000069988 001__ 69988
000069988 005__ 20210301081639.0
000069988 0247_ $$2doi$$a10.3390/f9040158
000069988 0248_ $$2sideral$$a105439
000069988 037__ $$aART-2018-105439
000069988 041__ $$aeng
000069988 100__ $$0(orcid)0000-0002-8362-7559$$aDomingo, D.$$uUniversidad de Zaragoza
000069988 245__ $$aEstimation of total biomass in Aleppo pine forest stands applying parametric and nonparametric methods to low-density airborne laser scanning data
000069988 260__ $$c2018
000069988 5060_ $$aAccess copy available to the general public$$fUnrestricted
000069988 5203_ $$aThe account of total biomass can assist with the evaluation of climate regulation policies from local to global scales. This study estimates total biomass (TB), including tree and shrub biomass fractions, in Pinus halepensis Miller forest stands located in the Aragon Region (Spain) using Airborne Laser Scanning (ALS) data and fieldwork. A comparison of five selection methods and five regression models was performed to relate the TB, estimated in 83 field plots through allometric equations, to several independent variables extracted from ALS point cloud. A height threshold was used to include returns above 0.2 m when calculating ALS variables. The sample was divided into training and test sets composed of 62 and 21 plots, respectively. The model with the lower root mean square error (15.14 tons/ha) after validation was the multiple linear regression model including three ALS variables: the 25th percentile of the return heights, the variance, and the percentage of first returns above the mean. This study confirms the usefulness of low-density ALS data to accurately estimate total biomass, and thus better assess the availability of biomass and carbon content in a Mediterranean Aleppo pine forest.
000069988 536__ $$9info:eu-repo/grantAgreement/ES/MEC/FPU14-06250$$9info:eu-repo/grantAgreement/ES/MINECO/CGL2014-57013-C2-2-R
000069988 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000069988 590__ $$a2.116$$b2018
000069988 591__ $$aFORESTRY$$b17 / 67 = 0.254$$c2018$$dQ2$$eT1
000069988 592__ $$a0.734$$b2018
000069988 593__ $$aForestry$$c2018$$dQ1
000069988 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000069988 700__ $$0(orcid)0000-0002-8954-7517$$aLamelas, M.T.
000069988 700__ $$0(orcid)0000-0001-6288-2780$$aMontealegre, A.L.$$uUniversidad de Zaragoza
000069988 700__ $$0(orcid)0000-0003-2610-7749$$aGarcía-Martín, A.
000069988 700__ $$0(orcid)0000-0003-2615-270X$$ade la Riva, J.$$uUniversidad de Zaragoza
000069988 7102_ $$13006$$2010$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Análisis Geográfico Regi.
000069988 773__ $$g9, 4 (2018), 158 [17 pp]$$pForests$$tFORESTS$$x1999-4907
000069988 8564_ $$s1386695$$uhttps://zaguan.unizar.es/record/69988/files/texto_completo.pdf$$yVersión publicada
000069988 8564_ $$s101864$$uhttps://zaguan.unizar.es/record/69988/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000069988 909CO $$ooai:zaguan.unizar.es:69988$$particulos$$pdriver
000069988 951__ $$a2021-03-01-08:01:18
000069988 980__ $$aARTICLE