Measurement of volume and accuracy analysis of standing trees using Forest Survey Intelligent Dendrometer

Abstract The standing tree volume is very important for accurately evaluating stand growth. This paper introduced a new type of high precision portable electronic instrument - Forest Survey Intelligent Dendrometer (FSID). For the instrument, we developed guidelines for measuring the standing tree volume in the sample plot and explained the principles and methods. The instrument can use the integrated angle and distance measuring device to determine the height of standing trees based on the low-power Bluetooth data transmission, extract the coordinates of the characteristic points of the standing trees, calculate the diameter of the tree trunk at any height, and realize the real-time measurement of tree volume in single photo and multiple photo solutions. To verify and analyze the accuracy of the instrument, we measured 181 standing trees in a 45x45m temporary plot in Haidian District, Beijing. The experimental results showed that the accuracy of the FSID for measuring the standing tree volume was 96.89%. Different tree heights lead to different optimal observation distances, and the optimal observation distance of this experiment was approximately 8 m. The method in this paper has the characteristics of real-time, fast, efficient and non-destructive, which can meet the requirements of forest survey, especially in the forest areas where logging is prohibited or restricted. The method shows great potential in forest survey and environmental protection.

[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 .