High resolution Digital Elevation Model of Merapi summit in 2015 generated by UAVs and TLS
Cite as:
Darmawan, Herlan; Walter, Thomas; Richter, Nicole; Nikkoo, Mehdi (2017): High resolution Digital Elevation Model of Merapi summit in 2015 generated by UAVs and TLS. V. 2015. GFZ Data Services. https://doi.org/10.5880/GFZ.2.1.2017.003
Status
I N R E V I E W : Darmawan, Herlan; Walter, Thomas; Richter, Nicole; Nikkoo, Mehdi (2017): High resolution Digital Elevation Model of Merapi summit in 2015 generated by UAVs and TLS. V. 2015. GFZ Data Services. https://doi.org/10.5880/GFZ.2.1.2017.003
Abstract
This data publication is a high resolution Digital Elevation Model (DEM) generated for the Merapi summit by combining terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) photogrammetry data acquired in 2014 and 2015, respectively. The structures of the data are further analysed in Darmawan et al. 2017 (http://doi.org/10.1016/j.jvolgeores.2017.11.006).
The published datasets consist of combined point clouds with ~65 million data points and a DEM with a resampled resolution of 0.5 m. The DEM data covers the complexity of the Merapi summit with area of 2 km2. The coordinate of the datasets is projected to global coordinates (WGS 1984 UTM Zone 49 South).
TLS is a topography mapping technique which exploits the travel time of a laser beam to measure the range between the ground-based scanning instrument and the earth’s surface. TLS provides high accuracy, precision, and resolution for topography mapping, however, it requires different scan position to obtain accurate topography model in a complex topography. The TLS dataset was acquired by using a long-range RIEGL VZ-6000 instrument with a Pulse Repetition Rate (PRR) of 30 kHz.
The Merapi data includes an observation range of 0.129 – 4393.75 m, a theta range (vertical) of 73 – 120° with a sampling angle of 0.041°, a phi range (horizontal) of 33° - 233° with a sampling angle of 0.05°, and 12 reflectors for each scan. The used TLS dataset was achieved by combining two scan positions, both realized in September 2014. In order to reduce still eminent shadowing, we conducted additionally a UAV photogrammetry survey. The UAV data allows to fill data gaps and generate a complete 3D point cloud.
The UAV photogrammetry was conducted by using DJI Phantom 2 quadcopter drone in October 2015. The drone carried GoPro HERO 3+ camera and a H3-3D gimbal to reduce image shaking. We obtained over 300 images which cover the summit area of Merapi. By applying the Structure from Motion algorithm, we are able to generate a 3D point cloud model of Merapi summit. Further details on this procedure are provided in Darmawan et al. (2017).
Structure from Motion is a technique to generate a 3D model based on 2D overlapped images. The algorithm detects and matches the same ground features of 2D images, reconstructs a 3D scene, and calculates a depth map for each camera frame. The algorithm used is implemented in Agisoft Photoscan Professional software. After importing the images in Agisoft, we used the ‘align image’ function with high accuracy setting to generate 3D sparse point cloud and ‘build dense cloud’ function with high quality to generate 3D dense point cloud.
The 3D point clouds of TLS and UAV photogrammetry were then georeferenced to our georeferenced 3D point cloud which acquired in 2012. The RMS of TLS and UAV photogrammetry during georeferenced is 0.60 and 0.44 m, respectively, as described in Further details on this procedure are provided in Darmawan et al. (2017). After georeferencing, both 3D point clouds were merged and interpolated to a raster format in the ArcMap software.
Authors
Darmawan, Herlan;GFZ German Research Centre for Geosciences, Potsdam, Germany
Walter, Thomas;GFZ German Research Centre for Geosciences, Potsdam, Germany
Richter, Nicole;GFZ German Research Centre for Geosciences, Potsdam, Germany
Nikkoo, Mehdi;GFZ German Research Centre for Geosciences, Potsdam, Germany
Contact
Darmawan, Herlan
(PhD student)
; GFZ German Research Centre for Geosciences, Potsdam, Germany;
affiliation (affiliationIdentifier=0000-0002-5361-5194 affiliationIdentifierScheme=ORCID): GFZ German Research Centre for Geosciences, Potsdam, Germany
affiliation (affiliationIdentifier=0000-0002-9925-4486 affiliationIdentifierScheme=ORCID): GFZ German Research Centre for Geosciences, Potsdam, Germany
creator
creatorName (nameType=Personal): Richter, Nicole
givenName: Nicole
familyName: Richter
affiliation (affiliationIdentifier= affiliationIdentifierScheme=): GFZ German Research Centre for Geosciences, Potsdam, Germany
affiliation (affiliationIdentifier=0000-0002-1077-454X affiliationIdentifierScheme=ORCID): GFZ German Research Centre for Geosciences, Potsdam, Germany
titles
title: High resolution Digital Elevation Model of Merapi summit in 2015 generated by UAVs and TLS
affiliation (affiliationIdentifier=0000-0002-5361-5194 affiliationIdentifierScheme=ORCID): GFZ German Research Centre for Geosciences, Potsdam, Germany
affiliation (affiliationIdentifier=0000-0002-5361-5194 affiliationIdentifierScheme=ORCID): GFZ German Research Centre for Geosciences, Potsdam, Germany
affiliation (affiliationIdentifier=0000-0002-5361-5194 affiliationIdentifierScheme=ORCID): GFZ German Research Centre for Geosciences, Potsdam, Germany
contributor (contributorType=ProjectLeader)
contributorName (nameType=Personal): Walter, Thomas
affiliation (affiliationIdentifier=0000-0002-9925-4486 affiliationIdentifierScheme=ORCID): GFZ German Research Centre for Geosciences, Potsdam, Germany
affiliation (affiliationIdentifier=0000-0002-1077-454X affiliationIdentifierScheme=ORCID): GFZ German Research Centre for Geosciences, Potsdam, Germany
contributor (contributorType=ContactPerson)
contributorName: Darmawan, Herlan
affiliation (affiliationIdentifier= affiliationIdentifierScheme=): GFZ German Research Centre for Geosciences, Potsdam, Germany
CharacterString: This data publication is a high resolution Digital Elevation Model (DEM) generated for the Merapi summit by combining terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) photogrammetry data acquired in 2014 and 2015, respectively. The structures of the data are further analysed in Darmawan et al. 2017 (http://doi.org/10.1016/j.jvolgeores.2017.11.006).
The published datasets consist of combined point clouds with ~65 million data points and a DEM with a resampled resolution of 0.5 m. The DEM data covers the complexity of the Merapi summit with area of 2 km2. The coordinate of the datasets is projected to global coordinates (WGS 1984 UTM Zone 49 South).
TLS is a topography mapping technique which exploits the travel time of a laser beam to measure the range between the ground-based scanning instrument and the earth’s surface. TLS provides high accuracy, precision, and resolution for topography mapping, however, it requires different scan position to obtain accurate topography model in a complex topography. The TLS dataset was acquired by using a long-range RIEGL VZ-6000 instrument with a Pulse Repetition Rate (PRR) of 30 kHz.
The Merapi data includes an observation range of 0.129 – 4393.75 m, a theta range (vertical) of 73 – 120° with a sampling angle of 0.041°, a phi range (horizontal) of 33° - 233° with a sampling angle of 0.05°, and 12 reflectors for each scan. The used TLS dataset was achieved by combining two scan positions, both realized in September 2014. In order to reduce still eminent shadowing, we conducted additionally a UAV photogrammetry survey. The UAV data allows to fill data gaps and generate a complete 3D point cloud.
The UAV photogrammetry was conducted by using DJI Phantom 2 quadcopter drone in October 2015. The drone carried GoPro HERO 3+ camera and a H3-3D gimbal to reduce image shaking. We obtained over 300 images which cover the summit area of Merapi. By applying the Structure from Motion algorithm, we are able to generate a 3D point cloud model of Merapi summit. Further details on this procedure are provided in Darmawan et al. (2017).
Structure from Motion is a technique to generate a 3D model based on 2D overlapped images. The algorithm detects and matches the same ground features of 2D images, reconstructs a 3D scene, and calculates a depth map for each camera frame. The algorithm used is implemented in Agisoft Photoscan Professional software. After importing the images in Agisoft, we used the ‘align image’ function with high accuracy setting to generate 3D sparse point cloud and ‘build dense cloud’ function with high quality to generate 3D dense point cloud.
The 3D point clouds of TLS and UAV photogrammetry were then georeferenced to our georeferenced 3D point cloud which acquired in 2012. The RMS of TLS and UAV photogrammetry during georeferenced is 0.60 and 0.44 m, respectively, as described in Further details on this procedure are provided in Darmawan et al. (2017). After georeferencing, both 3D point clouds were merged and interpolated to a raster format in the ArcMap software.
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;GFZ German Research Centre for Geosciences, Potsdam, Germany
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