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Spatio-temporal Analysis of Beach Morphology using LIDAR, RTK-GPS and Open Source GRASS GIS

Spatio-temporal Analysis of Beach Morphology using LIDAR, RTK-GPS and Open Source GRASS GIS

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Spatio-temporal Analysis of Beach Morphology using LIDAR, RTK-GPS and Open Source GRASS GIS

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  1. Spatio-temporal Analysis of Beach Morphology using LIDAR, RTK-GPS and Open Source GRASS GIS Helena Mitasova Department of Marine, Earth and Atmospheric Sciences, NCSU, Raleigh, T. Drake, MEAS NCSU, R. Harmon, US Army Research Office, D. Bernstein CMWS, Coastal Carolina Univ. SC, H.C. Miller, USACE FRF Duck http://www.skagit.meas.ncsu.edu/~helena

  2. Goal - explore the possibilities to gain new insights into short-term coastal topography evolution by combining modern mapping technologies with Open source GRASS GIS - provide methodology for cost effective short-term monitoring and analysis of topographic change to support sustainable coastal management - quantify the spatial and temporal changes in beach morphology before and after human intervention at Bald Head Island, NC

  3. Mapping technologies Bathymetry: multibeam and conventional sonar (J.McNinch, H.Miller) Beach topography: Real Time Kinematic GPS (D. Bernstein) Coastal topography: LIDAR USGS/NOAA ATM-II • Challenges : • massive data sets, oversampling, noise • complex surfaces with important subtle features • anisotropy and heterogeneous coverage

  4. Integrating digital coastal data and GIS Open source GIS: GRASS5 grass.itc.it General purpose GIS for raster, vector, site and image data processing, analysis and visualization Developed at US Army CERL 1982-1995, GPL in 1999 DEM time series slope, curvatures shoreline change 1st ,2nd order diffs volume change visualization GRASS GIS RST interpolation topoanalysis map algebra: change analysis RTK GPS LIDAR points

  5. Spatial Approximation using RST Gridding with high accuracy and detailed representation of morphology can be obtained byRST(Regularized Spline with Smoothing and Tension) : LIDAR data: 1m binning • flexibility: tension and smoothing, • simultaneous computation of slope, aspect, curvatures, • segmented processing for large data sets • formally equivalent to universal kriging (covariance function determined by smoothness seminorm) • physical basis: minimum energy surface 3m binning 1m approximation by RST H. Mitasova

  6. Bald Head Island Human impact on evolution of shore topography and nearshore bathymetry: channel deepening and re-alignment, beach nourishment in 2001. Cape Fear Rv LIDAR 1997-2000 RTK GPS 2001-02 elevation [m] re-aligned channel Single and multi beam sonar 2000, 2001, 2002 Integrated 10m resolution model from multiple sources

  7. 2D shoreline change Dec. 02: 21m beyond pre-nourishment A A 1997 2000 2001 2002 B A LIDAR 97 – 00 30m 10m/y RTKGPS 01 – 02 42m 42m/y B LIDAR 97 – 00 36m 12m/y RTKGPS 01 – 02 17m 17m/y 1998: LIDAR 0m 2000: LIDAR 0m 2001 Dec.: RTK GPS after nourishment

  8. South Beach evolution 1997-2000 Overlayed 1997 and 2000 LIDAR surfaces: central section is relatively stable, rest erodes while changing its shape and moving landwards Annual sand loss rate: 3500 m3/ha Shoreline erosion rate 10m/year 15% of sand was deposited behind the foredune: landward movement West Center East convex -> concave 2000 z>0m z<0m stable pivot area stable concave -> convex

  9. Slope and curvature High erosion area 1998 Interpolated by RST at 2m resolution with high tension parameter Slope 2000 concave convex Curvature H. Mitasova

  10. Slope and curvature change Severely eroding area approximated and analyzed by RST 1998 Slope Profile curvature concave convex 2000

  11. South Beach change: 1997-2000 Elevation change 1997-2000 Volume change: loss: 376,000 m3 gain: 30,000 m3 m loss gain acceleration Second order elevation change 1997-1998-2000 H. Mitasova

  12. RTK GPS 2001-2001 isotropic RST anisotropic RST cros-shore profiles + shoreline survey pattern ~250m cross-shore + long-shore profiles survey pattern RST with anisotropic tension H. Mitasova

  13. RTK GPS surveying pattern Binned LIDAR data were sampled by RTK-GPS survey points. DEM was then interpolated and compared with the LIDAR data: 4643 grid points for 5m, 13108 grid points for 3m resolution. survey pattern / RST gridding no. of points MAE [m] RMSE csh profiles / isotropic 179 / 55 0.73 0.78 csh profiles / anis. optim. 179 / 55 0.43 0.36 lsh profiles / anis., optim. 990 / 757 0.27 0.12 csh+lsh profiles / anis., optim. 1169 / 789 0.21 0.08 same at 3m resolution 1169 / 988 0.19 0.07 csh+lsh profiles / anis., opt. subset 0.16 0.05 DEM approximated from cross-shore profiles is the least accurate. Long-shore profiles, anisotropy and optimized approximation parameters can significantly improve the accuracy of DEM. H. Mitasova

  14. Pre-nourishment 2000 LIDAR LIDAR 2000 H. Mitasova

  15. Change after nourishment LIDAR 2000 + RTK GPS Dec. 2001 1 million m3 of sand added H. Mitasova

  16. Change after nourishment LIDAR 2000 + RTK GPS May 2002 H. Mitasova

  17. Change after nourishment LIDAR 2000 + RTK GPS Sep. 2002

  18. Change after nourishment LIDAR 2000 + RTK GPS Dec. 2002

  19. Change after nourishment: profiles LIDAR 2000 RTKS: Dec. 2001 May 2002 September 2002

  20. Elevation change after nourishment Sep. 2002 - Dec. 2001 RTK GPS Aug. 2000 - Fall 1997 LIDAR Sep. 2002-Aug. 2000 RTK GPS - LIDAR H. Mitasova

  21. Volume and shoreline change time period loss gain loss rate [m3] [m3] [m3/ha.year] 1 y 1997 - 1998 160000 42000 4400 2 y 1998 - 2000 254000 48000 3500 3 y 1997 - 2000 376000 65000 3500 5 mo Dec.01 - May 02 220000 2000 13200 4 mo May 02 - Sep 02 162000 80000 12100 4 mo Sep 02 - Dec 02 108000 107000 8100 H. Mitasova

  22. Zalewski: June 2001 Bernstein December 2002

  23. Conclusions I Combination of modern mapping techniques with Open source GIS provides unique insight into 3D coastal topography evolution at high spatial and temporal resolution. GIS based analysis and visualization allows us to quantify the observed changes (elevation, shoreline, volume, slope and shape) and evaluate effectiveness of stabilization measures. The developed methodology is being further enhanced and applied to other areas. H. Mitasova

  24. Conclusions II Bald Head Island Analysis based on LIDAR and RTK GPS data showed systematic, spatially variable erosion of the beach accompanied with beach shape change. After renourishment the rates increased in the west section and the beach became more stable in the east. Future Analysis of the entire area as a single system: - bathymetry (fate of eroded sand: back to channel, CF shoal, sandbars ?) - new LIDAR survey - modeling (SBEACH, DELFT3D) H. Mitasova

  25. Acknowledgment: This project is funded by the NRC/ARO fellowship. In addition to observations acquired by co-authors, data from NOAA-USGS (LDART), USACE FRF Duck NC (FRF web site) and UNC Wilmigton (Anders et al. 1990, Clearly et al. 1989) were used. 1997 1998 1999 2000 12/2001 05/2002 09/2002 1997-2002 Cape Fear change 1997 - 2002 H. Mitasova

  26. Cape Fear elevation change LIDAR 1997-2000(grey) RTK GPS Dec. 2001 Dec. 2002 1997-2000 2000-Dec. 2001 Dec. 2001-Dec. 2002

  27. Change after nourishment LIDAR 2000 September 2002 December 2002

  28. Bald Head Island shore change Historical change ~ 1850 - 1962 Recent change 1998: LIDAR 0m 2000: LIDAR 0m 2001 Dec.: RTK GPS after nourishment after Cleary et al. 1989 800m Shoreline rotates around pivot area

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