Using canopy height model derived from UAV images to tree height estimation in Sisangan forest
Subject Areas : Geospatial systems development
Mohammad Reza Kargar
1
,
Hormoz Sohrabi
2
1 - MSc. Student of Forest Sciences and Engineering, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University
2 - Assoc. Prof. Department of Forest Sciences and Engineering, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University
Keywords: Crown height model, Digital terrain model, Structure from Motion (SFM) algorithm, Sisangan, Unmanned aerial vehicle (UAV),
Abstract :
Recent advances in unmanned aerial vehicles (UAVs) technology, as well as the development of lightweight sensors, offers a great possibility for the measurement of different tree features with relatively low costs compared to traditional methods. In this research, the precision and accuracy of tree height measurement and estimation using imagery by a low-cost UAV were studied. For this aim, 854 images with an altitude of 100 m above the ground were taken and the images were processed and dense point cloud was extracted by applying Structure from Motion (SFM) algorithm. The study was conducted in 34.79 ha of Sisangan forest park and 28 sample plots (30 × 30 m) were located in the field and tree heights were measured. Also, tree height was measured using the canopy height model. Linear regression was applied to estimate the actual tree heights based on CHM derived tree eights. The accuracy and precision of the estimates were assessed using relative bias and relative root mean square error. The differences between the field measured and CHM derived tree heights were statistically significant. Based on the results, the relative root means the square error of the height estimation of Buxus hyrcana, Carpinus betulus, Parrotia persica, and other species was 20.39, 20.39, 20.57 and 20.52 percent, respectively. The results showed that tree height measurement based on UAV images and methods that were applied in this research, is biased and the estimations are highly uncertain.
بابازاده، ا.، ا. دانه کار، ب. ریاضی، ا. زاهدی، ف. طاهری و س. موسوی. 1394. تحلیل پوشش گیاهی مناطق باز در پارک جنگلی سیسنگان (استان مازندران). مجله پژوهش های گیاهی (مجله زیست شناسی)، 28(3): 486-498.
بزرگی، ک. و ع. شیخ‌الاسلامی. 1395. بررسی ضریب قدکشیدگی در جنگل راش آمیخته در منطقه حاجیکلا تیرانکلی- ساری. تحقیقات منابع طبیعی تجدیدشونده. 7(1): 1-10.
چناری، ا.، ی. عرفانیفرد، م. دهقانی و ح. پورقاسمی. 1396. برآورد مساحت تاج تک درختان بنه با استفاده از DSM تصاویر هوایی پهپاد در جنگل تحقیقاتی بنه استان فارس. پژوهش‌های علوم و فناوری چوب و جنگل، 24(4): 117-130.
Agisoft L, St Petersburg R. 2014. Agisoft photoscan. Professional Edition, 7: 340 p.
Anderson K, Gaston KJ. 2013. Lightweight unmanned aerial vehicles will revolutionize spatial ecology. Frontiers in Ecology and the Environment, 11(3): 138-146.
Araus JL, Cairns JE. 2014. Field high-throughput phenotyping: the new crop breeding frontier. Trends in Plant Science, 19(1): 52-61.
Bhardwaj A, Sam L, Martín-Torres FJ, Kumar R. 2016. UAVs as remote sensing platform in glaciology: Present applications and future prospects. Remote Sensing of Environment, 175: 196-204.
Dandois JP, Ellis EC. 2010. Remote sensing of vegetation structure using computer vision. Remote Sensing, 2(4): 1157-1176.
Dellaert F, Seitz SM, Thorpe CE, Thrun S. 2000. Structure from motion without correspondence. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No. PR00662). IEEE, pp 557-564.
Engel J, Schöps T, Cremers D. 2014. LSD-SLAM: Large-scale direct monocular SLAM. In: European conference on computer vision. Springer, pp 834-849.
Iizuka K, Yonehara T, Itoh M, Kosugi Y. 2018. Estimating Tree Height and Diameter at Breast Height (DBH) from Digital surface models and orthophotos obtained with an unmanned aerial system for a Japanese Cypress (Chamaecyparis obtusa) Forest. Remote Sensing, 10(1): 13.
Lim YS, La PH, Park JS, Lee MH, Pyeon MW, Kim J-I. 2015. Calculation of tree height and canopy crown from drone images using segmentation. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 33(6): 605-613.
Lisein J, Linchant J, Lejeune P, Bouché P, Vermeulen C. 2013. Aerial surveys using an unmanned aerial system (UAS): comparison of different methods for estimating the surface area of sampling strips. Tropical Conservation Science, 6(4): 506-520.
Malambo L, Popescu SC, Murray SC, Putman E, Pugh NA, Horne DW, Richardson G, Sheridan R, Rooney WL, Avant R. 2018. Multitemporal field-based plant height estimation using 3D point clouds generated from small unmanned aerial systems high-resolution imagery. International Journal of Applied Earth Observation and Geoinformation, 64: 31-42.
Miller E, Dandois J, Detto M, Hall J. 2017. Drones as a tool for monoculture plantation assessment in the steepland tropics. Forests, 8(5): 168.
Mohan M, Silva C, Klauberg C, Jat P, Catts G, Cardil A, Hudak A, Dia M. 2017. Individual tree detection from unmanned aerial vehicle (UAV) derived canopy height model in an open canopy mixed conifer forest. Forests, 8(9): 340.
Naesset E. 2002. Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sensing of Environment, 80(1): 88-99.
Nevalainen O, Honkavaara E, Tuominen S, Viljanen N, Hakala T, Yu X, Hyyppä J, Saari H, Pölönen I, Imai N. 2017. Individual tree detection and classification with UAV-based photogrammetric point clouds and hyperspectral imaging. Remote Sensing, 9(3): 185.
Panagiotidis D, Abdollahnejad A, Surový P, Chiteculo V. 2017. Determining tree height and crown diameter from high-resolution UAV imagery. International Journal of Remote Sensing, 38(8-10): 2392-2410.
Puliti S, Ørka H, Gobakken T, Næsset E. 2015. Inventory of small forest areas using an unmanned aerial system. Remote Sensing, 7(8): 9632-9654.
Shao G, Zhao S, Shugart H. 1995. Forest dynamics modeling: preliminary explanations of optimizing management of Korean pine forests. China Forestry Publishing House, Beijing, 255 p.
Yu X, Hyyppä J, Holopainen M, Vastaranta M. 2010. Comparison of area-based and individual tree-based methods for predicting plot-level forest attributes. Remote Sensing, 2(6): 1481-1495.
Zarco-Tejada PJ, Diaz-Varela R, Angileri V, Loudjani P. 2014. Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods. European Journal of Agronomy, 55: 89-99.
Zimble DA, Evans DL, Carlson GC, Parker RC, Grado SC, Gerard PD. 2003. Characterizing vertical forest structure using small-footprint airborne LiDAR. Remote Sensing of Environment, 87(2-3): 171-182.
_||_
بابازاده، ا.، ا. دانه کار، ب. ریاضی، ا. زاهدی، ف. طاهری و س. موسوی. 1394. تحلیل پوشش گیاهی مناطق باز در پارک جنگلی سیسنگان (استان مازندران). مجله پژوهش های گیاهی (مجله زیست شناسی)، 28(3): 486-498.
بزرگی، ک. و ع. شیخ‌الاسلامی. 1395. بررسی ضریب قدکشیدگی در جنگل راش آمیخته در منطقه حاجیکلا تیرانکلی- ساری. تحقیقات منابع طبیعی تجدیدشونده. 7(1): 1-10.
چناری، ا.، ی. عرفانیفرد، م. دهقانی و ح. پورقاسمی. 1396. برآورد مساحت تاج تک درختان بنه با استفاده از DSM تصاویر هوایی پهپاد در جنگل تحقیقاتی بنه استان فارس. پژوهش‌های علوم و فناوری چوب و جنگل، 24(4): 117-130.
Agisoft L, St Petersburg R. 2014. Agisoft photoscan. Professional Edition, 7: 340 p.
Anderson K, Gaston KJ. 2013. Lightweight unmanned aerial vehicles will revolutionize spatial ecology. Frontiers in Ecology and the Environment, 11(3): 138-146.
Araus JL, Cairns JE. 2014. Field high-throughput phenotyping: the new crop breeding frontier. Trends in Plant Science, 19(1): 52-61.
Bhardwaj A, Sam L, Martín-Torres FJ, Kumar R. 2016. UAVs as remote sensing platform in glaciology: Present applications and future prospects. Remote Sensing of Environment, 175: 196-204.
Dandois JP, Ellis EC. 2010. Remote sensing of vegetation structure using computer vision. Remote Sensing, 2(4): 1157-1176.
Dellaert F, Seitz SM, Thorpe CE, Thrun S. 2000. Structure from motion without correspondence. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No. PR00662). IEEE, pp 557-564.
Engel J, Schöps T, Cremers D. 2014. LSD-SLAM: Large-scale direct monocular SLAM. In: European conference on computer vision. Springer, pp 834-849.
Iizuka K, Yonehara T, Itoh M, Kosugi Y. 2018. Estimating Tree Height and Diameter at Breast Height (DBH) from Digital surface models and orthophotos obtained with an unmanned aerial system for a Japanese Cypress (Chamaecyparis obtusa) Forest. Remote Sensing, 10(1): 13.
Lim YS, La PH, Park JS, Lee MH, Pyeon MW, Kim J-I. 2015. Calculation of tree height and canopy crown from drone images using segmentation. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 33(6): 605-613.
Lisein J, Linchant J, Lejeune P, Bouché P, Vermeulen C. 2013. Aerial surveys using an unmanned aerial system (UAS): comparison of different methods for estimating the surface area of sampling strips. Tropical Conservation Science, 6(4): 506-520.
Malambo L, Popescu SC, Murray SC, Putman E, Pugh NA, Horne DW, Richardson G, Sheridan R, Rooney WL, Avant R. 2018. Multitemporal field-based plant height estimation using 3D point clouds generated from small unmanned aerial systems high-resolution imagery. International Journal of Applied Earth Observation and Geoinformation, 64: 31-42.
Miller E, Dandois J, Detto M, Hall J. 2017. Drones as a tool for monoculture plantation assessment in the steepland tropics. Forests, 8(5): 168.
Mohan M, Silva C, Klauberg C, Jat P, Catts G, Cardil A, Hudak A, Dia M. 2017. Individual tree detection from unmanned aerial vehicle (UAV) derived canopy height model in an open canopy mixed conifer forest. Forests, 8(9): 340.
Naesset E. 2002. Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sensing of Environment, 80(1): 88-99.
Nevalainen O, Honkavaara E, Tuominen S, Viljanen N, Hakala T, Yu X, Hyyppä J, Saari H, Pölönen I, Imai N. 2017. Individual tree detection and classification with UAV-based photogrammetric point clouds and hyperspectral imaging. Remote Sensing, 9(3): 185.
Panagiotidis D, Abdollahnejad A, Surový P, Chiteculo V. 2017. Determining tree height and crown diameter from high-resolution UAV imagery. International Journal of Remote Sensing, 38(8-10): 2392-2410.
Puliti S, Ørka H, Gobakken T, Næsset E. 2015. Inventory of small forest areas using an unmanned aerial system. Remote Sensing, 7(8): 9632-9654.
Shao G, Zhao S, Shugart H. 1995. Forest dynamics modeling: preliminary explanations of optimizing management of Korean pine forests. China Forestry Publishing House, Beijing, 255 p.
Yu X, Hyyppä J, Holopainen M, Vastaranta M. 2010. Comparison of area-based and individual tree-based methods for predicting plot-level forest attributes. Remote Sensing, 2(6): 1481-1495.
Zarco-Tejada PJ, Diaz-Varela R, Angileri V, Loudjani P. 2014. Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods. European Journal of Agronomy, 55: 89-99.
Zimble DA, Evans DL, Carlson GC, Parker RC, Grado SC, Gerard PD. 2003. Characterizing vertical forest structure using small-footprint airborne LiDAR. Remote Sensing of Environment, 87(2-3): 171-182.
