Comparing parametric and non-parametric methods of predicting Site Index for radiata pine using combinations of data derived from environmental surfaces, satellite imagery and airborne laser scanning
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[1] M. Tomé,et al. Age-independent difference equations for modelling tree and stand growth , 2006 .
[2] A. Hewitt. New Zealand soil classification. , 1993 .
[3] M. Nilsson. Estimation of tree heights and stand volume using an airborne lidar system , 1996 .
[4] D. J. Palmer. Development of national extent terrain attributes (tanz), soil water balance surfaces (swatbal), and environmental surfaces, and their application for spatial modelling of pinus radiata productivity across new zealand , 2008 .
[5] Xiaojun Xu,et al. Estimating Aboveground Carbon of Moso Bamboo Forests Using the k Nearest Neighbors Technique and Satellite Imagery , 2011 .
[6] P. Gong,et al. Isolating individual trees in a savanna woodland using small footprint lidar data , 2006 .
[7] J. Holmgren,et al. Estimation of Tree Height and Stem Volume on Plots Using Airborne Laser Scanning , 2003, Forest Science.
[8] Luca Scrucca,et al. GA: A Package for Genetic Algorithms in R , 2013 .
[9] Yang Chen,et al. Site quality assessment of a Pinus radiata plantation in Victoria, Australia, using LiDAR technology , 2012 .
[10] Jussi Peuhkurinen,et al. Predicting Tree Attributes and Quality Characteristics of Scots Pine Using Airborne Laser Scanning Data , 2009 .
[11] E. Tomppo,et al. Satellite image-based national forest inventory of finland for publication in the igarss'91 digest , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.
[12] Ronald E. McRoberts,et al. Estimating forest attribute parameters for small areas using nearest neighbors techniques , 2012 .
[13] M. Maltamo,et al. ALS-based estimation of plot volume and site index in a eucalyptus plantation with a nonlinear mixed-effect model that accounts for the clone effect , 2011, Annals of Forest Science.
[14] Jerome K. Vanclay,et al. Forest site productivity: a review of the evolution of dendrometric concepts for even-aged stands , 2008 .
[15] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[16] M. Watt,et al. Use of regression kriging to develop a Carbon:Nitrogen ratio surface for New Zealand , 2012 .
[17] Alex Zvoleff,et al. Calculate Textures from Grey-Level Co-Occurrence Matrices(GLCMs) , 2015 .
[18] Ian Ferguson,et al. Campaign and site effects in LiDAR prediction models for site-quality assessment of radiata pine plantations in South Australia , 2010 .
[19] Charles O. Sabatia,et al. Predicting site index of plantation loblolly pine from biophysical variables , 2014 .
[20] Nicholas L. Crookston,et al. yaImpute: An R Package for kNN Imputation , 2008 .
[21] Åsa Persson,et al. Detecting and measuring individual trees using an airborne laser scanner , 2002 .
[22] Randolph H. Wynne,et al. Fusion of Small-Footprint Lidar and Multispectral Data to Estimate Plot- Level Volume and Biomass in Deciduous and Pine Forests in Virginia, USA , 2004, Forest Science.
[23] Michael C. Wimberly,et al. Mapping wildland fuels and forest structure for land management: a comparison of nearest neighbor imputation and other methods , 2009 .
[24] José Cristóbal Riquelme Santos,et al. Evolutionary feature selection to estimate forest stand variables using LiDAR , 2014, Int. J. Appl. Earth Obs. Geoinformation.
[25] Nicholas C. Coops,et al. Assessing forest productivity in Australia and New Zealand using a physiologically-based model driven with averaged monthly weather data and satellite-derived estimates of canopy photosynthetic capacity , 1998 .
[26] M. Kimberley,et al. Comparison of spatial prediction techniques for developing Pinus radiata productivity surfaces across New Zealand , 2009 .
[27] R. Khosla,et al. Influence of climatic conditions, topography and soil attributes on the spatial distribution of site productivity index of the species rich forests of Jalisco, Mexico , 2014, Journal of Forestry Research.
[28] K. Lim,et al. Estimation of above ground forest biomass from airborne discrete return laser scanner data using canopy-based quantile estimators , 2004 .
[29] I. Ozdemir,et al. Estimating stem volume by tree crown area and tree shadow area extracted from pan‐sharpened Quickbird imagery in open Crimean juniper forests , 2008 .
[30] Erkki Tomppo,et al. The k-nearest neighbor technique with local linear regression , 2014 .
[31] B. Muys,et al. Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests , 2010 .
[32] N. Mitchell,et al. The derivation of climate surfaces for New Zealand, and their application to the bioclimatic analysis of the distribution of kauri (Agathis australis) , 1991 .
[33] T. J. Dean,et al. Estimating individual tree leaf area in loblolly pine plantations using LiDAR-derived measurements of height and crown dimensions , 2005 .
[34] J. Hyyppä,et al. Automatic detection of harvested trees and determination of forest growth using airborne laser scanning , 2004 .
[35] Mikko Inkinen,et al. A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners , 2001, IEEE Trans. Geosci. Remote. Sens..
[36] D. Donoghue,et al. Using LiDAR to compare forest height estimates from IKONOS and Landsat ETM+ data in Sitka spruce plantation forests , 2006 .
[37] P. Defourny,et al. Retrieving forest structure variables based on image texture analysis and IKONOS-2 imagery , 2006 .
[38] Michael J. Falkowski,et al. A review of methods for mapping and prediction of inventory attributes for operational forest management , 2014 .
[39] Anne H. Schistad Solberg. Contextual data fusion applied to forest map revision , 1999, IEEE Trans. Geosci. Remote. Sens..
[40] Ali Shamsoddini,et al. Pine plantation structure mapping using WorldView-2 multispectral image , 2013 .
[41] Nicholas C. Coops,et al. Comparison of forest attributes extracted from fine spatial resolution multispectral and lidar data , 2004 .
[42] M. Watt,et al. Use of a process-based model to describe spatial variation in Pinus radiata productivity in New Zealand , 2011 .
[43] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[44] E. Næsset,et al. Estimating tree heights and number of stems in young forest stands using airborne laser scanner data , 2001 .
[45] S. Popescu,et al. A voxel-based lidar method for estimating crown base height for deciduous and pine trees , 2008 .
[46] M. Kimberley,et al. Predicting the spatial distribution of Cupressus lusitanica productivity in New Zealand , 2009 .
[47] D. Lu. Aboveground biomass estimation using Landsat TM data in the Brazilian Amazon , 2005 .
[48] Michael A. Wulder,et al. Modeling Stand Height, Volume, and Biomass from Very High Spatial Resolution Satellite Imagery and Samples of Airborne LiDAR , 2013, Remote. Sens..
[49] I. Burke,et al. Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests , 2005 .
[50] Cédric Véga,et al. Mapping site index and age by linking a time series of canopy height models with growth curves , 2009 .
[51] Sakari Tuominen,et al. Performance of different spectral and textural aerial photograph features in multi-source forest inventory , 2005 .
[52] M. Kimberley,et al. A National height-age model for Pinus radiata in New Zealand , 2013, New Zealand Journal of Forestry Science.
[53] T. Eid,et al. Site index prediction from site and climate variables for Norway spruce and Scots pine in Norway , 2012 .
[54] A. R. Gibson,et al. PREDICTING PINUS RADIATA SITE INDEX FROM ENVIRONMENTAL VARIABLES , 1984 .
[55] F. Parmiggiani,et al. An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters , 1995, IEEE Transactions on Geoscience and Remote Sensing.
[56] R. McRoberts,et al. Remote sensing support for national forest inventories , 2007 .
[57] M. Kimberley,et al. Development of models to predict Pinus radiata productivity throughout New Zealand , 2010 .
[58] Åsa Persson,et al. Identifying species of individual trees using airborne laser scanner , 2004 .
[59] R. Davey. Measurement of trees. , 1942 .