UAV-based photogrammetric point clouds - Tree stem mapping in open stands in comparison to terrestrial laser scanner point clouds

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 40, Issue 1W2, 2013, Pages 141-146

  Fritz, A ^a   Kattenborn, T ^a   Koch, B ^a  

^a UNIVERSITY OF FREIBURG   (Germany)

Author keywords

CMVS PMVS; Forest inventory; Point clouds; Single tree detection; Structure from motion; UAV

Indexed keywords

AIRCRAFT DETECTION; ANTENNAS; IMAGE SEGMENTATION; LASER APPLICATIONS; MOTION ANALYSIS; OPTICAL RADAR; PHOTOGRAMMETRY; ROCK MECHANICS; SCANNING; SEEBECK EFFECT; SURVEYING INSTRUMENTS; UNMANNED AERIAL VEHICLES (UAV);

AERIAL VEHICLE; CMVS/PMVS; FOREST INVENTORY; POINT-CLOUDS; SINGLE TREE DETECTION; STRUCTURE FROM MOTION; TERRESTRIAL LASER SCANNERS; TREE DETECTIONS; TREE STEMS; UNMANNED AERIAL VEHICLE;

FORESTRY;

AIR CRAFT; COMPUTER PROGRAMS; ECOLOGY; FORESTRY; IMAGES; MAPPING; PHOTOGRAMMETRY;

EID: 84897486809     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (30)

1. Asner, G. P., 2009. Tropical forest carbon assessment: integrating satellite and airborne mapping approaches. Environmental Research Letters 4(3), pp. 034009.
2. Bienert, A., Scheller, S., Keane, E., Mohan, F. and Nugent, C, 2007. Tree detection and diameter estimations by analysis of forest terrestrial laserscanner point clouds. In: Proceedings of ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007, Espoo, September 12-14, 2007, Finland, Commission V, WG V/3, p. 5055.
3. Eisenbeiss, H., 2009. UAV Photogrammetry. PhD thesis, ETH Zurich.
4. Frolking, S., Palace, M. W., Clark, D. B., Chambers, J. Q., Shugart, H. H. and Hurtt, G. C, 2009. Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure. Journal of Geophysical Research: Biogeosciences 114(G2), pp. n/a-n/a.
5. Furukawa, Y. and Ponce, J., 2010a. Accurate, dense, and robust multi-view stereopsis. IEEE Trans, on Pattern Analysis and Machine Intelligence 32(8), pp. 1362-1376.
6. Furukawa, Y. and Ponce, J., 2010b. Accurate, dense, and robust multiview stereopsis. Pattern Analysis and Machine Intelligence, IEEE Transactions on 32(8), pp. 1362-1376.
7. Haala, N., Cramer, M., Weimer, F. and Trittler, M., 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, pp. 7-12.
8. Harwin, S. and Lucieer, A., 2012. Assessing the accuracy of georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle (uav) imagery. Remote Sensing 4(6), pp. 1573-1599.
9. Hongoh, D., Kajiwara, K. and Honda, Y, 2001. Developing ground truth measurement system using re helicopter and brdf model in forest area. In: 22nd Asian Conference on Remote Sensing, Vol. 5, Sigapore, p. 9.
10. Hunt, E. Raymond, J., Cavigelli, M., Daughtry, C, Mcmurtrey, James E., I. and Walthall, C, 2005. Evaluation of digital photography from model aircraft for remote sensing of crop biomass and nitrogen status. Precision Agriculture 6(4), pp. 359-378.
11. Hyyppa, J., Hyyppa, H., Leckie, D., Gougeon, E, Yu, X. and Maltamo, M., 2008. Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests. International Journal of Remote Sensing 29(5), pp. 1339-1366.
12. Liang, X., Litkey, P., Hyyppa, J., Kukko, A., Kaartinen, H. and Holopainen, M., 2008. Plot-level trunk detection and reconstruction using one-scan-mode terrestrial laser scanning data. In: International Workshop on Earth Observation and Remote Sensing Applications, pp. 1-5.
13. Lingua, A., Marenchino, D. and Nex, E, 2009. Performance analysis of the sift operator for automatic feature extraction and matching in photogrammetric applications. Sensors 9(5), pp. 3745-3766.
14. Lovell, J., Jupp, D., Newnham, G. and Culvenor, D., 2011. Measuring tree stem diameters using intensity profiles from groundbased scanning lidar from a fixed viewpoint. ISPRS Journal of Photogrammetry and Remote Sensing 66(1), pp. 46-55.
15. Lowe, D., 2004. Distinctive image features from scale-invariant keypoints. International journal of computer vision 60(2), pp. 91-110.
16. Lucieer, A., Robinson, S., Turner, D., Harwin, S. and Kelcey, J., 2012. Using a micro-uav for ultra-high resolution multi-sensor observations of antarctic moss beds. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B1, pp. 429-433.
17. Merino, L., Caballero, E, Martnez-de Dios, J., Maza, I. and Ollero, A., 2012. An unmanned aircraft system for automatic forest Are monitoring and measurement. Journal of Intelligent & Robotic Systems 65, pp. 533-548.
18. Moberg, L. and Nordmark, U., 2006. Predicting lumber volume and grade recovery for scots pine stems using tree models and sawmill conversion simulation. Forest products journal 56(4), pp. 68-74.
19. Remondino, E, Barazzetti, L., Nex, E, Scaioni, M. and Sarazzi, D., 2011. Uav photogrammetry for mapping and 3d modelingcurrent status and future perspectives. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 38, pp. 25-31.
20. Rosnell, T. and Honkavaara, E., 2012. Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera. Sensors 12(1), pp. 453-480.
21. Rusu, R. B., Marton, Z. C, Blodow, N., Dolha, M. and Beetz, M., 2008. Towards 3d point cloud based object maps for household environments, robotics and autonomous systems. Robotics and Autonomous Systems 56, pp. 927-941.
22. Snavely, N., Seitz, S. M. and Szeliski, R., 2006. Photo tourism: Exploring photo collections in 3d. In: ACM Transactions on Graphics (Proceedings of SIGGRAPH 2006).
23. Tao, W., Lei, Y and Mooney, P., 2011. Dense point cloud extraction from uav captured images in forest area. In: Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2011 IEEE International Conference on, pp. 389-392.
24. Tesfamichael, S., Ahmed, E, Van Aardt, J. and Blakeway, E, 2009. A semi-variogram approach for estimating stems per hectare in eucalyptus grandis plantations using discrete-return lidar height data. Forest Ecology and Management 258(7), pp. 1188-1199.
25. Turner, D., Lucieer, A. and Watsona, C, 2011. Development of an unmanned aerial vehicle (uav) for hyper resolution vineyard mapping based on visible, multispectral, and thermal imagery. In: Proceedings of the 34th International Symposium on Remote Sensing of Environment (ISRSE34), Sydney, Australia.
26. Valente, J. a., Sanz, D., Del Cerro, J., Barrientos, A. and de Frutos, M., 2013. Near-optimal coverage trajectories for image mosaicing using a mini quad-rotor over irregular-shaped fields. Precision Agriculture 14, pp. 115-132.
27. Vierling, K. T., Vierling, L. A., Gould, W. A., Martinuzzi, S. and Clawges, R. M., 2008. Lidar: shedding new light on habitat characterization and modeling. Frontiers in Ecology and the Environment 6(2), pp. 90-98.
28. Wallace, L. O., Lucieer, A. and Watson, C. S., 2012. Assessing the feasibility of uav-based lidar for high resolution forest change detection. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B7, pp. 499-504.
29. Wu, C, Agarwal, S., Curless, B. and Seitz, S. M., 2011. Multicore bundle adjustment. In: Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, IEEE, pp. 3057-3064.
30. Zhang, C. and Kovacs, J., 2012. The application of small unmanned aerial systems for precision agriculture: a review. Precision Agriculture 13, pp. 693-712.