全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Seamless Mapping of River Channels at High Resolution Using Mobile LiDAR and UAV-Photography

DOI: 10.3390/rs5126382

Keywords: UAV, mobile laser scanning, LiDAR, photogrammetry, optical bathymetry, seamless DTM, DTM, elevation, river, Finland

Full-Text   Cite this paper   Add to My Lib

Abstract:

Accurate terrain models are a crucial component of studies of river channel evolution. In this paper we describe a new methodology for creating high-resolution seamless digital terrain models (DTM) of river channels and their floodplains. We combine mobile laser scanning and low-altitude unmanned aerial vehicle (UAV) photography-based methods for creating both a digital bathymetric model of the inundated river channel and a DTM of a point bar of a meandering sub-arctic river. We evaluate mobile laser scanning and UAV-based photogrammetry point clouds against terrestrial laser scanning and combine these data with an optical bathymetric model to create a seamless DTM of two different measurement periods. Using this multi-temporal seamless data, we calculate a DTM of difference that allows a change detection of the meander bend over a one-year period.

References

[1]  Veijalainen, N.; Lotsari, E.; Alho, P.; Vehvil?inen, B.; K?yhk?, J. National scale assessment of climate change impacts on flooding in Finland. J. Hydrol 2010, 391, 333–350.
[2]  Lotsari, E.; Wainwright, D.; Corner, G.; Alho, P.; K?yhk?, J. Surveyed and modelled one-year morphodynamics in the braided lower Tana River. Hydrol. Process. 2013, doi:10.1002/hyp.9750.
[3]  Alho, P.; Hyypp?, H.; Hyypp?, J. Consequence of DTM precision for flood hazard mapping: A case study in SW Finland. Nord. J. Surv. Real Estate Res 2009, 6, 21–39.
[4]  Hicks, D.M.; Shankar, U.; Duncan, M.J.; Rebuffé, M.; Aberle, J. Use of Remote-Sensing with Two-Dimensional Hydrodynamic Models to Assess Impacts of Hydro-Operations on a Large, Braided, Gravel-Bed River: Waitaki River, New Zealand. In Braided Rivers; Smith, G.H.S., Best, J.L., Bristow, C.S., Petts, G.E., Eds.; Blackwell Publishing Ltd: Malden, MA, USA, 2009; pp. 311–326.
[5]  Vetter, M.; Hofle, B.; Mandlburger, G.; Rutzinger, M. Estimating changes of riverine landscapes and riverbeds by using airborne LiDAR data and river cross-sections. Z. Geomorphol. Suppl. Issues 2011, 55, 51–65.
[6]  Williams, R.; Brasington, J.; Vericat, D.; Hicks, D. Hyperscale terrain modelling of braided rivers: Fusing mobile terrestrial laser scanning and optical bathymetric mapping. Earth Surf. Process. Landf. 2013, doi:10.1002/esp.3437.
[7]  Allouis, T.; Bailly, J.S.; Feurer, D. Assessing Water Surface Effects on LiDAR Bathymetry Measurements in Very Shallow Rivers: A Theoretical Study. Proceedings of the Second Space for Hydrology Workshop “Surface Water Storage and Runoff: Modeling, In-Situ Data and Remote Sensing”, Geneva, Switzerland, 12–14 November 2007.
[8]  Feurer, D.; Bailly, J.S.; Puech, C.; Le Coarer, Y.; Viau, A.A. Very-high-resolution mapping of river-immersed topography by remote sensing. Prog. Phys. Geogr 2008, 32, 403–419.
[9]  Lyzenga, D.R. Remote sensing of bottom reflectance and water attenuation parameters in shallow water using aircraft and Landsat data. Int. J. Remote Sens 1981, 2, 71–82.
[10]  Best, J. The fluid dynamics of river dunes: A review and some future research directions. J. Geophys. Res. Earth Surf. 2005, 110, doi:10.1029/2004JF000218.
[11]  Fuller, I.C.; Large, A.R.; Charlton, M.E.; Heritage, G.L.; Milan, D.J. Reach-scale sediment transfers: An evaluation of two morphological budgeting approaches. Earth Surf. Process. Landf 2003, 28, 889–903.
[12]  Smith, M.J.; Chandler, J.; Rose, J. High spatial resolution data acquisition for the geosciences: Kite aerial photography. Earth Surf. Process. Landf 2009, 34, 155–161.
[13]  Heritage, G.; Hetherington, D. Towards a protocol for laser scanning in fluvial geomorphology. Earth Surf. Process. Landf 2007, 32, 66–74.
[14]  Cobby, D.M.; Mason, D.C.; Davenport, I.J. Image processing of airborne scanning laser altimetry data for improved river flood modelling. ISPRS J. Photogramm. Remote Sens 2001, 56, 121–138.
[15]  Bates, P. Remote sensing and flood inundation modelling. Hydrol. Process 2004, 18, 2593–2597.
[16]  Hyypp?, J.; Hyypp?, H.; Leckie, D.; Gougeon, F.; Yu, X.; Maltamo, M. Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests. Int. J. Remote Sens 2008, 29, 1339–1366.
[17]  Mason, D.C.; Cobby, D.M.; Horritt, M.S.; Bates, P.D. Floodplain friction parameterization in two-dimensional river flood models using vegetation heights derived from airborne scanning laser altimetry. Hydrol. Process 2003, 17, 1711–1732.
[18]  Kasvi, E.; Vaaja, M.; Alho, P.; Hyypp?, H.; Hyypp?, J.; Kaartinen, H.; Kukko, A. Morphological changes on meander point bars associated with flow structure at different discharges. Earth Surf. Process. Landf 2012, 38, 577–590.
[19]  Wang, Y.; Liang, X.; Flener, C.; Kukko, A.; Kaartinen, H.; Kurkela, M.; Vaaja, M.; Hyypp?, H.; Alho, P. 3D modeling of coarse fluvial sediments based on mobile laser scanning data. Remote Sens 2013, 5, 4571–4592.
[20]  El-Sheimy, N. An Overview of Mobile Mapping Systems. Proceedings of the From Pharaohs to Geoinformatics FIG Working Week 2005 and GSDI-8, Cairo, Egypt, 16–21 April 2005.
[21]  Kukko, A.; Andrei, C.O.; Salminen, V.M.; Kaartinen, H.; Chen, Y.; R?nnholm, P.; Hyypp?, H.; Hyypp?, J.; Chen, R.; Haggrén, H.; et al. Road environment mapping system of the Finnish Geodetic Institute-FGI ROAMER. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci 2007, 36, 241–247.
[22]  Barber, D.; Mills, J.; Smith-Voysey, S. Geometric validation of a ground-based mobile laser scanning system. ISPRS J. Photogramm. Remote Sens 2008, 63, 128–141.
[23]  Graham, L. Mobile mapping systems overview. Photogramm. Eng. Remote Sens 2010, 76, 222–228.
[24]  Alho, P.; Kukko, A.; Hyypp?, H.; Kaartinen, H.; Hyypp?, J.; Jaakkola, A. Application of boat-based laser scanning for river survey. Earth Surf. Process. Landf 2009, 34, 1831–1838.
[25]  Hohenthal, J.; Alho, P.; Hyypp?, J.; Hyypp?, H. Laser scanning applications in fluvial studies. Prog. Phys. Geogr 2011, 35, 782–809.
[26]  Jaakkola, A.; Hyyppa, J.; Kukko, A.; Yu, X.; Kaartinen, H.; Lehtomaki, M.; Lin, Y. A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements. ISPRS J. Photogramm. Remote Sens 2010, 65, 514–522.
[27]  Haarbrink, R.; Koers, E. Helicopter UAV for Photogrammetry and Rapid Response. Proceedings of the 2nd International Workshop “The Future of Remote Sensing”, Antwerp, Belgium, 17–18 October 2006; 36, p. 1.
[28]  Sauerbier, M.; Eisenbeiss, H. UAVs for the documentation of archaeological excavations. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci 2010, 38, 526–531.
[29]  Remondino, F.; Barazzetti, L.; Nex, F.; Scaioni, M.; Sarazzi, D. UAV photogrammetry for mapping and 3d modeling—Current status and future perspectives. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci 2011, 38, 1.
[30]  Rosnell, T.; Honkavaara, E. Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera. Sensors 2012, 12, 453–480.
[31]  Berni, J.; Zarco-Tejada, P.J.; Suárez, L.; Fereres, E. Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Trans. Geosci. Remote Sens 2009, 47, 722–738.
[32]  Koljonen, S.; Huusko, A.; M?ki-Pet?ys, A.; Louhi, P.; Muotka, T. Assessing habitat suitability for juvenile atlantic salmon in relation to in-stream restoration and discharge variability. Restor. Ecol 2012, 21, 344–352.
[33]  Maxwell, S.L.; Smith, A.V. Generating river bottom profiles with a Dual-Frequency Identification Sonar (DIDSON). North Am. J. Fish. Manag 2007, 27, 1294–1309.
[34]  Sirni?, V.P. Uoman Kartoitus-Teknologia. Maank?ytt? 2004, 3, 26–27.
[35]  Kaeser, A.J.; Litts, T.L.; Tracy, T.W. Using low-cost side-scan sonar for benthic mapping throughout the Lower Flint River, Georgia, USA. River Res. Appl 2013, 29, 634–644.
[36]  Gao, J. Bathymetric mapping by means of remote sensing: Methods, accuracy and limitations. Prog. Phys. Geogr 2009, 33, 103–116.
[37]  Hilldale, R.C.; Raff, D. Assessing the ability of airborne LiDAR to map river bathymetry. Earth Surf. Process. Landf 2008, 33, 773–783.
[38]  Winterbottom, S.J.; Gilvear, D.J. Quantification of channel bed morphology in gravel-bed rivers using airborne multispectral imagery and aerial photography. Regul. Rivers-Res. Manag 1997, 13, 489–499.
[39]  Westaway, R.; Lane, S.; Hicks, D. Remote survey of large-scale braided, gravel-bed rivers using digital photogrammetry and image analysis. Int. J. Remote Sens 2003, 24, 795–815.
[40]  Gilvear, D.; Hunter, P.; Higgins, T. An experimental approach to the measurement of the effects of water depth and substrate on optical and near infra-red reflectance: A field-based assessment of the feasibility of mapping submerged instream habitat. Int. J. Remote Sens 2007, 28, 2241–2256.
[41]  Flener, C.; Lotsari, E.; Alho, P.; K?yhk?, J. Comparison of empirical and theoretical remote sensing based bathymetry models in river environments. River Res. Appl 2012, 28, 118–133.
[42]  Legleiter, C.; Roberts, D.; Marcus, W.; Fonstad, M. Passive optical remote sensing of river channel morphology and in-stream habitat: Physical basis and feasibility. Remote Sens. Environ 2004, 93, 493–510.
[43]  Fonstad, M.; Marcus, W. Remote sensing of stream depths with hydraulically assisted bathymetry (HAB) models. Geomorphology 2005, 72, 320–339.
[44]  Marcus, W.A.; Fonstad, M.A. Optical remote mapping of rivers at sub-meter resolutions and watershed extents. Earth Surf. Process. Landf 2008, 33, 4–24.
[45]  Legleiter, C.; Roberts, D.; Lawrence, R. Spectrally based remote sensing of river bathymetry. Earth Surf. Process. Landf 2009, 34, 1039–1059.
[46]  Flener, C. Estimating deep water radiance in shallow water: Adapting optical bathymetry modelling to shallow river environments. Boreal Environ. Res 2013, 18, 488–502.
[47]  Legleiter, C.J.; Roberts, D.A. A forward image model for passive optical remote sensing of river bathymetry. Remote Sens. Environ 2009, 113, 1025–1045.
[48]  Legleiter, C.J.; Overstreet, B.T. Mapping gravel bed river bathymetry from space. J. Geophys. Res. Earth Surf. 2012, 117, doi:10.1029/2012JF002539.
[49]  Alho, P.; M?kinen, J. Hydraulic parameter estimations of a 2D model validated with sedimentological findings in the point bar environment. Hydrol. Process 2010, 24, 2578–2593.
[50]  Mansikkaniemi, H.; M?ki, O.P. Palaeochannels and recent changes in the Pulmankijoki valley, northern Lapland. Fennia 1990, 168, 137–152.
[51]  Vaaja, M.; Kukko, A.; Kaartinen, H.; Kurkela, M.; Kasvi, E.; Flener, C.; Hyypp?, H.; Hyypp?, J.; J?rvel?, J.; Alho, P. Data processing and quality evaluation of a boat-based mobile laser scanning system. Sensors 2013, 13, 12497–12515.
[52]  Kukko, A.; Kaartinen, H.; Hyypp?, J.; Chen, Y. Multiplatform mobile laser scanning: Usability and performance. Sensors 2012, 12, 11712–11733.
[53]  Axelsson, P. DEM generation from laser scanner data using adaptive TIN models. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci 2000, 33, 111–118.
[54]  Combrink, A. Introduction to Lidar-Based Aerial Surveys (Part 2). In PositionIT; EE Publishers: Muldersdrift, South Africa, 2011; pp. 20–24.
[55]  Bilker, M.; Kaartinen, H. The Quality of Real-Time Kinematic (RTK) GPS Positioning; Reports of the Finnish Geodetic Institute: Masala, Finland, 2001.
[56]  Schürch, P.; Densmore, A.L.; Rosser, N.J.; Lim, M.; McArdell, B.W. Detection of surface change in complex topography using terrestrial laser scanning: Application to the Illgraben debris-flow channel. Earth Surf. Process. Landf 2011, 36, 1847–1859.
[57]  Milan, D.J.; Heritage, G.L.; Hetherington, D. Application of a 3D laser scanner in the assessment of erosion and deposition volumes and channel change in a proglacial river. Earth Surf. Process. Landf 2007, 32, 1657–1674.
[58]  Bitenc, M.; Lindenbergh, R.; Khoshelham, K.; van Waarden, A.P. Evaluation of a LiDAR land-based mobile mapping system for monitoring sandy coasts. Remote Sens 2011, 3, 1472–1491.
[59]  Marcus, W.; Legleiter, C.; Aspinall, R.; Boardman, J.; Crabtree, R. High spatial resolution hyperspectral mapping of in-stream habitats, depths, and woody debris in mountain streams. Geomorphology 2003, 55, 363–380.
[60]  Carbonneau, P.E.; Lane, S.N.; Bergeron, N. Feature based image processing methods applied to bathymetric measurements from airborne remote sensing in fluvial environments. Earth Surf. Process. Landf 2006, 31, 1413–1423.
[61]  Alho, P.; Vaaja, M.; Kukko, A.; Kasvi, E.; Kurkela, M.; Hyyppa, J.; Hyyppa, H.; Kaartinen, H.A. Mobile laser scanning in fluvial geomorphology: Mapping and change detection of point bars. Z. für Geomorphol 2011, 55, 31–50.
[62]  Vaaja, M.; Hyypp?, J.; Kukko, A.; Kaartinen, H.; Hyypp?, H.; Alho, P. Mapping topography changes and elevation accuracies using a mobile laser scanner. Remote Sens 2011, 3, 587–600.
[63]  Kasvi, E.; Alho, P.; Vaaja, M.; Hyypp?, H.; Hyypp?, J. Spatial and temporal distribution of fluvio-morphological processes on a meander point bar during a flood event. Hydrol. Res 2013, 44, 1022–1039.
[64]  Entwistle, N.S.; Fuller, I.C. Terrestrial Laser Scanning to Derive the Surface Grain Size Facies Character of Gravel Bars. In Laser Scanning for the Environmental Sciences; Heritage, G.L.L.A., Ed.; Wiley-Blackwell: Oxford, UK, 2009; pp. 102–114.
[65]  Lotsari, E.; Vaaja, M.; Flener, C.; Kaartinen, H.; Kukko, A.; Kasvi, E.; Hyypp?, H.; Hyypp?, J.; Alho, P. Detecting the morphological changes of banks and point bars in a meandering river using high-accuracy multi-temporal laser scanning and flow measurements. Water Resour. Res. 2013. submitted.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133