Comparison of UAV photograph-based and airborne lidar-based point clouds over forest from a forestry application perspective

International Journal of Remote Sensing

Volumn 38, Issue 8-10, 2017, Pages 2411-2426

  Thiel, Christian ^a   Schmullius, Christiane ^a  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

AIRCRAFT DETECTION; ANTENNAS; FORESTRY; OPTICAL RADAR; PHOTOGRAPHY;

AIRBORNE LIDAR; CANOPY HEIGHT MODELS; DATA LEVEL; DETECTION RATES; FORESTED AREA; FORESTRY APPLICATIONS; POINT CLOUD; TREE LEVEL;

UNMANNED AERIAL VEHICLES (UAV);

AERIAL PHOTOGRAPHY; FOREST CANOPY; FORESTRY; LIDAR; RASTER; UNMANNED VEHICLE;

GERMANY; JENA; THURINGIA;

EID: 84988405264     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2016.1225181     Document Type: Article

References (20)

1. Chianucci, F., L., Disperati, D., Guzzi, D., Bianchini, V., Nardino, C., Lastri, A., Rindinella, and P., Corona. 2016. “Estimation of Canopy Attributes in Beech Forests Using True Colour Digital Images from a Small Fixed-Wing UAV.” International Journal of Applied Earth Observation and Geoinformation 47:60–68. doi:10.1016/j.jag.2015.12.005.
2. 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.
3. Hernández-Clemente, R., R., Navarro-Cerrillo, F., Ramírez, A., Hornero, and P., Zarco-Tejada. 2014. “A Novel Methodology to Estimate Single-Tree Biophysical Parameters from 3D Digital Imagery Compared to Aerial Laser Scanner Data.” Remote Sensing 6:11627–11648. doi:10.3390/rs61111627.
4. Jakubowski, M., W., Li, Q., Guo, and M., Kelly. 2013. “Delineating Individual Trees from Lidar Data:A Comparison of Vector- and Raster-based Segmentation Approaches.” Remote Sensing 5:4163–4186. doi:10.3390/rs5094163.
5. Jalobeanu, A., and G., Goncalves. 2015. “The Unknown Spatial Quality of Dense Point Clouds Derived from Stereo Images.” IEEE Geoscience and Remote Sensing Letters 12:1013–1017. doi:10.1109/LGRS.2014.2373133.
6. Kaartinen, H., J., Hyyppä, X., Yu, M., Vastaranta, H., Hyyppä, A., Kukko, M., Holopainen, et al. 2012. “An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning.” Remote Sensing 4:950–974. doi:10.3390/rs4040950.
7. Khosravipour, A., A. K., Skidmore, M., Isenburg, and T. J., Wang. 2015. Development of an Algorithm to Generate Pit-Free Digital Surface Models from Lidar, 247–249. France:SilviLaser La Grande Motte.
8. Liang, X., V., Kankare, J., Hyyppä, Y., Wang, A., Kukko, H., Haggrén, X., Yu, et al. 2016. “Terrestrial Laser Scanning in Forest Inventories.” ISPRS Journal of Photogrammetry and Remote Sensing 115:63–77. doi:10.1016/j.isprsjprs.2016.01.006.
9. 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.
10. Liu, T., J., Im, and L. J., Quackenbush. 2015. “A Novel Transferable Individual Tree Crown Delineation Model Based on Fishing Net Dragging and Boundary Classification.” ISPRS Journal of Photogrammetry and Remote Sensing 110:34–47. doi:10.1016/j.isprsjprs.2015.10.002.
11. Llc, A., 2016. Agisoft PhotoScan User Manual - Professional Edition, Version 1.2. St. Petersburg, Russia.
12. Mader, D., R., Blaskow, P., Westfeld, and H. G., Maas. 2015. “Uav-Based Acquisition of 3d Point Cloud–a Comparison of a Low-Cost Laser Scanner and Sfm-Tools.” ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W3:335–341. doi:10.5194/isprsarchives-XL-3-W3-335-2015.
13. McGaughey, R. J., 2015. FUSION/LDV:Software for LIDAR Data Analysis and Visualization, FUSION Version 3.50. USA:USDA - Pacific Northwest Research Station.
14. Mongus, D., and B., Žalik. 2015. “An Efficient Approach to 3D Single Tree-Crown Delineation in Lidar Data.” ISPRS Journal of Photogrammetry and Remote Sensing 108:219–233. doi:10.1016/j.isprsjprs.2015.08.004.
15. Popescu, S. C., and R. H., Wynne. 2004. “Seeing the trees in the Forest:Using Lidar and Multispectral Data Fusion with Local Filtering and Variable Window Size for Estimating Tree Height.” PhotogrammetricEngineering & Remote Sensing 70:589–604. doi:10.14358/PERS.70.5.589.
16. Puliti, S., H., Olerka, T., Gobakken, and E., Næsset. 2015. “Inventory of Small Forest Areas Using an Unmanned Aerial System.” Remote Sensing 7:9632–9654. doi:10.3390/rs70809632.
17. Suomalainen, J., N., Anders, S., Iqbal, G., Roerink, J., Franke, P., Wenting, D., Hünniger, H., Bartholomeus, R., Becker, and L., Kooistra. 2014. “A Lightweight Hyperspectral Mapping System and Photogrammetric Processing Chain for Unmanned Aerial Vehicles.” Remote Sensing 6:11013–11030. doi:10.3390/rs61111013.
18. Zarco-Tejada, P. J., R., Diaz-Varela, V., Angileri, and P., Loudjani. 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. doi:10.1016/j.eja.2014.01.004.
19. Zeiss, B., 2016. “Growth Rate in Roda Forest according to Yield Tables.” In Communication via Email, edited by C., Thiel, 1. Jena.
20. Zhen, Z., L., Quackenbush, and L., Zhang. 2016. “Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data.” Remote Sensing 8:333. doi:10.3390/rs8040333.