#1There-dimensional change detection in coastal cliffs using UAV and TLS study site: rapidly eroded small coastal island 2020.05.08 fri Yuichi S. Hayakawa* & Hiroyuki Obanawa *Environmental Earth Science, Hokkaido University 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 decades 35 19 11.4 N Tokyo 14C 04 36.6, E The isumi River → 1974 (Suzume-jima) Shooting date: 31/12/1974 Flight altitude: 1416 m Original scale: 1/8,000 Suzume-Jima Island 1967 Cape Taito-Saki 1 km coastal protection 2014 35 m 20 m 32 m a.s.l. 33 m 35 m Obanawa et al. 2015 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)#2methods TLS TLS #1: TOPCON GLS-1500 a 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 TX5 a short-range scanner max. distance: 120 m max. frequency: 900,000 pts/s range accuracy: 2 mm @25 m weight: 5 kg • . UAV DJI Phantom 2+ NIKON COOLPIX A; Phantom 3 Professional/Advanced; Phantom 4; Mavic Pro; Mavic 2 Pro; Single-point positioning GNSS unit post processing Digital camera 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) TLS + UAV . further aligned by ICP - UAS dense cloud → TLS cloud - CloudCompare / Trimble RealWorks - cloud-based registration (ICP), errors: 25.1 39.7 mm 10 m 2#3methods workflow TLS point cloud point point point cloud cloud cloud 2 3 N georeference GNSS ICP ICP ICP ICP ICP point point point cloud cloud cloud 1 2 3 N UAS-SfM workflow of Differential Volume Estimate pre- point cloud post- point cloud 160223 160618 calculate cloud-to-cloud distance point cloud mesh dataset 1...N DOME differentiating extract changed areas (detectable distance: 10 cm or more) DVE invert normals for post dataset merge Poisson surface reconstruction fill holes, repair error faces make solid manual removal of erroneous polygons 3D mesh polygons of changed areas 3#4results quantification of volumetric changes was successful! interval changes 2014.06.24 → 2019.10.02 I) 140624141031 VII) 161029 → 170218 (southeast) (northeast) (west) II) 141031 → 150211 (southeast) VIII) 170218 → 170702 (northeast) (west) III) 150211 → 150618 IV) 150618 → 151023 IV) 151023 ⇒ 160223 V) 160223 → 160618 IX) 1707028171007 X) 171007 → 180127 XI) 180127180916 XII) 180916 190311 VI) 160618 161029 XIII) 190311 → 191002 4#5results quantification of volumetric changes was successful! total changes 2014.06.24 → 2019.10.02 5 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#6500.0 discussion effects of waves spatial variations: differences in wave attacks N refraction E W shore platform S 6 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 temporal variations: frequency of high tidal waves and erosion mass volume 600.0 400.0 eroded mass volume (m^3) 300.0 200.0 100.0 0.0 Jun. 10, 2014 Dec. 27, 2014 Jul. 15, 2015 Jan. 31, 2016 erosion rate volume Aug. 18, 2016 Mar. 6, 2017 . 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 Sep. 22, 2017 Apr. 10, 2018 Oct. 27, 2018 May. 15, 2019 < Typhoon Faxai > Dec. 1, 2019 0.700 0.600 0.500 0.400 mean erosion rate (m/y) 0.300 0.200 0.100 0.000 600 500 eroded volume in a period (m³) 400 y = 5.128x+19.056 300 R2 = 0.1136 200 100 10 20 30 number of observation of waves over 3 m high 40 50