Range imaging: a new method for high‐resolution topographic measurements in small‐ and medium‐scale field sites

Nitsche, Manuel; Turowski, Jens M.; Badoux, Alexandre; Rickenmann, Dieter; Kohoutek, Tobias K.; Pauli, Michael; Kirchner, James W.

doi:10.1002/esp.3322

Cited by 21 publications

(21 citation statements)

References 53 publications

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“…However, they remain relatively expensive items of technology and have only recently become truly portable. Thus, much interest remains in acquiring DEM data using much less expensive technologies and the last few years has seen a series of innovative adaptation of imaging systems for geomorphic research, including range imaging (Nitsche et al, 2013) and applications of the Kinect sensor (Mankoff and Russo, 2013). Such methods have proved capable of measuring topographic surfaces with a precision in the mm to cm range as the basis of DEM construction.…”

Section: Introductionmentioning

confidence: 99%

Investigating the geomorphological potential of freely available and accessible structure‐from‐motion photogrammetry using a smartphone

Micheletti

Chandler

Lane

2014

Earth Surf Processes Landf

287

225

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We test the acquisition of high‐resolution topographic and terrain data using hand‐held smartphone technology, where the acquired images can be processed using technology freely available to the research community. This is achieved by evaluating the quality of digital terrain models (DTM) of a river bank and an Alpine alluvial fan generated with a fully automated, free‐to‐use, structure‐from‐motion package and a smartphone integrated camera (5 megapixels) with terrestrial laser scanning (TLS) data used to provide a benchmark. To evaluate this approach a 16.2‐megapixel digital camera and an established, commercial, close‐range and semi‐automated software are also employed, and the product of the four combinations of the two types of cameras and software are compared. Results for the river bank survey demonstrate that centimetre‐precision DTMs can be achieved at close range (10 m or less), using a smartphone camera and a fully automated package. Results improve to sub‐centimetre precision with either higher‐resolution images or by applying specific post‐processing techniques to the smartphone DTMs. Application to an entire Alpine alluvial fan system shows the degradation of precision scales linearly with image scale, but that (i) the expected level of precision remains and (ii) difficulties in separating vegetation and sediment cover within the results are similar to those typically found when using other photo‐based techniques and laser scanning systems. Copyright © 2014 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%

Investigating the geomorphological potential of freely available and accessible structure‐from‐motion photogrammetry using a smartphone

Micheletti

Chandler

Lane

2014

Earth Surf Processes Landf

287

225

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“…Scheidl et al (2008) showed that their calculations mainly correspond to the volume estimates by experts in the field and concluded that ALS is a practical, but expensive method for erosion and deposition analyses. The range imaging cameras (Nitsche et al, , 2012 or photogrammetric cameras (Berger et al, 2010) were applied for smallscale analyses in easily accessible areas. Their application in debris-flow studies is very limited to date.…”

Section: Rickenmannmentioning

confidence: 99%

Methods for detecting channel bed surface changes in a mountain torrent – experiences from the Dorfbach torrent

et al. 2015

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Abstract. The erosion of and depositions on channel bed surfaces are instrumental to understanding debris flow processes. We present an overview of existing field methods and highlight their respective advantages and disadvantages. Terrestrial laser scanning (TLS), airborne laser scanning (ALS), erosion sensors, cross sections (CS) and geomorphological mapping are compared. Additionally, two of these approaches (i.e. TLS and CS) are tested and applied in the channel reaches of the torrent catchments. The results of the comparison indicate that the methods are associated with variable temporal and spatial resolution as well as data quality and invested effort. TLS data were able to quantify small-scale variations of erosion and deposition volumes. While the same changes could be detected with CS and geomorphological mapping, it was only possible with lower precision and coarser spatial resolution. The study presents a range of potential methods that can be applied accordingly to address the objectives and to support the analyses of specific applications. The availability of erosion data, acquired mainly by TLS and ALS, in combination with debris-flow monitoring data, provides promising sources of information to further support torrent risk management.

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“…multiple reflections and surface reflectivity properties) influence the RIM data. A good overview is given in Nitsche et al (2012), yet there is no error model for RIM noise established (Lindner et al 2010). In laboratory experiments with the CamCube 2.0 at the ETH Zurich a distance accuracy of 2-23 mm was determined for measurements on a highly reflective flat surface.…”

Section: Processing and Anaylsis Of The Range Datamentioning

confidence: 99%

“…A higher precision could be achieved when measuring without ambient light. Nitsche et al (2012) presented that random noise can be reduced effectively by taking the median of repeated measurements, which results in significantly reduced distance errors.…”

Section: Processing and Anaylsis Of The Range Datamentioning

confidence: 99%

“…for cultural heritage studies (Chiabrando et al 2010) and the measurement of canopy density (Schulze 2010). Our application is based on the measurements of streambed morphology (Nitsche et al 2010, Nitsche et al 2012) when the used RIM camera was mounted on a lightweight crane. The acquired 3D point clouds have been registered by connecting points that have been measured in a global coordinate system for georeferencing of the scene.…”

Section: Introductionmentioning

confidence: 99%

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Processing of Uav Based Range Imaging Data to Generate Detailed Elevation Models of Complex Natural Structures

Kohoutek

Eisenbeiss

2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission I, WG I/V KEY WORDS: RIM, UAV, tracking, differential GNSS, mapping, DEM/DTM ABSTRACT:Unmanned Aerial Vehicles (UAVs) are more and more used in civil areas like geomatics. Autonomous navigated platforms have a great flexibility in flying and manoeuvring in complex environments to collect remote sensing data. In contrast to standard technologies such as aerial manned platforms (airplanes and helicopters) UAVs are able to fly closer to the object and in small-scale areas of high-risk situations such as landslides, volcano and earthquake areas and floodplains. Thus, UAVs are sometimes the only practical alternative in areas where access is difficult and where no manned aircraft is available or even no flight permission is given. Furthermore, compared to terrestrial platforms, UAVs are not limited to specific view directions and could overcome occlusions from trees, houses and terrain structures. Equipped with image sensors and/or laser scanners they are able to provide elevation models, rectified images, textured 3D-models and maps. In this paper we will describe a UAV platform, which can carry a range imaging (RIM) camera including power supply and data storage for the detailed mapping and monitoring of complex structures, such as alpine riverbed areas. The UAV platform NEO from Swiss UAV was equipped with the RIM camera CamCube 2.0 by PMD Technologies GmbH to capture the surface structures. Its navigation system includes an autopilot. To validate the UAV-trajectory a 360° prism was installed and tracked by a total station. Within the paper a workflow for the processing of UAV-RIM data is proposed, which is based on the processing of differential GNSS data in combination with the acquired range images. Subsequently, the obtained results for the trajectory are compared and verified with a track of a UAV (Falcon 8, Ascending Technologies) carried out with a total station simultaneously to the GNSS data acquisition. The results showed that the UAV's position using differential GNSS could be determined in the centimetre to the decimetre level. The RIM data indicated a high noise level in the measured distance image, due to the vibrations caused by the flight system. Multi-image processing reduced the noise level of the distance image. The produced elevation models from a test area show the high potential of the proposed method for complex structures such as riverbeds.

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Range imaging: a new method for high‐resolution topographic measurements in small‐ and medium‐scale field sites

Cited by 21 publications

References 53 publications

Investigating the geomorphological potential of freely available and accessible structure‐from‐motion photogrammetry using a smartphone

Investigating the geomorphological potential of freely available and accessible structure‐from‐motion photogrammetry using a smartphone

Methods for detecting channel bed surface changes in a mountain torrent – experiences from the Dorfbach torrent

Processing of Uav Based Range Imaging Data to Generate Detailed Elevation Models of Complex Natural Structures

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