Assessing lean and positional error of individual mature Douglas-fir (Pseudotsuga menziesii) trees using active and passive sensors
暂无分享,去创建一个
[1] Peter E. Hart,et al. Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.
[2] Paul J. Besl,et al. Method for registration of 3-D shapes , 1992, Other Conferences.
[3] Tomas Brandtberg. Automatic individual tree based analysis of high spatial resolution aerial images on naturally regenerated boreal forests , 1999 .
[4] Juha M. Hyyppae,et al. Assessment of forest attributes and single-tree segmentation by means of laser scanning , 2000, Defense, Security, and Sensing.
[5] 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..
[6] Chengcui Zhang,et al. A progressive morphological filter for removing nonground measurements from airborne LIDAR data , 2003, IEEE Trans. Geosci. Remote. Sens..
[7] W. W. Carson,et al. Accuracy of a high-resolution lidar terrain model under a conifer forest canopy , 2003 .
[8] D. A. Hill,et al. Combined high-density lidar and multispectral imagery for individual tree crown analysis , 2003 .
[9] N. Pfeifer,et al. Three-dimensional reconstruction of stems for assessment of taper, sweep and lean based on laser scanning of standing trees , 2004 .
[10] S. Popescu,et al. Seeing the Trees in the Forest: Using Lidar and Multispectral Data Fusion with Local Filtering and Variable Window Size for Estimating Tree Height , 2004 .
[11] Takeo Kanade,et al. Shape and motion from image streams under orthography: a factorization method , 1992, International Journal of Computer Vision.
[12] S. Reutebuch,et al. A rigorous assessment of tree height measurements obtained using airborne lidar and conventional field methods , 2006 .
[13] P. Radtke,et al. Detailed Stem Measurements of Standing Trees from Ground-Based Scanning Lidar , 2006, Forest Science.
[14] P. Marshall,et al. Effects of forest roads on the growth of adjacent lodgepole pine trees , 2006 .
[15] Yi Lin,et al. A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements , 2010 .
[16] Yi Lin,et al. Mini-UAV-Borne LIDAR for Fine-Scale Mapping , 2011, IEEE Geoscience and Remote Sensing Letters.
[17] Wang Tao,et al. Dense point cloud extraction from UAV captured images in forest area , 2011, Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services.
[18] A. J. Rossi,et al. Abstracted workflow framework with a structure from motion application , 2012, 2012 Western New York Image Processing Workshop.
[19] Juha Hyyppä,et al. An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning , 2012, Remote. Sens..
[20] Arko Lucieer,et al. Development of a UAV-LiDAR System with Application to Forest Inventory , 2012, Remote. Sens..
[21] Maggi Kelly,et al. A New Method for Segmenting Individual Trees from the Lidar Point Cloud , 2012 .
[22] M. Westoby,et al. ‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications , 2012 .
[23] Juha Hyyppä,et al. Tree mapping using airborne, terrestrial and mobile laser scanning – A case study in a heterogeneous urban forest , 2013 .
[24] Jinqiang Cui,et al. UAV LiDAR for below-canopy forest surveys , 2013 .
[25] M. Pierrot-Deseilligny,et al. A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery , 2013 .
[26] Wenkai Li,et al. Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches , 2013, Remote. Sens..
[27] B. Koch,et al. UAV-BASED PHOTOGRAMMETRIC POINT CLOUDS – TREE STEM MAPPING IN OPEN STANDS IN COMPARISON TO TERRESTRIAL LASER SCANNER POINT CLOUDS , 2013 .
[28] Arko Lucieer,et al. Direct Georeferencing of Ultrahigh-Resolution UAV Imagery , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[29] Jordan Miller. Estimation of individual tree metrics using structure-from-motion photogrammetry. , 2015 .
[30] M. Holopainen,et al. SLAM-Aided Stem Mapping for Forest Inventory with Small-Footprint Mobile LiDAR , 2015 .
[31] L. Wallace,et al. Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (SfM) Point Clouds , 2016 .
[32] Wuming Zhang,et al. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation , 2016, Remote. Sens..
[33] Sébastien Bauwens,et al. Forest Inventory with Terrestrial LiDAR: A Comparison of Static and Hand-Held Mobile Laser Scanning , 2016 .
[34] A. R. Proto,et al. Forest and UAV: a bibliometric review , 2016 .
[35] Niclas Börlin,et al. Estimation of Tree Stem Attributes Using Terrestrial Photogrammetry with a Camera Rig , 2016 .
[36] Michele Dalponte,et al. Tree‐centric mapping of forest carbon density from airborne laser scanning and hyperspectral data , 2016, Methods in ecology and evolution.
[37] C. Silva,et al. Imputation of Individual Longleaf Pine (Pinus palustris Mill.) Tree Attributes from Field and LiDAR Data , 2016 .
[38] Hamid Hamraz,et al. Vertical stratification of forest canopy for segmentation of understory trees within small-footprint airborne LiDAR point clouds , 2016, 1701.00169.
[39] Pablo Rodríguez-Gonzálvez,et al. Automatic tree parameter extraction by a Mobile LiDAR System in an urban context , 2018, PloS one.
[40] David A. Coomes,et al. Accurate Measurement of Tropical Forest Canopy Heights and Aboveground Carbon Using Structure From Motion , 2019, Remote. Sens..
[41] John Sessions,et al. Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices , 2019, Remote. Sens..
[42] Farid Kendoul,et al. Modelling the effects of fundamental UAV flight parameters on LiDAR point clouds to facilitate objectives-based planning , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.
[43] R. Irizarry. ggplot2 , 2019, Introduction to Data Science.
[44] Wen Xiao,et al. INDIVIDUAL TREE DETECTION FROM UAV LIDAR DATA IN A MIXED SPECIES WOODLAND , 2019, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.