Optimizing the k-Nearest Neighbors technique for estimating forest aboveground biomass using airborne laser scanning data

[1]  Robert L. Wolpert,et al.  Statistical Inference , 2019, Encyclopedia of Social Network Analysis and Mining.

[2]  M. Gregory,et al.  Scale considerations for integrating forest inventory plot data and satellite image data for regional forest mapping , 2014 .

[3]  Ronald E. McRoberts,et al.  Effects of uncertainty in model predictions of individual tree volume on large area volume estimates , 2014 .

[4]  Juha Hyyppä,et al.  Retrieval of Forest Aboveground Biomass and Stem Volume with Airborne Scanning LiDAR , 2013, Remote. Sens..

[5]  Terje Gobakken,et al.  Inference for lidar-assisted estimation of forest growing stock volume , 2013 .

[6]  Ronald E. McRoberts,et al.  Estimating forest attribute parameters for small areas using nearest neighbors techniques , 2012 .

[7]  E. Næsset,et al.  Improving k-nearest neighbor predictions in forest inventories by combining high and low density airborne laser scanning data , 2012 .

[8]  Gherardo Chirici,et al.  Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data , 2011 .

[9]  Ronald E. McRoberts,et al.  Satellite image-based maps: Scientific inference or pretty pictures? , 2011 .

[10]  Juha Hyyppä,et al.  Comparing Accuracy of Airborne Laser Scanning and TerraSAR-X Radar Images in the Estimation of Plot-Level Forest Variables , 2010, Remote. Sens..

[11]  Nicholas L. Crookston,et al.  The roles of nearest neighbor methods in imputing missing data in forest inventory and monitoring databases , 2009 .

[12]  Ronald E. McRoberts,et al.  Diagnostic tools for nearest neighbors techniques when used with satellite imagery , 2009 .

[13]  S. Magnussen,et al.  Model-based mean square error estimators for k-nearest neighbour predictions and applications using remotely sensed data for forest inventories , 2009 .

[14]  Ronald E. McRoberts,et al.  Predicting categorical forest variables using an improved k-Nearest Neighbour estimator and Landsat imagery , 2009 .

[15]  Piermaria Corona,et al.  Design-based approach to k-nearest neighbours technique for coupling field and remotely sensed data in forest surveys , 2009 .

[16]  R. McRoberts.  Using satellite imagery and the k-nearest neighbors technique as a bridge between strategic and management forest inventories , 2008 .

[17]  Terje Gobakken,et al.  Assessing effects of laser point density, ground sampling intensity, and field sample plot size on biophysical stand properties derived from airborne laser scanner data , 2008 .

[18]  J. Heikkinen,et al.  Estimating areal means and variances of forest attributes using the k-Nearest Neighbors technique and satellite imagery , 2007 .

[19]  R. McRoberts.  A model-based approach to estimating forest area , 2006 .

[20]  Hailemariam Temesgen,et al.  Comparison of Nearest Neighbor Methods for Estimating Basal Area and Stems per Hectare Using Aerial Auxiliary Variables , 2005, Forest Science.

[21]  Erkki Tomppo,et al.  Using coarse scale forest variables as ancillary information and weighting of variables in k-NN estimation: a genetic algorithm approach , 2004 .

[22]  Ronald E. McRoberts,et al.  Stratified estimation of forest area using satellite imagery, inventory data, and the k-Nearest Neighbors technique , 2002 .

[23]  Janet L. Ohmann,et al.  Predictive mapping of forest composition and structure with direct gradient analysis and nearest- neighbor imputation in coastal Oregon, U.S.A. , 2002 .

[24]  Jonathan Goldstein,et al.  When Is ''Nearest Neighbor'' Meaningful? , 1999, ICDT.

[25]  Pat Langley,et al.  Selection of Relevant Features and Examples in Machine Learning , 1997, Artif. Intell..

[26]  Carl-Erik Särndal,et al.  Model Assisted Survey Sampling , 1997 .

[27]  Albert R. Stage,et al.  Most Similar Neighbor: An Improved Sampling Inference Procedure for Natural Resource Planning , 1995, Forest Science.

[28]  R. Tibshirani,et al.  An Introduction to the Bootstrap , 1995 .

[29]  Richard Anderson-Sprecher,et al.  Model Comparisons and R 2 , 1994 .

[30]  P. Langley,et al.  Average-case analysis of a nearest neighbor algorthim , 1993, IJCAI 1993.

[31]  Lloyd S. Nelson,et al.  A Dictionary of Statistical Terms, 5th Ed. , 1991 .

[32]  John Price-Wilkin,et al.  Oxford English Dictionary (2nd ed.) , 1991 .

[33]  M. H. Hansen.  An Evaluation of Model-Dependent and Probability-Sampling Inferences in Sample Surveys , 1983 .

[34]  A. Wepster,et al.  European Cooperation in Science and Technology , 1981, Journal of Navigation.

[35]  M. R. Mickey,et al.  Estimation of Error Rates in Discriminant Analysis , 1968 .

[36]  Boyd Harshbarger,et al.  Statistical Inference I. , 1964 .

[37]  Richard Bellman,et al.  Adaptive Control Processes: A Guided Tour , 1961, The Mathematical Gazette.

[38]  W. R. Buckland,et al.  A dictionary of statistical terms , 1958 .

[39]  Piermaria Corona,et al.  Design-based diagnostics for k-NN estimators of forest resourcesThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time. , 2011 .

[40]  Shuangzhe Liu,et al.  Regression diagnostics , 2020, Applied Quantitative Analysis for Real Estate.

[41]  Eamonn J. Keogh.  Nearest Neighbor , 2010, Encyclopedia of Machine Learning.

[42]  E. Tomppo.  National Forest Inventories : pathways for common reporting , 2010 .

[43]  M. Kenward,et al.  An Introduction to the Bootstrap , 2007 .

[44]  M. Pontil.  Leave-one-out error and stability of learning algorithms with applications , 2002 .

[45]  Pat Langley,et al.  Average-Case Analysis of a Nearest Neighbor Algorithm , 1993, IJCAI.

[46]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[47]  J. Simpson,et al.  The Oxford English Dictionary , 1884 .