FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2039768055> ?p ?o ?g. }

• W2039768055 endingPage "65" @default.
• W2039768055 startingPage "57" @default.
• W2039768055 abstract "Multi-method ensembles are generally believed to return more reliable results than the application of one method alone. Here, we test if for the quantification of leaf traits an ensemble of regression models, consisting of Partial Least Squares (PLSR), Random Forest (RFR), and Support Vector Machine regression (SVMR) models, is able to improve the robustness of the spectral band selection process compared to the outcome of a single technique alone. The ensemble approach was tested using one artificial and five measured data sets of leaf level spectra and corresponding information on leaf chlorophyll, dry matter, and water content. PLSR models optimized for the goodness of fit, an established approach for band selection, were used to evaluate the performance of the ensemble. Although the fits of the models within the ensemble were poorer than the fits achieved with the reference approach, the ensemble was able to provide a band selection with higher consistency across all data sets. Due to the selection characteristics of the methods within the ensemble, the ensemble selection is moderately narrow and restrictive but in good agreement with known absorption features published in literature. We conclude that analyzing the range of agreement of different model types is an efficient way to select a robust set of spectral bands related to the foliar properties under investigation. This may help to deepen our understanding of the spectral response of biochemical and biophysical traits in foliage and canopies." @default.
• W2039768055 created "2016-06-24" @default.
• W2039768055 creator A5031087812 @default.
• W2039768055 creator A5033205837 @default.
• W2039768055 creator A5034805489 @default.
• W2039768055 date "2015-07-01" @default.
• W2039768055 modified "2023-10-18" @default.
• W2039768055 title "Multi-method ensemble selection of spectral bands related to leaf biochemistry" @default.
• W2039768055 cites W1964357740 @default.
• W2039768055 cites W1971838942 @default.
• W2039768055 cites W1977084785 @default.
• W2039768055 cites W1985643287 @default.
• W2039768055 cites W1986528915 @default.
• W2039768055 cites W1988233512 @default.
• W2039768055 cites W1988872612 @default.
• W2039768055 cites W1990763503 @default.
• W2039768055 cites W1991668437 @default.
• W2039768055 cites W1995386449 @default.
• W2039768055 cites W1995843625 @default.
• W2039768055 cites W1996601340 @default.
• W2039768055 cites W1999856162 @default.
• W2039768055 cites W2000733812 @default.
• W2039768055 cites W2008190217 @default.
• W2039768055 cites W2008283621 @default.
• W2039768055 cites W2009409575 @default.
• W2039768055 cites W2011221121 @default.
• W2039768055 cites W2014736305 @default.
• W2039768055 cites W2018027183 @default.
• W2039768055 cites W2021467912 @default.
• W2039768055 cites W2022108380 @default.
• W2039768055 cites W2034325283 @default.
• W2039768055 cites W2036003376 @default.
• W2039768055 cites W2036389990 @default.
• W2039768055 cites W2037226761 @default.
• W2039768055 cites W2038412351 @default.
• W2039768055 cites W2041550093 @default.
• W2039768055 cites W2046404820 @default.
• W2039768055 cites W2048651285 @default.
• W2039768055 cites W2051128904 @default.
• W2039768055 cites W2056868695 @default.
• W2039768055 cites W2059697555 @default.
• W2039768055 cites W2062171453 @default.
• W2039768055 cites W2064638681 @default.
• W2039768055 cites W2064818440 @default.
• W2039768055 cites W2066612219 @default.
• W2039768055 cites W2073503722 @default.
• W2039768055 cites W2077439648 @default.
• W2039768055 cites W2083955053 @default.
• W2039768055 cites W2089464686 @default.
• W2039768055 cites W2095649738 @default.
• W2039768055 cites W2098247895 @default.
• W2039768055 cites W2098722265 @default.
• W2039768055 cites W2102273661 @default.
• W2039768055 cites W2107412299 @default.
• W2039768055 cites W2109565719 @default.
• W2039768055 cites W2114091915 @default.
• W2039768055 cites W2118791227 @default.
• W2039768055 cites W2119868411 @default.
• W2039768055 cites W2121208785 @default.
• W2039768055 cites W2123314391 @default.
• W2039768055 cites W2124937378 @default.
• W2039768055 cites W2128458452 @default.
• W2039768055 cites W2142649963 @default.
• W2039768055 cites W2148376635 @default.
• W2039768055 cites W2150853404 @default.
• W2039768055 cites W2155261478 @default.
• W2039768055 cites W2155632266 @default.
• W2039768055 cites W2157559031 @default.
• W2039768055 cites W2159961845 @default.
• W2039768055 cites W2163522904 @default.
• W2039768055 cites W2165916356 @default.
• W2039768055 cites W2166660987 @default.
• W2039768055 cites W2317866228 @default.
• W2039768055 cites W2911964244 @default.
• W2039768055 cites W4211001371 @default.
• W2039768055 cites W4236408562 @default.
• W2039768055 cites W51106753 @default.
• W2039768055 cites W9910819 @default.
• W2039768055 doi "https://doi.org/10.1016/j.rse.2015.03.033" @default.
• W2039768055 hasPublicationYear "2015" @default.
• W2039768055 type Work @default.
• W2039768055 sameAs 2039768055 @default.
• W2039768055 citedByCount "142" @default.
• W2039768055 countsByYear W20397680552015 @default.
• W2039768055 countsByYear W20397680552016 @default.
• W2039768055 countsByYear W20397680552017 @default.
• W2039768055 countsByYear W20397680552018 @default.
• W2039768055 countsByYear W20397680552019 @default.
• W2039768055 countsByYear W20397680552020 @default.
• W2039768055 countsByYear W20397680552021 @default.
• W2039768055 countsByYear W20397680552022 @default.
• W2039768055 countsByYear W20397680552023 @default.
• W2039768055 crossrefType "journal-article" @default.
• W2039768055 hasAuthorship W2039768055A5031087812 @default.
• W2039768055 hasAuthorship W2039768055A5033205837 @default.
• W2039768055 hasAuthorship W2039768055A5034805489 @default.
• W2039768055 hasConcept C104317684 @default.
• W2039768055 hasConcept C105795698 @default.

• next