hasAuthorship W2015280663A5016914950 @default.
- W2015280663 hasConcept C105795698 @default.
- W2015280663 hasConcept C142724271 @default.
- W2015280663 hasConcept C165838908 @default.
- W2015280663 hasConcept C205649164 @default.
- W2015280663 hasConcept C2776133958 @default.
- W2015280663 hasConcept C33923547 @default.
- W2015280663 hasConcept C39432304 @default.
- W2015280663 hasConcept C51399673 @default.
- W2015280663 hasConcept C62649853 @default.
- W2015280663 hasConcept C71924100 @default.
- W2015280663 hasConcept C87621631 @default.
- W2015280663 hasConcept C97137747 @default.
- W2015280663 hasConceptScore W2015280663C105795698 @default.
- W2015280663 hasConceptScore W2015280663C142724271 @default.
- W2015280663 hasConceptScore W2015280663C165838908 @default.
- W2015280663 hasConceptScore W2015280663C205649164 @default.
- W2015280663 hasConceptScore W2015280663C2776133958 @default.
- W2015280663 hasConceptScore W2015280663C33923547 @default.
- W2015280663 hasConceptScore W2015280663C39432304 @default.
- W2015280663 hasConceptScore W2015280663C51399673 @default.