Template for high-resolution river landscape mapping using UAV technology

Measurement: Journal of the International Measurement Confederation

Volumn 115, Issue , 2018, Pages 139-151

  Rusnák, Miloš ^a   Sládek, Ján ^a,b   Kidová, Anna ^a   Lehotský, Milan ^a  

^a INSTITUTE OF CHEMISTRY   (Slovakia)

^b GEOTECH Bratislava   (Slovakia)

Author keywords

Data extraction; Fluvial landscape mapping; UAV; UAV photogrammetry; Workflow

Indexed keywords

DATA HANDLING; EXTRACTION; MAPPING; ROCK MECHANICS;

ACCURACY ASSESSMENT; DATA EXTRACTION; GEOMETRIC ERRORS; GROUND CONTROL POINTS; HIGH RESOLUTION; HIGH-RESOLUTION MAPPING; WORKFLOW; WORKFLOW DESIGNS;

UNMANNED AERIAL VEHICLES (UAV);

EID: 85032179372     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2017.10.023     Document Type: Article

References (60)

1. Wheaton, J.M., Fryirs, K.A., Brierley, G., Bangen, S.G., Bouwes, N., O'Brien, G., Geomorphic mapping and taxonomy of fluvial landforms. Geomorphology 248 (2015), 273–295, 10.1016/j.geomorph.2015.07.010.
2. Milton, E.J., Gilvear, D.J., Hooper, I.D., Investigating change in fluvial systems using remotely sensed data. Gurnell, A.M., Petts, G.E., (eds.) Changing River Channels, 1995, John Wiley and Sons, Chichester, 276–301.
3. Bryant, R.G., Gilvear, D.J., Quantifying geomorphic and riparian land cover changes either side of a large flood event using airborne remote sensing: river Tay, Scotland. Geomorphology 29 (1999), 307–321, 10.1016/S0169-555X(99)00023-9.
4. Gilvear, D., Davids, C., Tyler, A.N., The use of remotely sensed data to detect channel hydromorphology; River Tummel, Scotland. River Res. Appl. 20 (2004), 795–811, 10.1002/rra.792.
5. Hooke, J.M., Redmond, C.E., Use of cartographic sources for analyzing river channel change with examples from Britain. Petts, G.E., (eds.) Historical Change of Large Alluvial Rivers: Western Europe, 1989, John Wiley and Sons, Chichester, 79–93.
6. Lejot, J., Delacourt, C., Piégay, H., Fournier, T., Trémélo, M.L., Allemand, P., Very high spatial resolution imagery for channel bathymetry and topography from an unmanned mapping controlled platform. Earth Surf. Process. Landf. 32 (2007), 1705–1725, 10.1002/esp.1595.
7. Gilvear, D., Bryant, R., Analysis of aerial photography and other remotely sensed data. Kondolf, M., Piégay, H., (eds.) Tools in Geomorphology, 2003, Wiley, Chichester, 135–170 doi: 10.1002/0470868333.ch6.
8. Gurnell, A.M., Peiry, J.L., Petts, G.E., Using historical data in fluvial geomorphology. Kondolf, M., Piégay, H., (eds.) Tools in Geomorphology, 2003, Wiley, Chichester, 77–103.
9. Fonstad, M.A., Dietrich, J.T., Courville, B.C., Jensen, J.L., Carbonneau, P.E., Topographic structure from motion: a new development in photogrammetric measurement. Earth Surf. Process. Landf. 38 (2013), 421–430, 10.1002/esp.3366.
10. Sládek, J., Rusnák, M., Nizkonákladové mikro-UAV techológie v geografii (nová metóda zberu priestorových dát). Geografický Časopis 65:3 (2013), 269–285.
11. Sankey, T., Donager, J., McVay, J., Sankey, J.B., UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA. Remote Sens. Environ. 195 (2017), 30–43, 10.1016/j.rse.2017.04.007.
12. Turner, D., Lucieer, A., de Jong, M., Time series analysis of landslide dynamics using an unmanned aerial vehicle (UAV). Remote Sens. 7 (2015), 1736–1757, 10.3390/rs70201736.
13. Harwin, S., Lucieer, A., Assessing the accuracy of georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle (UAV) imagery. Remote Sens. 4 (2012), 1573–1599, 10.3390/rs4061573.
14. Hugenholtz, Ch.H., Whitehead, K., Brown, O.W., Barchyn, T.E., Moorman, B.J., LeClair, A., Riddell, K., Hamilton, T., Geomorphological mapping with a small unmanned aircraft system (sUAS): feature detection and accuracy assessment of a photogrammetrically-derived digital terrain model. Geomorphology 194 (2013), 16–24, 10.1016/j.geomorph.2013.03.023.
15. Niethammer, U., James, M.R., Rothmund, S., Travelletti, J., Joswig, M., UAV-based remote sensing of the Super-Sauze landslide: evaluation and results. Eng. Geol. 128 (2012), 2–11, 10.1016/j.enggeo.2011.03.012.
16. Tonkin, T.N., Midgley, N.G., Graham, D.J., Labadz, J.C., The potential of small unmanned aircraft systems and Structure-from-Motion for topographic surveys: a test of emerging integrated approaches at Cwm Idwal. North Wales. Geomorphol. 226 (2014), 35–43, 10.1016/j.geomorph.2014.07.021.
17. Clapuyt, F., Vanacker, V., Van Oost, K., Reproducibility of UAV-based earth topography reconstructions based on structure-from-motion algorithms. Geomorphology 260 (2016), 4–15, 10.1016/j.geomorph.2015.05.011.
18. Cook, K.J., An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection. Geomorphology 278 (2017), 195–208, 10.1016/j.geomorph.2016.11.009.
19. Rusnák, M., Sládek, J., Buša, J., Greif, V., Suitability of digital elevation models generated by UAV photogrammetry for slope stability assessment (case study of landslide in Svätý Anton, Slovakia). Acta Sci. Pol. Form. Cir. 15:4 (2016), 439–449, 10.15576/ASP.FC/2016.15.4.439.
20. Dunford, R., Michel, K., Gagnage, M., Piégay, H., Trémélo, M.L., Potential and constraints of unmanned aerial vehicle technology for the characterization of Mediterranean riparian forest. Int. J. Remote Sens. 30 (2009), 4915–4935, 10.1080/01431160903023025.
21. Vericat, D., Brasington, J., Wheaton, J., Cowie, M., Accuracy assessment of aerial photographs acquired using lighter-than-air-blimps: low-cost tools for mapping river corridors. River Res. Appl. 25 (2009), 985–1000, 10.1002/rra.1198.
22. Hervouet, A., Dunford, R., Piégay, H., Belletti, B., Trémélo, M.L., Analysis of post-flood recruitment patterns in braided-channel rivers at multiple scales based on an image series collected by unmanned aerial vehicles, ultralight aerial vehicles, and satellites. GIsci. Remote Sens. 48 (2011), 50–73, 10.2747/1548-1603.48.1.50.
23. Flener, C., Vaaja, M., Jaakkola, A., Krooks, A., Kaartinen, H., Kukko, A., Kasvi, E., Hyyppä, H., Alho, P., Seamless mapping of river channels at high resolution using mobile LiDAR and UAV-photography. Remote Sens. 5 (2013), 6382–6407, 10.3390/rs5126382.
24. Flynn, K.F., Chapra, S.C., Remote sensing of submerged aquatic vegetation in a shallow non-turbid river using an unmanned aerial vehicle. Remote Sens. 6 (2014), 12815–12836, 10.3390/rs61212815.
25. Javernick, L., Brasington, J., Caruso, B., Modeling the topography of shallow braided rivers using Structure-from-Motion photogrammetry. Geomorphology 213 (2014), 166–182, 10.1016/j.geomorph.2014.01.006.
26. Miřijovský, J., Langhammer, J., Multitemporal monitoring of the morphodynamics of a mid-mountain stream using UAS photogrammetry. Remote Sens. 7 (2015), 8586–8609, 10.3390/rs70708586.
27. Miřijovský, J., Michalková, M.Š., Petyniak, O., Máčka, Z., Trizna, M., Spatiotemporal evolution of a unique preserved meandering system in Central Europe – The Morava River near Litovel. Catena 127 (2015), 300–311, 10.1016/j.catena.2014.12.006.
28. Tamminga, A.D., Eaton, B.C., Hugenholtz, Ch.H., UAS-based remote sensing of fluvial change following an extreme flood event. Earth Surf. Process. Landf. 40 (2015), 1464–1476, 10.1002/esp.3728.
29. Tamminga, A., Hugenholtz, C., Eaton, B., Lapointe, M., Hyperspatial remote sensing of channel reach morphology and hydraulic fish habitat using an unnmanned aerial vehicle (UAV): a first assessment in the context of river research and management. River Res. Appl. 31 (2015), 379–391, 10.1002/rra.2743.
30. Woodget, A.S., Carbonneau, P.E., Visser, F., Maddock, I.P., Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry. Earth Surf. Process. Landf. 40 (2015), 47–64, 10.1002/esp.3613.
31. Casado, M.R., Gonzales, R.B., Wright, R., Bellamy, P., Quantifying the effect of aerial imagery resolution in automated hydromorphological river characterisation. Remote Sens., 8, 2016, 650, 10.3390/rs8080650.
32. Michez, A., Piégay, H., Lisein, J., Claessens, H., Lejeune, P., Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system. Environ. Monit. Assess., 188, 2016, 146, 10.1007/s10661-015-4996-2.
33. Niedzielski, T., Witek, M., Spallek, W., Observing river stages using unmanned aerial vehicles. Hydrol. Earth Syst. Sci. 20 (2016), 3193–3205, 10.5194/hess-20-3193-2016.
34. Langhammer, J., Lendzioch, T., Miřijovský, J., Hartvich, F., UAV-based optical granulometry as tool for detecting changes in structure of flood depositions. Remote Sens. 9 (2017), 240–261, 10.3390/rs9030240.
35. Marteau, B., Vericat, D., Gibbins, Ch., Batalla, R.J., Green, D.R., Application of Structure-from-Motion photogrammetry to river restoration. Earth Surf. Process. Landf. 42:3 (2016), 503–515, 10.1002/esp.4086.
36. Woodget, A.S., Austrums, R., Subaerial gravel size measurement using topographic data derived from a UAV-SfM approach. Earth Surf. Process. Landf. 42:9 (2017), 1434–1443, 10.1002/esp.4139.
37. Turner, D., Lucieer, A., Watson, Ch., An Automated Technique for generating georectified mosaics from ultra-high resolution unmanned aerial vehicle (UAV) imagery, based on structure from motion (SfM) point clouds. Remote Sens. 4 (2012), 1392–1410, 10.3390/rs4051392.
38. Laliberte, A.S., Goforth, M.A., Steele, C.M., Rango, A., Multispectral remote sensing from unmanned aircraft: image processing workflows and applications for rangeland environments. Remote Sens. 3 (2011), 2529–2551, 10.3390/rs3112529.
39. Stöcker, C., Bennett, R., Nex, F., Gerke, M., Zevenbergen, J., Review of the current state of UAV regulations. Remote Sens., 9, 2017, 459, 10.3390/rs9050459.
40. Harwin, S., Lucieer, A., Osborn, J., The impact of the calibration method on the accuracy of point clouds derived using unmanned aerial vehicle multi-view stereopsis. Remote Sens. 7 (2015), 11933–11953, 10.3390/rs70911933.
41. James, M.R., Robson, S., d'Oleire-Oltmanns, S., Niethammer, U., Optimising UAV topographic surveys processed with structure-from-motion: ground control quality, quantity and bundle adjustment. Geomorphology 280 (2017), 51–66, 10.1016/j.geomorph.2016.11.021.
42. James, M.R., Robson, S., Straightforward reconstruction of 3D surfaces and topography with a camera: accuracy and geoscience application. J. Geophys. Res., 117, 2012, F03017, 10.1029/2011JF002289.
43. Tonkin, T.N., Midgley, N.G., Ground-control networks for image based surface reconstruction: an investigation of optimum survey designs using UAV derived imagery and structure-from-motion photogrammetry. Remote Sens., 8, 2016, 876, 10.3390/rs8090786.
44. Kraus, K., Photogrammetry. Geometry from Images and Laser Scans. second ed., 1997, DeGruyter, Berlin.
45. McGlone, C., Mikhail, E., Bethel, J., Manual of Photogrammetry. fifth ed., 2004, ASPRS, Bethesda.
46. Agüera-Vega, F., Carvajal-Ramírez, F., Martínez-Carricondo, P., Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle. Measurement 98 (2017), 221–227, 10.1016/j.measurement.2016.12.002.
47. Agisoft PhotoScan User Manual. < http://www.agisoft.com/pdf/photoscan-pro_1_3_en.pdf> (accessed 10.03.2017).
48. Miřijovský, J., Bezpilotní systémy – sběr dat a využití ve fotogrammetrii. first ed., 2013, UP Publishing, Olomouc.
49. Fraser, C.S., Automatic camera calibration in close range photogrammetry. Photogramm. Eng. Remote Sens. 79 (2013), 381–388.
50. James, M.R., Robson, S., Mitigating systematic error in topographic models derived from UAV and ground-based image networks. Earth Surf. Process. Landf. 39 (2014), 1413–1420, 10.1002/esp.3609.
51. Sieberth, T., Wackrow, R., Chandler, J.H., Automatic detection of blurred images in UAV image sets. ISPRS J. Photogramm. Remote Sens. 122 (2016), 1–16, 10.1016/j.isprsjprs.2016.09.010.
52. Westoby, M.J., Brasington, J., Glasser, N.F., Hambrey, M.J., Reynolds, J.M., “Structure from Motion” photogrammetry: a low-cost, effective tool for geoscience applications. Geomorphology 179 (2012), 300–314, 10.1016/j.geomorph.2012.08.021.
53. Obanawa, H., Hayakawa, Y., Saito, H., Gomez, C., Comparison of DSMs derived from UAV-SfM method and terrestrial laser scanning. J. Jpn. Soc. Photogramm. Remote Sens. 53 (2014), 67–74, 10.4287/jsprs.53.67.
54. Ouédraogo, M.M., Degré, A., Debouche, C., Lisein, J., The evaluation of unmanned aerial system-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds. Geomorphology 214 (2014), 339–355, 10.1016/j.geomorph.2014.02.016.
55. Thévenet, A., Citterio, A., Piégay, H., A new methodology for the assessment of large woody debris accumulations on highly modified rivers (example of two French piedmont rivers). Regul. River. 14 (1998), 467–483, 10.1002/(SICI)1099-1646(1998110)14:6<467::AID-RRR514>3.0.CO;2-X.
56. Piégay, H., Thévenet, A., Citterio, A., Input, storage and distribution of large woody debris along a mountain river continuum, the Drôme River, France. Catena 35 (1999), 19–39, 10.1016/S0341-8162(98)00120-9.
57. Wyžga, B., Zawiejska, J., Wood storage in a wide mountain river: case study of the Czarny Dunajec, Polish Carpathians. Earth Surf. Process. Landf. 30 (2005), 1475–1494, 10.1002/esp.1204.
58. Rango, A., Laliberte, A.S., Impact of flight regulationson effective use of unmanned aircraft systems for natural resources applications. J Appl. Remote Sens., 4(1), 2010, 10.1117/1.3474649.
59. Kršlák, B., Blišťan, P., Pauliková, A., Puškárová, P., Kovanič, Ľ., Palková, J., Zelizňáková, V., Use of low-cost UAV photogrammetry to analyze the accuracy of a digital elevation model in a case study. Measurement 91 (2016), 276–287, 10.1016/j.measurement.2016.05.028.
60. Kidová, A., Lehotský, M., Rusnák, M., Geomorphic diversity in the braided-wandering Belá River, Slovak Carpathians, as a response to flood variability and environmental changes. Geomorphlogy 272 (2016), 137–149, 10.1016/j.geomorph.2016.01.002.