1. [1] F. Xu, Z. Gao, X. Jiang, W. Shang, J. Ning, D. Song and J. Ai, "A UAV and S2A data-based estimation of the initial biomass of green algae in the South Yellow Sea", Marine pollution bulletin, vol.128, pp. 408-414, 2018. [ DOI:10.1016/j.marpolbul.2018.01.061] 2. [2] Z. Zhou, Y. Yang and B. Chen, "Estimating Spartina alterniflora fractional vegetation cover and aboveground biomass in a coastal wetland using SPOT6 satellite and UAV data", Aquatic Botany, vol.144, pp. 38-45, 2018. [ DOI:10.1016/j.aquabot.2017.10.004] 3. [3] S. Manfreda, M. F. McCabe, P. E. Miller, R. Lucas, V. Pajuelo Madrigal, G. Mallinis, ... and J. Müllerová, "On the Use of Unmanned Aerial Systems for Environmental Monitoring". Remote Sensing, vol.10, pp. 641, 2018. [ DOI:10.3390/rs10040641] 4. [4] M. Ruwaimana, B. Satyanarayana, V. Otero, A. M. Muslim, M. Syafiq, S. Ibrahim, D. Raymaekers, N. Koedam and F. Dahdouh-Guebas, "the advantages of using drones over space-borne imagery in the mapping of mangrove forests", PloS one, vol.13, e0200288, 2018. [ DOI:10.1371/journal.pone.0200288] 5. [5] S. Jiang and W. Jiang, "Efficient structure from motion for oblique UAV images based on maximal spanning tree expansion", ISPRS Journal of Photogrammetry and Remote Sensing, vol.132, pp. 140-161, 2017. [ DOI:10.1016/j.isprsjprs.2017.09.004] 6. [6] N. Micheletti, J. H. Chandler and S. N. Lane, Structure from motion (SFM) photogrammetry. Loughborough University: British Society for Geomorphology, 2015. 7. [7] J. D. Stevenson, S. O'Young and L. Rolland, "Enhancing the visibility of small unmanned aerial vehicles", Procedia Manufacturing, vol.3, pp. 944-951, 2015. [ DOI:10.1016/j.promfg.2015.07.146] 8. [8] J. Guerra-Hernández, E. González-Ferreiro, V. J. Monleón, S. P. Faias, M. Tomé and R. A. Díaz-Varela, "Use of Multi-Temporal UAV-Derived Imagery for Estimating Individual Tree Growth in Pinus pinea Stands", Forests, vol.8, pp. 300, 2017. [ DOI:10.3390/f8080300] 9. [9] D. Panagiotidis, A. Abdollahnejad, P. Surový and V. Chiteculo, "Determining tree height and crown diameter from high-resolution UAV imagery", International journal of remote sensing, vol.38, pp. 2392-2410, 2017. [ DOI:10.1080/01431161.2016.1264028] 10. [10] W. Li, Z. Niu, H. Chen, D. Li, M. Wu and W. Zhao, "Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system", Ecological indicators, vol.67, pp. 637-648, 2016. [ DOI:10.1016/j.ecolind.2016.03.036] 11. [11] D. J. Kachamba, H. O. Ørka, T. Gobakken, T. Eid and W. Mwase, "Biomass estimation using 3D data from unmanned aerial vehicle imagery in a tropical woodland", Remote Sensing, vol.8, pp. 968, 2016. [ DOI:10.3390/rs8110968] 12. [12] S. Puliti, H. O. Ørka, T. Gobakken and E. Næsset, "Inventory of small forest areas using an unmanned aerial system". Remote Sensing, vol.7, pp. 9632-9654, 2015. [ DOI:10.3390/rs70809632] 13. [13] R. Jing, Z. Gong, W. Zhao, R. Pu and L. Deng, "Above-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform-A case study in Wild Duck Lake Wetland, Beijing, China", ISPRS Journal of Photogrammetry and Remote Sensing, vol.134, pp. 122-134, 2017. [ DOI:10.1016/j.isprsjprs.2017.11.002] 14. [14] D. A. Zimble, D. L. Evans, G. C. Carlson, R. C. Parker, S. C. Grado and P. D. Gerard, "characterizing vertical forest structure using small-footprint airborne LiDAR", Remote sensing of Environment, vol.87, pp. 171-182, 2003. [ DOI:10.1016/S0034-4257(03)00139-1] 15. [15] Y. Seul, P. Hien, J. Soo, M. Hee and M. Wook, "Calculation of tree height and canopy crown from drone images using segmentation", Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, vol.33, pp. 605-613, 2015. [ DOI:10.7848/ksgpc.2015.33.6.605] 16. [16] V. Luoma, N. Saarinen, M. A. Wulder, J. C. White, M. Vastaranta, M. Holopainen and J. Hyyppä, "Assessing precision in conventional field measurements of individual tree attributes", Forests, vol.8, pp. 38, 2017. [ DOI:10.3390/f8020038] 17. [17] T. Gobakken, O. M. Bollandsås and E. Næsset, "Comparing biophysical forest characteristics estimated from photogrammetric matching of aerial images and airborne laser scanning data", Scandinavian Journal of Forest Research, vol.30, pp. 73-86, 2015. [ DOI:10.1080/02827581.2014.961954] 18. [18] G. V. Laurin, N. Puletti, Q. Chen, P. Corona, D. Papale and R. Valentini, "Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests", International Journal of Applied Earth Observation and Geoinformation, vol.52, pp. 371-379, 2016. [ DOI:10.1016/j.jag.2016.07.008] 19. [19] E. W. Mauya, L. T. Ene, O. M. Bollandsås, T. Gobakken, E. Næsset, R. E. Malimbwi and E. Zahabu, "Modelling aboveground forest biomass using airborne laser scanner data in the miombo woodlands of Tanzania", Carbon balance and management, vol.10, pp. 28, 2015. [ DOI:10.1186/s13021-015-0037-2] 20. [20] G. W. Frazer, S. Magnussen, M. A. Wulder and K. O. Niemann, "Simulated impact of sample plot size and co-registration error on the accuracy and uncertainty of LiDAR-derived estimates of forest stand biomass", Remote Sensing of Environment, vol.115, pp. 636-649, 2011. [ DOI:10.1016/j.rse.2010.10.008] 21. [21] E. H. Hansen, T. Gobakken, O. M. Bollandsås, E. Zahabu and E. Næsset, "Modeling aboveground biomass in dense tropical submontane rainforest using airborne laser scanner data", Remote Sensing, vol.7, pp. 788-807, 2015. [ DOI:10.3390/rs70100788]
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