*Environmental Earth Science, Hokkaido University study ...
Transcript of *Environmental Earth Science, Hokkaido University study ...
There-dimensional change detection in coastal cliffs using UAV and TLSYuichi S. Hayakawa* & Hiroyuki Obanawa
*Environmental Earth Science, Hokkaido University
2020.05.08 fri
coastal
ßprotection
ß
35°19’11.4”N
140°
04’3
6.6”
E
1 km
Kuju
kuri
Sand
y C
oa
st
Suzume-Jima Island
Cape Taito-Saki
The Isumi
Riveràà
Tokyo
a rare opportunity in Japan: natural rapid processes of coastal erosion
out of the coastal protection oceanic waves directly attacks the bedrock cliff
rapidly shrinking for decades1974 2014
Obanawa et al. 2015
33 m
35 m
35 m
20 m
32 m a.s.l.
1967 1972 1977 1982
1987 1992 1997 2002
2007 2012 • constant erosion• shore platform formation• reported erosion rates around this
site: 1 m/y• (1960–1966 by 1:1,000 topo maps;
Horikawa and Sunamura 1967)
study site: rapidly eroded small coastal island
2
TLS #1: TOPCON GLS-1500a medium-range scanner– max. distance: 500 m– max. frequency: 30,000 pts/s– range accuracy: 4 mm @150 m– weight: 16 kg (body) + batteries
TLS #2: Trimble TX5a short-range scanner– max. distance: 120 m– max. frequency: 900,000 pts/s– range accuracy: 2 mm @25 m–weight: 5 kg
methods
DJI Phantom 2 + NIKON COOLPIX A; Phantom 3 Professional/Advanced; Phantom 4; Mavic Pro; Mavic 2 Pro;
post processing• SfM-MVS photogrammetry
by PhotoScan• 500-1,000 photos for each time• positioning accuracy 1: camera-mounted GNSS, >1 m• positioning accuracy 2: GCP by PPK-GNSS (fix solution)
(Trimble GeoXH), 13.4–14.9 mm (14.4 mm RMS)
• further aligned by ICP– UAS dense cloud à TLS cloud– CloudCompare / Trimble RealWorks– cloud-based registration (ICP), errors: 25.1–39.7 mm 10 m
TLS UAV
TLS + UAV
point cloud
1
TLS
GNSS
point cloud
2
point cloud
N
point cloud
3
...
georeference
ICP
ICP
ICP ......
UAS-SfM
point cloud
1
point cloud
2
point cloud
3
.........point cloud
N
ICP ICP ICP ICP ICP
mes
hing
......mesh
dataset1...N
differentiating
DVE
3methods – workflow
160223160618
pre-point cloud
post-point cloud
calculate cloud-to-cloud distance
invert normals for post dataset
extract changed areas(detectable distance:
10 cm or more)
merge
Poisson surface reconstruction
3D mesh polygons of changed areas
fill holes, repair error faces
make solid
manual removal of erroneous polygons
workflow of Differential Volume Estimate
4results – quantification of volumetric changes was successful!
interval changes 2014.06.24 àà 2019.10.02 I) 140624 àà 141031
II) 141031 àà 150211
III) 150211 àà 150618
IV) 150618 àà 151023
IV) 151023 àà 160223
V) 160223 àà 160618
(southeast) (northeast) (west)
VI) 160618 àà 161029
VII) 161029 àà 170218
VIII) 170218 àà 170702
IX) 1707028 àà 171007
X) 171007 àà 180127
XI) 180127 àà 180916
(southeast) (northeast) (west)
XII) 180916 àà 190311
XIII) 190311 àà 191002
5results – quantification of volumetric changes was successful!
total changes 2014.06.24 àà 2019.10.02
total volume loss: 1,980 m3
average volume loss per month: 30 m3
current volume of the island: 11,300 m3
estimated time to fully eroded: ca. 30 years
6discussion – effects of waves
temporal variations: frequency of high tidal waves and erosion mass volume
• mass volume varies, 10.6 – 527.7 m3 per 4-7 months• equivalent annual erosion rates: 0.03 – 0.63 m/y• cf. approx. projected area of bedrock: 1,436 m2
< Ty
pho
on
Faxa
i>
volume
erosionrate y = 5.128x + 19.056
R² = 0.1136
0
100
200
300
400
500
600
0 10 20 30 40 50
ero
de
d v
olu
me
in a
pe
riod
(m
3 )
number of observation of waves over 3 m high
spatial variations: differences in wave attacks
refraction
ßß shore platform
N S
E
W
different directions of wave attacks for the cliff faces of the island could cause differences in the amount of erosion
although the relation is not clear, attacks by high tidal waves could have affected the amount of erosion