Anderson Jeanne, Martin M.E., Smith M-L., Dubayah R.O., Hofton M.A., Hyde P., Peterson B.E., Blair J.B., Knox R.G. (2006): The use of waveform lidar to measure northern temperate mixed conifer and deciduous forest structure in New Hampshire. Remote Sensing of Environment, 105, 248-261  https://doi.org/10.1016/j.rse.2006.07.001 Avery T.E., Burkhart H. (1994): Forest Measurements. 4th Ed. Boston, McGraw-Hill: 407. Belsley D. (1991): Conditioning Diagnostics: Collinearity and Weak Data in Regression. New York, John Wiley & Sons: 396.Frazer G.W., Magnussen S., Wulder M.A., Niemann K.O. (2011): Simulated impact of sample plot size and co-registration error on the accuracy and uncertainty of LiDAR-derived estimates of forest stand biomass. Remote Sensing of Environment, 115, 636-649  https://doi.org/10.1016/j.rse.2010.10.008Garcia-Gutierrez Jorge, Gonzalez-Ferreiro Eduardo, Riquelme-Santos Jose C., Miranda David, Dieguez-Aranda Ulises, Navarro-Cerrillo Rafael M. (2014): Evolutionary feature selection to estimate forest stand variables using LiDAR. International Journal of Applied Earth Observation and Geoinformation, 26, 119-131  https://doi.org/10.1016/j.jag.2013.06.005Gobakken Terje, Næsset Erik (2008): Assessing effects of laser point density, ground sampling intensity, and field sample plot size on biophysical stand properties derived from airborne laser scanner data. Canadian Journal of Forest Research, 38, 1095-1109  https://doi.org/10.1139/X07-219Gonzalez-Ferreiro E., Dieguez-Aranda U., Miranda D. (): Estimation of stand variables in Pinus radiata D. Don plantations using different LiDAR pulse densities. Forestry, 85, 281-292  https://doi.org/10.1093/forestry/cps002González-Ferreiro Eduardo, Diéguez-Aranda Ulises, Barreiro-Fernández Laura, Buján Sandra, Barbosa Miguel, Suárez Juan C., Bye Iain J., Miranda David (2013): A mixed pixel- and region-based approach for using airborne laser scanning data for individual tree crown delineation in Pinus radiata D. Don plantations. International Journal of Remote Sensing, 34, 7671-7690  https://doi.org/10.1080/01431161.2013.823523Hernández-Clemente Rocío, Navarro-Cerrillo Rafael M., Suárez Lola, Morales Fermín, Zarco-Tejada Pablo J. (2011): Assessing structural effects on PRI for stress detection in conifer forests. Remote Sensing of Environment, 115, 2360-2375  https://doi.org/10.1016/j.rse.2011.04.036Latifi H., Nothdurft A., Koch B. (): Non-parametric prediction and mapping of standing timber volume and biomass in a temperate forest: application of multiple optical/LiDAR-derived predictors. Forestry, 83, 395-407  https://doi.org/10.1093/forestry/cpq022 Li Y., Andersen H.E., McGaughey R. (2008): A comparison of statistical methods for estimating forest biomass from light detection and ranging data. Western Journal of Applied Forestry, 23: 223–231.Maltamo M (2004): Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions. Remote Sensing of Environment, 90, 319-330  https://doi.org/10.1016/j.rse.2004.01.006 Mauro F., Valbuena R., García A., Manzanera J. (2009): GPS admissible errors in positioning inventory plots for forest structure studies. Available at http://skog.for.msu.edu/meeting/proc2/Mauro_Valbuena_Garcia_Manzanera.pdf McGaughey R. (2009): FUSION/LDV: Software for LIDAR Data Analysis and Visualization. Seattle, USDA Forest Service, Pacific Northwest Research Station: 182. Means J., Acker S., Fitt B., Renslow M., Emerson L. (2000): Predicting forest stand characteristics with airborne scanning LIDAR. Photogrammetric Engineering and Remote Sensing, 66: 1367–1371.Næsset Erik (2002): Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sensing of Environment, 80, 88-99  https://doi.org/10.1016/S0034-4257(01)00290-5Næsset Erik (2004): Accuracy of forest inventory using airborne laser scanning: evaluating the first nordic full-scale operational project. Scandinavian Journal of Forest Research, 19, 554-557  https://doi.org/10.1080/02827580410019544Navarro-Cerrillo Rafael Mª, Trujillo Jesus, de la Orden Manuel Sánchez, Hernández-Clemente Rocío (2014): Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation. International Journal of Applied Earth Observation and Geoinformation, 26, 88-96  https://doi.org/10.1016/j.jag.2013.06.001Nelson Ross, Short Austin, Valenti Michael (2004): Measuring biomass and carbon in delaware using an airborne profiling LIDAR. Scandinavian Journal of Forest Research, 19, 500-511  https://doi.org/10.1080/02827580410019508Renner Gábor, Ekárt Anikó (2003): Genetic algorithms in computer aided design. Computer-Aided Design, 35, 709-726  https://doi.org/10.1016/S0010-4485(03)00003-4Ruiz-Peinado Ricardo, Del Rio Miren, Montero Gregorio (2011): New models for estimating the carbon sink capacity of Spanish softwood species. Forest Systems, 20, 176-  https://doi.org/10.5424/fs/2011201-11643Schwarz Gideon (1978): Estimating the Dimension of a Model. The Annals of Statistics, 6, 461-464  https://doi.org/10.1214/aos/1176344136 Stevens J. (2002): Applied Multivariate Statistics for the Social Sciences. Hillsdale, Lawrence Erlbaum Associates, Inc.: 699.Sun Guoqing, Ranson K. Jon, Guo Z., Zhang Z., Montesano P., Kimes D. (2011): Forest biomass mapping from lidar and radar synergies. Remote Sensing of Environment, 115, 2906-2916  https://doi.org/10.1016/j.rse.2011.03.021 Whittingham M.J., Stephens P.A., Bradbury R.B., Freckleton R. (2006): Why do we still use stepwise modelling in ecology and behaviour? Journal of Animal Ecology, 75: 1182–1189.Zenner Eric K. (2005): Investigating scale-dependent stand heterogeneity with structure-area-curves. Forest Ecology and Management, 209, 87-100  https://doi.org/10.1016/j.foreco.2005.01.004Zhao Kaiguang, Popescu Sorin (2009): Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA. Remote Sensing of Environment, 113, 1628-1645  https://doi.org/10.1016/j.rse.2009.03.006