Measurement of volume and accuracy analysis of standing trees using Forest Survey Intelligent Dendrometer
暂无分享,去创建一个
Zhiming Wang | Guangpeng Fan | Wenxin Feng | Feixiang Chen | Danyu Chen | Yanqi Dong | Guangpeng Fan | Feixiang Chen | Yanqi Dong | Zhiming Wang | Danyu Chen | Wenxin Feng
[1] Jari Vauhkonen,et al. Geometrically explicit description of forest canopy based on 3D triangulations of airborne laser scanning data , 2016 .
[2] Niclas Börlin,et al. Bias of cylinder diameter estimation from ground-based laser scanners with different beam widths: A simulation study , 2018 .
[3] M. Fabrika,et al. Terrestrial single-photogrammetry for measuring standing trees, as applied in the Dobroc virgin forest , 2001 .
[4] P. Surový,et al. Forest Stand Inventory Based on Combined Aerial and Terrestrial Close-Range Photogrammetry , 2016 .
[5] Francesca Giannetti,et al. Comparing Three Different Ground Based Laser Scanning Methods for Tree Stem Detection , 2018, Remote. Sens..
[6] Steen Magnussen,et al. Lidar supported estimators of wood volume and aboveground biomass from the Danish national forest inventory (2012–2016) , 2018, Remote Sensing of Environment.
[7] Feng Zhongke,et al. Error analysis of measuring diameter at breast height and tree height and volume of standing tree by total station , 2016 .
[8] Lauri Mehtätalo,et al. Stand density estimators based on individual tree detection and stochastic geometry , 2016 .
[9] Philippe Giguère,et al. Mapping forests using an unmanned ground vehicle with 3D LiDAR and graph-SLAM , 2018, Comput. Electron. Agric..
[10] Roberto Pilli,et al. Wrong premises mislead the conclusions by Kallio et al. on forest reference levels in the EU , 2018, Forest Policy and Economics.
[11] Harold E. Burkhart,et al. Eucalyptus growth and yield system: Linking individual-tree and stand-level growth models in clonal Eucalypt plantations in Brazil , 2019, Forest Ecology and Management.
[12] Julián Tomaštík,et al. High Precision Individual Tree Diameter and Perimeter Estimation from Close-Range Photogrammetry , 2018, Forests.
[13] Zhang Ming-tie. Study on Volume Measurement of Single Trees , 2004 .
[14] Annika Kangas,et al. A Mobile Phone Application for the Collection of Opinion Data for Forest Planning Purposes , 2015, Environmental Management.
[15] C. Fraser,et al. Sensor modelling and camera calibration for close-range photogrammetry , 2016 .
[16] Tian Wang,et al. Classification of tree species and stock volume estimation in ground forest images using Deep Learning , 2019, Comput. Electron. Agric..
[17] She Guang-hui,et al. Study on estimation of tree volumes and final decision for deforestation and illegal felling of forests. , 2010 .
[18] Julián Tomastík,et al. Tango in forests - An initial experience of the use of the new Google technology in connection with forest inventory tasks , 2017, Comput. Electron. Agric..
[19] Gherardo Chirici,et al. Influence of Scan Density on the Estimation of Single-Tree Attributes by Hand-Held Mobile Laser Scanning , 2019, Forests.
[20] Christopher Dean. Calculation of wood volume and stem taper using terrestrial single-image close-range photogrammetry and contemporary software tools , 2003 .
[21] Feng Zhongke. Precision form method to determine standing wood volume. , 2005 .
[22] Juha Hyyppä,et al. Evaluation of a Smartphone App for Forest Sample Plot Measurements , 2015 .
[23] Eija Honkavaara,et al. Photogrammetric measurement of tree stems from vertical fisheye images , 2017 .
[24] Silvia Santini,et al. An annually-resolved stem growth tool based on 3D laser scans and 2D tree-ring data , 2018, Trees.
[25] Mathias Disney,et al. Tree height in tropical forest as measured by different ground, proximal, and remote sensing instruments, and impacts on above ground biomass estimates , 2019, Int. J. Appl. Earth Obs. Geoinformation.
[26] A. Camia,et al. An assessment of forest biomass maps in Europe using harmonized national statistics and inventory plots , 2018, Forest ecology and management.
[27] Satoshi Tsuyuki,et al. The use of fixed-wing UAV photogrammetry with LiDAR DTM to estimate merchantable volume and carbon stock in living biomass over a mixed conifer-broadleaf forest , 2018, Int. J. Appl. Earth Obs. Geoinformation.
[28] Juha Hyyppä,et al. Feasibility of Google Tango and Kinect for Crowdsourcing Forestry Information , 2017 .
[29] Sébastien Bauwens,et al. Terrestrial photogrammetry: a non‐destructive method for modelling irregularly shaped tropical tree trunks , 2017 .
[30] Matthieu Molinier,et al. Comparison of Sentinel-2 and Landsat 8 imagery for forest variable prediction in boreal region , 2019, Remote Sensing of Environment.
[31] Yi Lin,et al. A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements , 2010 .