Preliminary Result of Drone UAV Derived Multispectral Bathymetry in Coral Reef Ecosystem: A Case Study of Pemuteran Beach
D. R. Stoddart, R. F. McLean, and D. Hopley, “Geomorphology of reef islands, northern Great Barrier Reef,” Philos. Trans. R. Soc. London. B, Biol. Sci., vol. 284, no. 999, pp. 39–61, Nov. 1978, doi: 10.1098/rstb.1978.0052.
J. G. Fryer, “A Simple System for Photogrammetric Mapping in Shallow Water,” Photogramm. Rec., vol. 11, no. 62, pp. 203–208, Oct. 1983, doi: 10.1111/J.1477-9730.1983.TB00471.X.
H. Yao, R. Qin, and X. Chen, “Unmanned aerial vehicle for remote sensing applications - A review,” Remote Sens., vol. 11, no. 12, pp. 1–22, 2019, doi: 10.3390/rs11121443.
L. Rossi, I. Mammi, and F. Pelliccia, “UAV-Derived Multispectral Bathymetry,” Remote Sens. 2020, Vol. 12, Page 3897, vol. 12, no. 23, p. 3897, Nov. 2020, doi: 10.3390/RS12233897.
R. K. Slocum, C. E. Parrish, and C. H. Simpson, “Combined geometric-radiometric and neural network approach to shallow bathymetric mapping with UAS imagery,” ISPRS J. Photogramm. Remote Sens., vol. 169, pp. 351–363, Nov. 2020, doi: 10.1016/j.isprsjprs.2020.09.002.
P. Agrafiotis, D. Skarlatos, A. Georgopoulos, and K. Karantzalos, “Shallow Water Bathymetry Mapping from UAV Imagery Based on Machine Learning,” in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Apr. 2019, vol. 42, no. 2/W10, pp. 9–16, doi: 10.5194/isprs-archives-XLII-2-W10-9-2019.
Y. Matsuba and S. Sato, “Nearshore bathymetry estimation using UAV,” Coast. Eng. J., vol. 60, no. 1, pp. 51–59, 2018, doi: 10.1080/21664250.2018.1436239.
L. Fallati, L. Saponari, A. Savini, F. Marchese, C. Corselli, and P. Galli, “Multi-Temporal UAV Data and Object-Based Image Analysis (OBIA) for Estimation of Substrate Changes in a Post-Bleaching Scenario on a Maldivian Reef,” Remote Sens. 2020, Vol. 12, Page 2093, vol. 12, no. 13, p. 2093, Jun. 2020, doi: 10.3390/RS12132093.
C. G. David, N. Kohl, E. Casella, A. Rovere, P. Ballesteros, and T. Schlurmann, “Structure-from-Motion on shallow reefs and beaches: potential and limitations of consumer-grade drones to reconstruct topography and bathymetry,” Coral Reefs 2021 403, vol. 40, no. 3, pp. 835–851, May 2021, doi: 10.1007/S00338-021-02088-9.
J. T. Dietrich, “Bathymetric Structure-from-Motion: extracting shallow stream bathymetry from multi-view stereo photogrammetry,” Earth Surface Processes and Landforms, vol. 42, no. 2. John Wiley and Sons Ltd, pp. 355–364, Feb. 2017, doi: 10.1002/esp.4060.
P. Agrafiotis, K. Karantzalos, A. Georgopoulos, and D. Skarlatos, “Correcting image refraction: Towards accurate aerial image-based bathymetry mapping in shallow waters,” Remote Sens., vol. 12, no. 2, Jan. 2020, doi: 10.3390/rs12020322.
V. Raoult, S. Reid-Anderson, A. Ferri, and J. E. Williamson, “How Reliable Is Structure from Motion (SfM) over Time and between Observers? A Case Study Using Coral Reef Bommies,” Remote Sens. 2017, Vol. 9, Page 740, vol. 9, no. 7, p. 740, Jul. 2017, doi: 10.3390/RS9070740.
S. Harwin and A. Lucieer, “Assessing the accuracy of geo-referenced point clouds produced via multi-view stereopsis from Unmanned Aerial Vehicle (UAV) imagery,” Remote Sens., vol. 4, no. 6, pp. 1573–1599, Jun. 2012, doi: 10.3390/RS4061573.
J. P. Duffy, J. D. Shutler, M. J. Witt, L. DeBell, and K. Anderson, “Tracking Fine-Scale Structural Changes in Coastal Dune Morphology Using Kite Aerial Photography and Uncertainty-Assessed Structure-from-Motion Photogrammetry,” Remote Sens. 2018, Vol. 10, Page 1494, vol. 10, no. 9, p. 1494, Sep. 2018, doi: 10.3390/RS10091494.
O. Bagheri, M. Ghodsian, M. Saadatseresht, O. Bagheri, M. Ghodsian, and M. Saadatseresht, “Reach Scale Application oF UAV+SfM Method in Shallow Rivers Hyperspectral Bathymetry,” 2015, doi: 10.5194/isprsarchives-XL-1-W5-77-2015.
M. D. M. Manessa et al., “Satellite-Derived Bathymetry Using Random Forest Algorithm and Worldview-2 Imagery,” Geoplanning J. Geomatics Plan., vol. 3, no. 2, pp. 117–126, Nov. 2016, doi: 10.14710/geoplanning.3.2.117-126.
M. D. M. Manessa, K. T. Setiawan, M. Haidar, S. Supriatna, A. Pataropura, and A. H. Supardjo, “Optimization of the random forest algorithm for multispectral derived bathymetry,” Int. J. Geoinformatics, vol. 16, no. 3, 2020.
P. Agrafiotis, D. Skarlatos, A. Georgopoulos, and K. Karantzalos, “Shallow Water Bathymetry Mapping from UAV Imagery based on Machine Learning,” ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci., vol. 42, no. 2/W10, pp. 9–16, Feb. 2019, doi: 10.5194/isprs-archives-XLII-2-W10-9-2019.
DJI, “P4 Multispectral - Specifications,” 2020. .
“Agisoft Metashape.” .
G. Verhoeven, “Taking computer vision aloft - archaeological three-dimensional reconstructions from aerial photographs with photoscan,” Archaeological Prospection, vol. 18, no. 1. John Wiley & Sons, Ltd, pp. 67–73, Jan. 2011, doi: 10.1002/arp.399.
S. Jiang, C. Jiang, and W. Jiang, “Efficient structure from motion for large-scale UAV images: A review and a comparison of SfM tools,” ISPRS J. Photogramm. Remote Sens., vol. 167, no. April, pp. 230–251, 2020, doi: 10.1016/j.isprsjprs.2020.04.016.
A. Eltner and G. Sofia, “Structure from motion photogrammetric technique,” Dev. Earth Surf. Process., vol. 23, no. June, pp. 1–24, 2020, doi: 10.1016/B978-0-444-64177-9.00001-1.
D. R. Lyzenga, “Passive remote sensing techniques for mapping water depth and bottom features,” Appl. Opt., vol. 17, no. 3, pp. 379–383, 1978, doi: 10.1364/AO.17.000379.
L. Breiman, “Random forests,” Mach. Learn., vol. 45, no. 1, pp. 5–32, 2001, doi: 10.1017/CBO9781107415324.004.
M. Andy Liaw, Wiener and M. Andy Liaw, “Package ‘randomForest’ Title Breiman and Cutler’s Random Forests for Classification and Regression,” 2018, doi: 10.1023/A:1010933404324.
- There are currently no refbacks.
Published by INSIGHT - Indonesian Society for Knowledge and Human Development