Estimation of positions and heights from UAV-sensed imagery in tree plantations in agrosilvopastoral systems

International Journal of Remote Sensing

Volumn 39, Issue 14, 2018, Pages 4786-4800

  Surový, Peter ^a   Almeida Ribeiro, Nuno ^b   Panagiotidis, Dimitrios ^a  

^a CZECH UNIVERSITY OF LIFE SCIENCES PRAGUE   (Czech Republic)

^b UNIVERSITY OF ÉVORA   (Portugal)

Author keywords

local maxima; Tree height; tree positions; unmanned aerial vehicle

Indexed keywords

ANTENNAS; CONSERVATION; ECOSYSTEMS; UNMANNED AERIAL VEHICLES (UAV);

FOREST ECOSYSTEM; LOCAL MAXIMUM; MEDITERRANEAN TREES; POTENTIAL BENEFITS; PROBLEM DETECTION; REMOTELY SENSED IMAGERY; TREE HEIGHT; TREE POSITIONS;

FORESTRY;

ESTIMATION METHOD; HEIGHT; IMAGERY; ORTHOPHOTO; PASTORALISM; PLANTATION; REMOTE SENSING; UNMANNED VEHICLE;

PINUS PINEA; QUERCUS; QUERCUS ILEX; QUERCUS SUBER; SCIADOPITYS VERTICILLATA;

EID: 85041554673     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2018.1434329     Document Type: Article

References (46)

1. Armstrong, A., C., Johns, and I., Tubby. 1999.“Effects of Spacing and Cutting Cycle on the Yield of Poplar Grown as an Energy Crop.” Biomass Bioenergy 17 (4): 305–314. doi:10.1016/S0961-9534(99)00054-9
2. Bay, H., A., Ess, T., Tuytelaars, and L., Van Gool. 2008. “SURF: Speeded Up Robust Features.” Computer Vision and Image Understanding (CVIU) 110 (3): 346–359. doi:10.1016/j.cviu.2007.09.014
3. Benomar, L., A., DesRochers, and G. R., Larocque. 2013. “Comparing Growth and Fine Root Distribution in Monocultures and Mixed Plantations of Hybrid Poplar and Spruce.” Journal of Forest Research 24 (2): 247−254. doi:10.1007/S11676-013-0348-7
4. Caccetta, P., S., Furby, and J., Wallace. 2012. “Long-Term Monitoring of Australian Land Cover Change Using Landsat Data: Development, Implementation, and Operation.” In Global Forest Monitoring from Earth Observation, edited by F., Achard, M. C., Hansen, 243–258. Boca Raton, FL, USA: C. R. C. Press
5. Cassidy, M., G., Palmer, and R. G. B., Smith. 2013. “The Effect of Wide Initial Spacing on Wood Properties in Plantation Grown Eucalyptus Pilularis.” New Forests 44 (6): 919–936. doi:10.1007/s11056-013-9385-5
6. Chudý, J., 2017. Využití Dronů Pro Získávání Dat O Zmlazení Z Území Ovlivněných Disturbancemi. (Utilization of drones for data acquisition of regeneration data in areas influenced by disturbances) in Czech, master thesis Czech University of Life Sciences in Prague, pp. 61
7. Culvenor, D., 2002. “TIDA: An Algorithm for the Delineation of Tree Crowns in High Spatial Resolution Remotely Sensed Imagery.” Computers & Geosciences 28 (1): 33–44. doi:10.1016/S0098-3004(00)00110-2
8. Dandois, J. P., and E. C., Ellis. 2010. “Remote Sensing of Vegetation Structure Using Computer Vision.” Remote Sensing 2 (4): 1157–1176. doi:10.3390/rs2041157
9. Dandois, J. P., and E. C., Ellis. 2013. “High Spatial Resolution Three-Dimensional Mapping of Vegetation Spectral Dynamics Using Computer Vision.” Remote Sensing of Environment 136 (136): 259–276. doi:10.1016/j.rse.2013.04.005
10. Edson, C., and M. G., Wing. 2011. “Airborne Light Detection and Ranging (Lidar) for Individual Tree Stem Location, Height, and Biomass Measurements.” Remote Sensing 3: 2494–2528. doi:10.3390/rs3112494
11. FAO. 2010. Global Forest Resources Assessment. Rome, Italy: Food and Agriculture Organization of the United Nations
12. Fonseca, C. R., G., Ganade, R., Baldissera, C. J., Becker, C. R., Boelter, A. D., Brescovit, L. M., Campos, T., Fleck, V. S., Fonseca, and S. M., Hartz. 2009. “Towards an Ecologically-Sustainable Forestry in the Atlantic Forest.” Biological Conservation 142: 1209–1219. doi:10.1016/j.biocon.2009.02.017
13. Gatziolis, D., J. F., Li ́enard, A., Vogs, and N. S., Strigul. 2015. “3D Tree Dimensionality Assessment Using Photogrammetry and Small Unmanned Aerial Vehicles.” PloS One 10 (9): e0137765. doi:10.1371/journal.pone.0137765
14. Grainger, A., 2008. “Difficulties in Tracking the Long-Term Global Trend in Tropical Forest Area.” Proceedings of the National Academy of Sciences of USA 105 (2): 818–823. doi:10.1073/pnas.0703015105
15. Haala, N., M., Cramer, F., Weimer, and M., Trittler. 2011. “Performance Test on UAV-based Photogrammetric Data Collection.” Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII (1/C22): 7–12
16. Hernandez, J. G., E., Gonzalez-Ferreiro, A., Sarmento, J., Silva, A., Nunes, A. C., Correia, L., Fontes, M., Tomé, and R., Diaz-Varela. 2016. “Using High Resolution UAV Imagery to Estimate Tree Variables in Pinus Pinea Plantation in Portugal.” Forest Systems 25(2):eSC09. [S.l.]. doi:10.5424/fs/2016252-08895
17. Jaakkola, A., J., Hyyppä, X., Yu, A., Kukko, H., Kaartinen, X., Liang, H., Hyyppä, and Y., Wang. 2017. “Autonomous Collection of Forest Field Reference—The Outlook and a First Step with UAV Laser Scanning.” Remote Sensing 9 (8): 785. doi:10.3390/rs9080785
18. Koh, L. P., and D. S., Wilcove. 2008. “Is Oil Palm Agriculture Really Destroying Tropical Biodiversity?” Conservation Letters 1 (2): 60–64. doi:10.1111/j.1755-263X.2008.00011.x
19. Lisein, J., M., Pierrot-Deseilligny, S., Bonnet, and P., Lejeune. 2013. “A Photogrammetric Workflow for the Creation of A Forest Canopy Height Model from Small Unmanned Aerial System Imagery.” Forests 4: 922–944. doi:10.3390/f4040922
20. Lowe, D. G., 2004. “Method and Apparatus for Identifying Scale Invariant Features in an Image and Use of Same for Locating an Object in an Image.” US Patent 6 (711): 293
21. Mikita, T., P., Janata, and P., Surový. 2016. “Forest Stand Inventory Based on Combined Aerial and Terrestrial Photogrammetry.” Forests 7 (8): 165. doi:10.3390/f7080165
22. Montero, G., and I., Cañellas. 1999. Sustainable Management of Mediterranean Forests in Spain, Unasylva No. 197, Mediterranean Forests (1999/2)
23. 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. doi:10.1016/S0034-4257(01)00290-5
24. Nájera, A., and J. A., Simonetti. 2010. “Enhancing Avifauna in Commercial Plantations.” Conservation Biology 24 (1): 319–324. doi:10.1111/j.1523-1739.2009.01350.x
25. Nevalainen, O., E., Honkavaara, S., Tuominen, N., Viljanen, T., Hakala, X., Yu, J., Hyyppä, et al. 2017. “Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging.” Remote Sensing 9 (3). doi:10.3390/rs9030185
26. Panagiotidis, D., A., Abdollahnejad, P., Surový, and V., Chiteculo. 2016. “Determining Tree Height and Crown Diameter from High-Resolution UAV Imagery.” International Journal of Remote Sensing 38 (8–10): 1–19. doi:10.1080/01431161.2016.1264028
27. Pinto-Correia, T., N., Ribeiro, and P., SÁ-Sousa. 2011. “Introducing the Montado, the Cork and Holm Oak Agroforestry System of Southern Portugal.” Agroforestry Systems 82 (2): 99–104. doi:10.1007/s10457-011-9388-1
28. Pitkänen, J., M., Maltamo, J., Hyyppä, and X., Yu. 2004. “Adaptive Methods for Individual Tree Detection on Airborne Laser Based Canopy Height Model.” In Proceedings of ISPRS Working Group VIII/2: “Laser-Scanners for Forest and Landscape Assessment, edited by M., Theis, B., Koch, H., Spiecker, and H., Weinacker, 187–191. Germany: University of Freiburg
29. Popescu, S. C., 2007. “Estimating Biomass of Individual Pine Trees Using Airborne LiDAR.” Biomass and Bioenergy 31: 646–655. doi:10.1016/j.biombioe.2007.06.022
30. Puliti, S., H., Olerka, T., Gobakken, and E., Næsset. 2015. “Inventory of Small Forest Areas Using an Unmanned Aerial System.” Remote Sensing 7 (8): 9632–9654. doi:10.3390/rs70809632
31. Puyravaud, J. P., P. W., Davidar, and F., Laurance. 2010. “Cryptic Destruction of India’s Native Forests.” Conservation Letters 3 (6): 390–394. doi:10.1111/j.1755-263X.2010.00141.x
32. Reitberger, J., C., Schnörr, P., Krzystek, and U., Stilla. 2009. “3D Segmentation of Single Trees Exploiting Full Waveform LiDAR Data.” ISPRS Journal of Photogrammetry and Remote Sensing 64 (6): 561–574. doi:10.1016/j.isprsjprs.2009.04.002
33. Remondino, F., L., Barazzetti, F., Nex, M., Scaioni, and D., Sarazzi. 2011. “UAV Photogrammetry for Mapping and 3D Modeling - Current Status and Future Perspectives. International Archives of the Photogrammetry.” Remote Sensing and Spatial Information Sciences 38: 25–31
34. Sperlich, M., T., Kattenborn, B., Koch, and G., Kattenborn. 2014. Potential of Unmanned Aerial Vehicle Based Photogrammetric Point Clouds for Automatic Single Tree Detection. Available at:https://www.researchgate.net/profile/Teja_Kattenborn/publication/261643648_Potential_of_Unmanned_Aerial_Vehicle_Based_Photogrammetric_Point_Clouds_for_Automatic_Single_Tree_Detection/links/0c960534ea7ab61ef7000000.pdf (accessed: 19. 04.2016)
35. Spetsakis, M., and J., Aloimonos. 1990. “Structure from Motion Using Line Correspondences.” International Journal of Computer Vision 4 (3): 171–183. doi:10.1007/BF00054994
36. Steinaker, D. F., E. G., Jobb, J. P., Martini, D. N., Arroyo, J. L., Pacheco, and V. A., Marchesini. 2016. “Vegetation Composition and Structure Changes following Roller-Chopping Deforestation in Central Argentina Woodlands.” Journal of Arid Environment 133: 19–24. doi:10.1016/j.jaridenv.2016.05.005
37. Sterling, S., and A., Ducharne. 2008. “Comprehensive Data Set of Global Land Cover Change for Land Surface Model Applications.” Global Biogeochemical Cycles 22 (GB3017). doi:10.1029/2007GB002959
38. Surový, P., N. A., Ribeiro, and J. S., Pereira. 2011. “Observations on 3-Dimensional Crown Growth of Stone Pine.” Journal of Agroforestry Systems 82: 105–110. doi:10.1007/s10457-010-9344-5
39. Surový, P., A., Yoshimoto, and D., Panagiotidis. 2016. “Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry.” Remote Sensing 8: 123. doi:10.3390/rs8020123
40. Tang, L., and G., Shao. 2015. “Drone Remote Sensing for Forestry Research and Practices.” Journal of Forestry Research 26 (4): 791–797. doi:10.1007/s11676-015-0088-y
41. Tiede, D., G., Hochleitner, and T., Blaschke. 2005. “A Full GIS-based Workflow for Tree Identification and Delineation Using Laser Scanning.” In The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, edited by U., Stilla, F., Rottensteiner, and S., Hinz, pp. 9–14. Vol. XXXVI. Austria, Vienna: International Society for Photogrammetry and Remote Sensing. Part 3/W24. http://www.pf.bgu.tum.de/isprs/cmrt05/cmrt05_pro.html
42. Tompalski, P., N. C., Coops, J. C., White, and M. A., Wulder. 2015. “Enriching ALS-derived Area-Based Estimates of Volume through Tree-Level Downscaling.” Forests 6 (8): 2608–2630. doi:10.3390/f6082608
43. Torresan, C., P., Corona, G., Scrinzi, and J., Vall Marsal. 2016. “Using Classification Trees to Predict Forest Structure Types from LiDAR Data.” Annals of Forest Research 59 (1): 1–18. doi:10.15287/afr.2016.423
44. Ullah, S., M., Farooq, M., Shafique, M. A., Siyab, F., Kareem, and M., Dees. 2016. “Spatial Assessment of Forest Cover and Land-Use Changes in the Hindu-Kush Mountain Ranges of Northern Pakistan.” Journal of Mountain Science 13 (7): 1229–1237. doi:10.1007/s11629-015-3456-3
45. Wallace, L., A., Lucieer, Z., Malenovský, D., Turner, and P., Vopěnka. 2016. “Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (Sfm) Point Clouds.” Forests 7 (3): 1–16. doi:10.3390/f7030062
46. Wallace, L., R., Musk, and A., Lucieer. 2014. “An Assessment of the Repeatability of Automatic Forest Inventory Metrics Derived from UAV-Borne Laser Scanning Data.” IEEE Trans Geoscience Remote Sensing 52 (11): 7160–7169. doi:10.1109/TGRS.2014.2308208