Shinjiro TOMIZAWA and Tomozou ONO KGPS DL GPS/IMU Inertial Measurement Unit SHOALS GCS Auto Process Fledermaus DGPS KGPS DGPS Fledermaus Mapper m SOUN

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1 REPORT OF HYDROGRAPHIC AND OCEANOGRAPHIC RESEARCHES No.50 March, 2013 Analysis with airborne LIDAR data Shinjiro TOMIZAWA and Tomozou ONO Abstract Japan Coast Guard has been working about how to incorporate airborne LIDAR light detection and ranging data to nautical charts while operating the airborne LIDAR system SHOALS. In order to use airborne LIDAR data to nautical charts, not only knowledge and experience of the hydrographic survey but also understanding the characteristics of the airborne LIDAR data are necessary. We describe the analysis methods for airborne LIDAR data in the Japan Coast Guard. SHOALS SHOALS Ground Control System GCS GIS SHOALS GCS DGPS Differential Global Positioning System KGPS Kinematic Global Positioning System DGPS Z SHOALS GCS Auto Process Fledermaus Hydrographic Survey Division 65

2 Shinjiro TOMIZAWA and Tomozou ONO KGPS DL GPS/IMU Inertial Measurement Unit SHOALS GCS Auto Process Fledermaus DGPS KGPS DGPS Fledermaus Mapper m SOUNDG_ m SOUNDG_ m DGPS DGPS OmniStar Infrared Green Infrared Fig Conceptual diagram of depth analyses for DGPS and KGPS method in SHOALSsystem. Fig Z Z Z DGPS SHOALS GCS Z Z SHOALS GCS.tid Z ZSHOALS GCS Z 66

3 Analysis with airborne LIDAR data SHOALS GCS Auto Process.tid Z SHOALS GCS Auto Process Fledermaus Auto Process Fledermaus GPS /IMU GNSS Global Navigation Satellite System GNSS KGPS Fig GPS Datum Level DL DL DL DL DL Bench MarkBM Z DL DL BM Fig Fig Positions of Geoid, DL and BM, referred to the geodetic ellipsoid. DL km DL DL m DL DL DL SHOALS GCS DL DL m Fig DL SHOALS GCS GPS/IMU KGPS GPS/IMU GNSS SBET Smoothed Best Estimated Trajectory 67

Shinjiro TOMIZAWA and Tomozou ONO SHOALS GCS Auto Process DL SBET SHOALS GCS Auto Process DGPS Auto Process Fig An example of ellipsoidal DL height zone file. Black lines indicate the ENC data.

4 Shinjiro TOMIZAWA and Tomozou ONO SHOALS GCS Auto Process DL SBET SHOALS GCS Auto Process DGPS Auto Process Fig An example of ellipsoidal DL height zone file. Black lines indicate the ENC data. The white dashed lines show the ellipsoidal DL height zone. Applanix POSPac MMS Mobile Mapping SuitePOSPac MMS SBET GPS/IMU GPS/IMU GPS IMU GPS IMU SBET SBET SBET SBET Fledermaus Auto Process Fledermaus Latitude Longitude Depth LMD Hypack Caris LMD Mapper Sort Mapper m Hypack Mapper Mapper 68

5 Analysis with airborne LIDAR data mm mm Mapper SOUNDG_ m Mapper m m Sort Sort m Sort SOUNDG_ m Fig An example of noise data found in contour map. The noise data remain in two red circles. SWA SOUNDG_ m SOUNDG_ m SOUNDG _ m SOUNDG_ m SOUNDG_ m SOUNDG_ m SOUNDG_ m Fig SWA Shallow Water Algorism SOUNDG_ m SOUNDG_ m 69

6 Shinjiro TOMIZAWA and Tomozou ONO SOUNDG_ m SOUNDG_ m SOUNDG_ SOUNDG_ SOUNDG_ mm SOUNDG_ SOUNDG_ m SOUNDG _ m SOUNDG_ m m SOUNDG_ SOUNDG_m SOUNG_ SOUNDG_Auto Contour SOUNDG_ Auto Contour m m Z GIS GIS DXF Shape GIS GIS Auto Contour 70

7 Analysis with airborne LIDAR data GIS m m SOUNDG_ SOUNDG_ m SOUNDG_ SOUNDG_ ArcGIS SHOALS Auto Process Fledermaus 71

Shinjiro TOMIZAWA and Tomozou ONO SHOALS Deep Greennm m m m Shallow Greennm m m m Infrared nmramannm Fig nsec Deep Green nsec Shallow Green nsec SHOALS Shallow Green Raman Infrared Primary Depth

8 Shinjiro TOMIZAWA and Tomozou ONO SHOALS Deep Greennm m m m Shallow Greennm m m m Infrared nmramannm Fig nsec Deep Green nsec Shallow Green nsec SHOALS Shallow Green Raman Infrared Primary Depth Secondary Depth Primary Depth Fig An example of observed waveforms by SHOALS system. Blue tick marks indicate arrival times of reflection at seafloor. Red tick marks show the secondary candidate of seafloor. Yellow tick marks in the displays of Shallow Green and Raman denote sea surface reflections and those in the Infrared display are reflections from sea surface or ground. See text for detail. Fig Primary Depth Shallow Green Secondary Depth Infrared Fig 72

9 Analysis with airborne LIDAR data Fig Right An example of observed waveforms in which sea surface was incorrectly determined as land. These waveforms were measured at the center of the red frame in the left photo. Whitecap was identified in the photo. The Infrared waveform in a yellow circle is saturatedleft Photo of the sea surface, taken at the same time of the LIDAR survey. Infrared Deep Green Shallow Green Infrared Infrared Infrared Fig Infrared Fig Raman Deep Green Shallow Green Fig Green Fig Deep 73

Fig An example of observed waveforms produced by suspended solids in the sea.

10 Shinjiro TOMIZAWA and Tomozou ONO Fig Right An example of observed waveforms with smooth sea surface such as calm water. Reflection signals in the Infrared waveform are not detected in the yellow circle. Fig An example of observed waveforms produced by suspended solids in the sea. The reflection in the left and right yellow circle corresponds to a fishnet and seafloor, respectively. Green Deep Green Shallow Green 74

ＬＳｅｒｖｅｒ勝美印刷海洋情報部研究報告第５０号本文技報１ 2013.03.12 17.26.35 Page 95 Analysis with airborne LIDAR data Fig ９ An example of observed waveforms with cloudy water.

11 ＬＳｅｒｖｅｒ勝美印刷海洋情報部研究報告第５０号本文技報１ Page 95 Analysis with airborne LIDAR data Fig ９ An example of observed waveforms with cloudy water. The reflection peak in the yellow circle was smooth. Fig １１ A harmful effect of specially cloudy and muddy water on determination of seafloor Top ３D image of specially cloudy and muddy water. Gray colored dots indicate wrong seafloor caused by muddy water Bottom ２D image of specially cloudy and muddy water. 説明と対処透明度の悪い海域で計測した点の反射波形の例を Fig ９に透明度の良い海域で計測した点の反射波形の例を Fig １０に示す透明度の悪い水では後方散乱が大きく生じてレーザーのエネルギーが散乱し Fig ９の黄色い円で示すように海底反射のピークが不明瞭となるそのため誤った水深を計算する場合があるその例として河川から流入する泥水など極度に濁った汚濁水の水塊 Fig １０ An example of observed waveforms with clear water. The reflection peak in the yellow circle was sharp. を面的に海底として誤認してしまう場合がある Fig １１は同じ場所を三次元表示と横からの断面表示で表しておりグレーで表示された計測点が濁った水塊である大きな川の河口付近等の濁っ形が海面反射の後から上方へ膨らんでおり反射た海域の計測データは解析時に特に注意し計測波形のピークが識別しづらい計測時に撮影した時に撮影した写真や周囲のデータとの連続性を確写真上で周辺海域の水が濁っている認しノイズを除去する 75

Shinjiro TOMIZAWA and Tomozou ONO Deep Green Shallow Green Fig Green Fig SHOALS GCS Primary Depth Secondary Depth Primary Depth Second depth swap tool Second depth swap tool Primary Depth Secondary

12 Shinjiro TOMIZAWA and Tomozou ONO Deep Green Shallow Green Fig Green Fig SHOALS GCS Primary Depth Secondary Depth Primary Depth Second depth swap tool Second depth swap tool Primary Depth Secondary Depth Shallow Green Deep Green Green m Shallow Green Fig An example of observed waveforms with several peaks produced by multiple reflection at seafloor. The reflection in the right yellow circle indicates primary depth. The reflection in the left yellow circle was secondary depth. Fig An example of observed waveforms with overlapped peaks in very shallow water. The left and right peaks in the yellow circle correspond to reflections from sea surface and seafloor, respectively. 76

Analysis with airborne LIDAR data Fig Right Picture taken at the same time of the LIDAR survey. Whitecaps and several characteristic land topography are shown in red circle.

13 Analysis with airborne LIDAR data Fig Right Picture taken at the same time of the LIDAR survey. Whitecaps and several characteristic land topography are shown in red circle. LeftD image of bathymetric data. Point cloud in the red circle is measured due to harmful effects detected in the right picture. Fig Shallow Green Detector Fig Fig Infrared Infrared SWA Shallow Water Algorism SWA SHOALS GCS Shallow Green SWA 77

14 Shinjiro TOMIZAWA and Tomozou ONO Shallow Green Detector SWA SWA Shallow Green Sort Sort Sort Deep Green Fig Deep Green m Fig An example of observed waveforms without seafloor reflection because of too clean water. There is no reflection in the yellow circle. SHOALS Fig 78

15 Analysis with airborne LIDAR data Infrared Fig Conceptual diagram of flight direction in the LIDAR survey with irregular topography. Fledermaus Detector SWA SHOALS 79

本文　４校／■７

本文　４校／■７ 49 24 12 20 REPORT OF HYDROGRAPHIC AND OCEANOGRAPHIC RESEARCHES No.49 December, 2012 Hydrographic surveys Hydrographic Survey Team responding to Disasters Abstract After emergent obstruction surveys to