Assessing forest inventory information obtained from different inventory approaches and remote sensing data sources
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Terje Gobakken | Erik Næsset | Hans Ole Ørka | Even Bergseng | E. Næsset | H. Ørka | T. Gobakken | Even Bergseng
[1] 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..
[2] H. Burkhart,et al. A segmented distribution approach for modeling diameter frequency data , 1984 .
[3] E. Næsset,et al. Improving k-nearest neighbor predictions in forest inventories by combining high and low density airborne laser scanning data , 2012 .
[4] J. Hyyppä,et al. DETECTING AND ESTIMATING ATTRIBUTES FOR SINGLE TREES USING LASER SCANNER , 2006 .
[5] Ljusk Ola Eriksson,et al. The Heureka Forestry Decision Support System: An Overview , 2011, Math. Comput. For. Nat. Resour. Sci..
[6] E. Baltsavias,et al. Semi-automatic classification of tree species in different forest ecosystems by spectral and geometric variables derived from Airborne Digital Sensor (ADS40) and RC30 data , 2011 .
[7] L. Bruzzone,et al. Tree species classification in the Southern Alps based on the fusion of very high geometrical resolution multispectral/hyperspectral images and LiDAR data , 2012 .
[8] Alan J. Miller,et al. leaps: Regression Subset Selection. , 2004 .
[9] Tomas Brandtberg,et al. Individual tree-based species classification in high spatial resolution aerial images of forests using fuzzy sets , 2002, Fuzzy Sets Syst..
[10] Michele Dalponte,et al. Tree Species Classification in Boreal Forests With Hyperspectral Data , 2013, IEEE Transactions on Geoscience and Remote Sensing.
[11] Michael L. Clutter,et al. The value of timber inventory information for management planning , 2008 .
[12] Jussi Peuhkurinen,et al. Comparing individual tree detection and the area-based statistical approach for the retrieval of forest stand characteristics using airborne laser scanning in Scots pine stands , 2011 .
[13] E. Næsset,et al. Laser scanning of forest resources: the nordic experience , 2004 .
[14] Jussi Peuhkurinen,et al. Airborne Laser Scanning for the Site Type Identification of Mature Boreal Forest Stands , 2011, Remote. Sens..
[15] Terje Gobakken,et al. Estimation of diameter and basal area distributions in coniferous forest by means of airborne laser scanner data , 2004 .
[16] Michael E. Ketzenberg,et al. A framework for the value of information in inventory replenishment , 2007, Eur. J. Oper. Res..
[17] E. Næsset. Practical large-scale forest stand inventory using a small-footprint airborne scanning laser , 2004 .
[18] Anssi Ahtikoski,et al. Applying the MOTTI simulator to analyse the effects of alternative management schedules on timber and non-timber production , 2005 .
[19] E. Næsset,et al. Single Tree Segmentation Using Airborne Laser Scanner Data in a Structurally Heterogeneous Spruce Forest , 2006 .
[20] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[21] S. Roberts,et al. Influence of Fusing Lidar and Multispectral Imagery on Remotely Sensed Estimates of Stand Density and Mean Tree Height in a Managed Loblolly Pine Plantation , 2003, Forest Science.
[22] E. Næsset. Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data , 2002 .
[23] Tron Eid,et al. Use of uncertain inventory data in forestry scenario models and consequential incorrect harvest decisions. , 2000 .
[24] Annika Kangas,et al. Correlations, distributions, and trends in forest inventory errors and their effects on forest planning , 2010 .
[25] Juha Hyyppä,et al. An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning , 2012, Remote. Sens..
[26] Liviu Theodor Ene,et al. Single tree detection in heterogeneous boreal forests using airborne laser scanning and area-based stem number estimates , 2012 .
[27] J. Holmgren,et al. Estimation of tree lists from airborne laser scanning data using a combination of analysis on single tree and raster cell level. , 2008 .
[28] H. Pretzscha,et al. The single tree-based stand simulator SILVA : construction , application and evaluation , 2002 .
[29] M. Maltamo,et al. A Two Stage Method to Estimate Species-specific Growing Stock , 2009 .
[30] Michele Dalponte,et al. Characterizing forest species composition using multiple remote sensing data sources and inventory approaches , 2013 .
[31] M. Maltamo,et al. Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics , 2010 .
[32] Petteri Packalen,et al. Improving species-specific plot volume estimates based on airborne laser scanning and image data using alpha shape metrics and balanced field data , 2012 .
[33] Terje Gobakken,et al. T: A forest simulator for bioeconomic analyses based on models for individual trees , 2008 .
[34] Annika Susanna Kangas,et al. Value of forest information , 2010, European Journal of Forest Research.
[35] W. Walker,et al. Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy , 2006 .
[36] Göran Ståhl,et al. Model-assisted regional forest biomass estimation using LiDAR and InSAR as auxiliary data: A case study from a boreal forest area , 2011 .
[37] Mary Ann Fajvan,et al. A Comparison of Multispectral and Multitemporal Information in High Spatial Resolution Imagery for Classification of Individual Tree Species in a Temperate Hardwood Forest , 2001 .
[38] Liviu Theodor Ene,et al. Simultaneously acquired airborne laser scanning and multispectral imagery for individual tree species identification , 2012 .
[39] James W. Flewelling. Forest inventory predictions from individual tree crowns: regression modeling within a sample framework , 2009 .
[40] Annika Kangas,et al. Sensitivity of Harvest Decisions to Errors in Stand Characteristics , 2011 .
[41] E. Næsset,et al. Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data , 2010 .
[42] G. Ståhl,et al. Cost-Plus-Loss Analyses of Forest Inventory Strategies Based on kNN- Assigned Reference Sample Plot Data , 2003 .
[43] E. Mønness. Diameter distributions and height curves in even-aged stands of Pinus Sylvestris L. , 1982 .
[44] Erik Næsset,et al. Estimating percentile-based diameter distributions in uneven-sized Norway spruce stands using airborne laser scanner data , 2007 .
[45] J. W. Flewelling,et al. Probability models for individually segmented tree crown images in a sampling context. , 2008 .
[46] Erik Næsset,et al. Advances and emerging issues in national forest inventories , 2010 .
[47] Juha Hyyppä,et al. Comparing thr accuracy of laser scanner with other optical remote sensing data sources for stand attributes retrieval , 2000 .
[48] A. Haara,et al. Tree Species Classification using Semi-automatic Delineation of Trees on Aerial Images , 2002 .
[49] Alexandre Carleer,et al. Exploitation of Very High Resolution Satellite Data for Tree Species Identification , 2004 .
[50] Åsa Persson,et al. Detecting and measuring individual trees using an airborne laser scanner , 2002 .
[51] Erik Næsset,et al. Effects of different sensors and leaf-on and leaf-off canopy conditions on echo distributions and individual tree properties derived from airborne laser scanning , 2010 .
[52] E. Næsset. Airborne laser scanning as a method in operational forest inventory: Status of accuracy assessments accomplished in Scandinavia , 2007 .
[53] E. Næsset,et al. Classifying species of individual trees by intensity and structure features derived from airborne laser scanner data , 2009 .
[54] Ross A. Hill,et al. Mapping woodland species composition and structure using airborne spectral and LiDAR data , 2005 .
[55] Liviu Theodor Ene,et al. Comparative testing of single-tree detection algorithms under different types of forest , 2011 .
[56] Chao Chen,et al. Using Random Forest to Learn Imbalanced Data , 2004 .
[57] R. Bailey,et al. Percentile-Based Distributions Characterize Forest Stand Tables , 1987, Forest Science.
[58] E. Næsset,et al. Weibull and percentile models for lidar-based estimation of basal area distribution , 2005 .
[59] J. Hyyppä,et al. Tree species classification using airborne LiDAR - effects of stand and tree parameters, downsizing of training set, intensity normalization, and sensor type , 2010 .
[60] Åsa Persson,et al. Species identification of individual trees by combining high resolution LiDAR data with multi‐spectral images , 2008 .
[61] Terje Gobakken,et al. Comparing stand inventories for large areas based on photo-interpretation and laser scanning by means of cost-plus-loss analyses , 2004 .