preliminary results on high accuracy estimation of shoreline change rate based on coastal elevation...

PPreliminary Results on High Accuracy reliminary Results on High Accuracy Estimation of Shoreline Change Rate Based on Estimation of Shoreline Change Rate Based on

Coastal Elevation ModelsCoastal Elevation Models

Research Project RNM 3575: Multisource Geospatial Data

Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and

Vulnerability

http://www.ual.es/GruposInv/ProyectoCostas/index.htm

F.J. AguilarF.J. Aguilaraa, I. Fernández, I. Fernándezaa, J.L. Pérez, J.L. Pérezbb, A. López, A. Lópezaa, M.A. , M.A. AguilarAguilaraa

A. MozasA. Mozasbb, J. Cardenal, J. Cardenalbb aa Dept. of Agricultural Engineering, Almería University, Spain Dept. of Agricultural Engineering, Almería University, Spain

bb Dept. of Cartographic Engineering, Geodesy and Photogrammetry, Jaén Dept. of Cartographic Engineering, Geodesy and Photogrammetry, Jaén University, SpainUniversity, Spain

Kyoto, Japan. 10 August Kyoto, Japan. 10 August 20102010

Corresponding Author: F.J. Aguilar Corresponding Author: F.J. Aguilar ([email protected])([email protected])



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INTRODUCTION

SHORELINE EXTRACTION METHODS

STUDY SITE, DATASETS & METHODOLOGY

RESULTS & DISCUSSION

CONCLUSIONS

1

Detailed coastal topographic information will be the key variable in understanding the likely impacts of global anthropogenic and natural hazards (including SLR due to Climate Change).

The shoreline is one of the most important and critical indicators of coastal evolution and vulnerability



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INTRODUCTION




CONCLUSIONS

Urban development on the coastal area and resource use conflicts spawn environmental degradation and increasing hazard vulnerability. In Spain, more than 44% population are now living in coastal areas (7% of territory)

Anthropic Pressure

Increase of urban areas (soil sealing and change of ISA)

Shortage of planning

Sand extraction to attend the demand from greenhouse crops

2



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INTRODUCTION




CONCLUSIONS

3

Yes but, How to extract the shoreline? Some of the methods are based on the intersection between the Coastal Elevation Model (CEM) and the plane corresponding to the chosen tidal datum

An open coast tide station very close to our working coastal area is needed to accurately estimate its MHW

Sometimes it is recommendable to use as a more reliable vertical reference the Mean Sea Level (MSL) tidal datum



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INTRODUCTION




CONCLUSIONS

4

1. A classic approach: the Cross-Shore Profile method (CSP) (e.g. Stockdon et al., 2002*)

0 10 20 30 40 50 60 70-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Shoreline distance (m)

Hei

ght

abov

e M

SL

(m)

R2 = 0.98

* Stockdon, H.F., Sallenger, A.H., List, J.H., Holman, R.A., 2002. Estimation of shoreline position and change using airborne topographic Lidar data. Journal of Coastal Research, 18(3), pp. 502-513.

0 10 20 30 40 50 60 70-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Shoreline distance (m)

Hei

ght

abov

e M

SL

(m)



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INTRODUCTION




CONCLUSIONS

5

But most of times the results are not as we wish

R2 = 0.33

1. A classic approach: the Cross-Shore Profile method (CSP)

0.68 0.58 0.48

0.44 0 0

0 0 0

-0.24 -0.23 -0.23 -0.10 -0.11 -0.11

-0.24 -0.24 -0.23 -0.10 -0.11 0

-0.24 -0.24 0 -0.10 -0.10 0

1 1 1 1 0 -1

0 0 0 1 0 -1

-1 -1 -1 1 0 -1

Previouslycomputed Gy

PreviouslyComputed Gx

Heights of initial grid CEM 3x3 window (Matrix M). Central pixel is the height toextrapolate

Δi matrix Δj matrix

0.68 0.58 0.48

0.44 0.3475 0

0 0 0

0.34 0.350.36

0.34Average of thefour propagatedvalues



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INTRODUCTION




CONCLUSIONS

6

2. Our approach: the Elevation Gradient Trend Propagation method (EGTP)

121

000

121-

Zz

;

101-

202-

101-

Zxz

y

ji

yz

xz

G



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INTRODUCTION




CONCLUSIONS

7


1.852 1.818 1.785 1.760 1.737 1.714 1.691 1.658 1.624

1.763 1.730 1.698 1.677 1.654 1.631 1.610 1.578 1.487

1.675 1.642 1.615 1.594 1.571 1.548 1.460 1.347 1.222

1.585 1.555 1.532 1.481 1.381 1.280 1.180 1.072 0.959

1.497 1.404 1.303 1.201 1.100 1.000 0.899 0.793 0.680

1.268 1.169 1.044 0.922 0.820 0.719 0.619 0.513 0.400

1.026 0.927 0.825 0.696 0.569 0.440 0.337 0.233 0

0.783 0.686 0.589 0.478 0.323 0.186 0.064 -0.046 0

0.541 0.444 0.352 0.247 0.133 -0.048 -0.195 -0.312 0

0 0.202 0.104 0.012 -0.097 -0.211 0 0 0

0 -0.040 -0.138 -0.235 0 0 0 0 0

0 0 0 0 0 0 0 0 0



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INTRODUCTION




CONCLUSIONS

8



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INTRODUCTION




CONCLUSIONS

9

Main wave direction East-West

Average wave height 1 m

Maximum wave height 5 m

Maximum tide range (microtidal coast)

0.5 m

ALMANZORA RIVER MOUTH



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INTRODUCTION




CONCLUSIONS

10

Data corresponding to 2001 come from an analogic RGB photogrammetric flight at an approximated scale of 1:5000 taken on 9 April 2001. 1 m grid-spacing CEM was carried out by means of stereo matching techniques ranking over previously digitized images and subsequent exhaustive and careful edition by one operator (SOCET SET® environment). The estimated vertical accuracy of the photogrammetrically-derived CEM was around 30 cm



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INTRODUCTION




CONCLUSIONS

11

Data corresponding to 2009 come from a combined flight

General information Height above ground: 1000 mNumber of strips: 4Number of photographs: 86

Digital camera DMC (Digital Mapping Camera) IntergraphGSD (cm) 10RGB+Nir (12 bits)Forward overlap (%) 65Side overlap (%) 60

LiDAR sensorALS60 LEICAFOV (º) 35Max. laser pulse Rate (Hz) 96100Max. point spacing across track(m) 1,33Max. point spacing along track (m) 1,46Average point density (points/m2) 1,61Average point space (m) 0,79Average point area (m2) 0,62Estimated height accuracy (m) 0,08



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INTRODUCTION




CONCLUSIONS

12

Methodology to compute the corresponding shoreline change rate between 2001 and 2009

End Point Rate (EPR) Computation (m/year) erosion (-) or accretion (+)

BAd

dBA

XsXsdABd

d

td

-XsXsd-μd

tBA

05.00

22

ˆ0:H

;ˆ ;ˆ

95% confidence level

T2

22

BA XsXsEPR

http://woodshole.er.usgs.gov/project-pages/dsas/images/inputs_b.jpg



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INTRODUCTION




CONCLUSIONS

13

Performance of the Two Tested Shoreline Mapping Methods

Year Transects lost Uncertainty (σxs)

CSP EGTP CSP EGTP

2001 12.84% 3.19% 2.95 4.10 m

2009 12.18% 1.54% 1.05 m 1.48 m

CSP method seems to be quite sensitive to noise due to an incorrect separation between water and land, unexpected artifacts along foreshore profile or actually non-straight profiles.

EGTP can be deemed as much more robust than CSP, maintaining a greater number of useful transects

Source of variation Degrees of freedom

Sum of squares F Signific. (p<0.05)

Method (A) 1 0.659 0.853 0.355

Tidal datum (B) 1 0.037 0.048 0.826

Transect spacing (C)

2 1.073 0.694 0.499

Zone (D) 28 33809.29 1562.34 <0.001*

A*B 1 0.134 0.174 0.676

A*C 2 0.834 0.539 0.582

B*C 2 0.085 0.055 0.946

A*B*C 2 0.0292 0.037 0.962

A*D 25 66.756 3.455 <0.001*

B*D 28 49.099 2.268 <0.001*

A*B*D 25 9.991 0.517 0.977

C*D 56 41.945 0.969 0.540

A*C*D 47 5.744 0.158 1

B*C*D 56 1.802 0.041 1

A*B*C*D 47 1.003 0.0.027 1

Error 12412 9592.72



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INTRODUCTION




CONCLUSIONS

14

Quantitative Analysis (ANOVA where EPR is the explained variable)

A (method) = CSP and EGTP

B (tidal datum) = MSL and MHW

C (transect spacing) = 5 m, 10 m and 20 m

D (Zone) = 29 homogeneous areas




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INTRODUCTION




CONCLUSIONS

15Kyoto, Japan. 10 August Kyoto, Japan. 10 August

20102010

Zone EPR (m/year) Useful transects EPR (m/year) Useful transects

Method CSP Method EGTP1 0 3 -0.95 162 ----- ---- -0.03 93 3.77 9 2.91 104 0 1 -0.19 95 -0.40 17 -0.34 156 0 14 0 157 0.28 8 0.09 88 ---- ---- 0.27 39 -0.10 15 -0.28 2110 2.50 8 2.39 1411 ---- ---- 0 512 ---- ---- -3.97 413 3.46 4 3.85 2414 0.30 13 0.12 1815 1.72 2 1.46 716 -0.09 16 -0.13 2917 -1.07 20 -1.01 2618 3.76 94 3.64 12219 2.84 52 2.92 5620 -2.16 82 -2.12 8221 0 23 0 2322 2.02 96 1.90 8423 0.27 24 0.30 2024 -0.58 102 -0.30 10225 -0.07 58 -0.16 6026 -1.38 43 -1.10 4227 2.05 25 1.98 2928 -2.17 75 -2.17 5929 0 47 -0.04 47

Average 0.39 851 0.55 959



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INTRODUCTION




CONCLUSIONS


20102010

ORTHOPHOTO 2009

PUNTA DE LOS HORNICOS

1989

2001

2009



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INTRODUCTION




CONCLUSIONS


20102010

PALOMARES BEACH

VERA BEACH

1989

2009

2001



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INTRODUCTION




CONCLUSIONS


20102010

VERA BEACH

1989

2009

2001

ACCRETION

EROSION



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INTRODUCTION




CONCLUSIONS


20102010

QUITAPELLEJOS BEACH



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INTRODUCTION




CONCLUSIONS


20102010

• The new grid-based approach can be strongly recommended because its precision, local slope acquisition, robustness regarding the presence of noise and outliers, and capability to deal with very curved and even closed coastal features.

• The preliminary results also indicate that, though the global rate-of-change for the whole coastline between 2001 and 2009 may be catalogued as relatively low (0.55 ± 0.50 m/year of net accretion), the local results for every one of the 29 homogeneous units considered have been extremely variable and statistically significant.

• Many local phenomena, registered in a short-term period and mainly due to human activities such as the presence of new engineered structures and artificial beach regeneration, may strongly affect the shoreline evolution in certain and localized areas



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INTRODUCTION




CONCLUSIONS


20102010

Thank you very much for your kind attention

2009 LiDAR data. Vertical Accuracy

Average dz +0.029 Minimum dz -0.284 Maximum dz +0.180 Std deviation 0.089N = 62

2009 LiDAR data. Vertical Accuracy

tgα

ez

Ground truth

MDE

elc MSL

tg

ee z

lc

HIGH WATER LINE


INTRODUCTION




CONCLUSIONS

2

,

,2

,

bba

baaba Cov

CovD

baxz

ˆ

)ˆ(),( 2

ˆˆ

)ˆ(32

2b

4

22a2

regression xs abm

baCovaa

bm

LEAST SQUARES ESTIMATION

ˆ 2

22

az

regressionxsxs

Theoretical framework to estimate the point shoreline error (xs) propagated from CSP method

FUNCTIONAL MODEL

1. A classic approach: the Cross-Shore Profile method (CSP)


INTRODUCTION




CONCLUSIONS

9


Computed uncertainty for the shoreline determination

2 z

2propagated

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22

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2propagated

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slope

slope

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B

preliminary results on high accuracy estimation of shoreline change rate based on coastal elevation...

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