scholarly journals Strengths and Limitations of UAV and Ground-based Structure from Motion Photogrammetry in a Gullied Savanna Catchment

2017 ◽  
Author(s):  
Jack Koci ◽  
Javier X. Leon ◽  
Ben Jarihani ◽  
Roy C. Sidle ◽  
Scott N. Wilkinson ◽  
...  
Keyword(s):  
High Resolution ◽  
Structure From Motion ◽  
Digital Camera ◽  
Cost Effective ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Tropical Savanna ◽  
Ground Survey ◽  
Rtk Gps ◽  
Point Data

Structure from Motion with Multi-View Stereo photogrammetry (SfM) is increasingly utilised in geoscience investigations as a cost-effective method of acquiring high resolution (sub-meter) topographic data, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via an Unmanned Aerial Vehicle, ‘UAV’) and ground-based (via a handheld digital camera, ‘Ground’) SfM in modelling a hillslope gully system in dry-tropical savanna, and to assess the strengths and limitations of the approach at different scales. A UAV survey covered an entire hillslope gully system (0.715 km2), whereas a Ground survey covered a single gully within the broader system (650 m2). SfM topographic models, including Digital Surface Models (DSM) and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM). Results indicate UAV SfM can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., 0.1 m resolution with ~ 0.5 – 1.3 m elevation error), while ground-based SfM is more capable of quantifying gully morphology (e.g., 0.01 m resolution with ~ 0.1 m elevation error). Key strengths of SfM for these applications include: the production of high resolution 3D topographic models and ortho-photo mosaics, low survey instrument costs (< $AUD 3,000); and rapid survey time (4 and 2 hours for UAV and Ground survey respectively). Current limitations of SfM include: difficulties in reconstructing vegetated surfaces; uncertainty as to optimal survey and processing designs; and high computational demands. Overall, this study has demonstrated great potential for SfM to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in tropical savanna landscapes and elsewhere.

scholarly journals Evaluation of the Apple iPhone 12 Pro LiDAR for an Application in Geosciences

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregor Luetzenburg ◽  
Aart Kroon ◽  
Anders A. Bjørk
Keyword(s):  
High Resolution ◽  
Optical Sensors ◽  
Cost Effective ◽  
Point Clouds ◽  
3D Models ◽  
Absolute Accuracy ◽  
Wide Range ◽  
Financial Investments ◽  
Coastal Cliff ◽  
High Resolution Models

AbstractTraditionally, topographic surveying in earth sciences requires high financial investments, elaborate logistics, complicated training of staff and extensive data processing. Recently, off-the-shelf drones with optical sensors already reduced the costs for obtaining a high-resolution dataset of an Earth surface considerably. Nevertheless, costs and complexity associated with topographic surveying are still high. In 2020, Apple Inc. released the iPad Pro 2020 and the iPhone 12 Pro with novel build-in LiDAR sensors. Here we investigate the basic technical capabilities of the LiDAR sensors and we test the application at a coastal cliff in Denmark. The results are compared to state-of-the-art Structure from Motion Multi-View Stereo (SfM MVS) point clouds. The LiDAR sensors create accurate high-resolution models of small objects with a side length > 10 cm with an absolute accuracy of ± 1 cm. 3D models with the dimensions of up to 130 × 15 × 10 m of a coastal cliff with an absolute accuracy of ± 10 cm are compiled. Overall, the versatility in handling outweighs the range limitations, making the Apple LiDAR devices cost-effective alternatives to established techniques in remote sensing with possible fields of application for a wide range of geo-scientific areas and teaching.

scholarly journals Structure from Motion Multisource Application for Landslide Characterization and Monitoring: The Champlas du Col Case Study, Sestriere, North-Western Italy

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2364 ◽  
Author(s):  
Martina Cignetti ◽  
Danilo Godone ◽  
Aleksandra Wrzesniak ◽  
Daniele Giordan
Keyword(s):  
Structure From Motion ◽  
Winter Season ◽  
Cost Effective ◽  
Point Clouds ◽  
Slope Instability ◽  
Ski Resorts ◽  
Area Of Interest ◽  
3D Point Clouds ◽  
North Western

Structure from Motion (SfM) is a powerful tool to provide 3D point clouds from a sequence of images taken from different remote sensing technologies. The use of this approach for processing images captured from both Remotely Piloted Aerial Vehicles (RPAS), historical aerial photograms, and smartphones, constitutes a valuable solution for the identification and characterization of active landslides. We applied SfM to process all the acquired and available images for the study of the Champlas du Col landslide, a complex slope instability reactivated in spring 2018 in the Piemonte Region (north-western Italy). This last reactivation of the slide, principally due to snow melting at the end of the winter season, interrupted the main road used to reach Sestriere, one of the most famous ski resorts in north-western Italy. We tested how SfM can be applied to process high-resolution multisource datasets by processing: (i) historical aerial photograms collected from five diverse regional flights, (ii) RGB and multi-spectral images acquired by two RPAS, taken in different moments, and (iii) terrestrial sequences of the most representative kinematic elements due to the evolution of the landslide. In addition, we obtained an overall framework of the historical development of the area of interest, and distinguished several generations of landslides. Moreover, an in-depth geomorphological characterization of the Champlas du Col landslide reactivation was done, by testing a cost-effective and rapid methodology based on SfM principles, which is easily repeatable to characterize and investigate active landslides.

scholarly journals High-Resolution Structure-from-Motion for Quantitative Measurement of Leading-Edge Roughness

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3916 ◽  
Author(s):  
Mikkel Schou Nielsen ◽  
Ivan Nikolov ◽  
Emil Krog Kruse ◽  
Jørgen Garnæs ◽  
Claus Brøndgaard Madsen
Keyword(s):  
High Resolution ◽  
Wind Turbine ◽  
Structure From Motion ◽  
Turbine Blades ◽  
Leading Edge ◽  
Cost Effective ◽  
Wind Turbine Blades ◽  
Edge Roughness ◽  
High Resolution Structure ◽  
Resolution Structure

Over time, erosion of the leading edge of wind turbine blades increases the leading-edge roughness (LER). This may reduce the aerodynamic performance of the blade and hence the annual energy production of the wind turbine. As early detection is key for cost-effective maintenance, inspection methods are needed to quantify the LER of the blade. The aim of this proof-of-principle study is to determine whether high-resolution Structure-from-Motion (SfM) has the sufficient resolution and accuracy for quantitative inspection of LER. SfM provides 3D reconstruction of an object geometry using overlapping images of the object acquired with an RGB camera. Using information of the camera positions and orientations, absolute scale of the reconstruction can be achieved. Combined with a UAV platform, SfM has the potential for remote blade inspections with a reduced downtime. The tip of a decommissioned blade with an artificially enhanced erosion was used for the measurements. For validation, replica molding was used to transfer areas-of-interest to the lab for reference measurements using confocal microscopy. The SfM reconstruction resulted in a spatial resolution of 1 mm as well as a sub-mm accuracy in both the RMS surface roughness and the size of topographic features. In conclusion, high-resolution SfM demonstrated a successful quantitative reconstruction of LER.

scholarly journals Preparation of High-Resolution DTM and Orthophoto Using LiDAR in Nepal

2020 ◽  
Vol 20 (1) ◽  
pp. 75-80
Author(s):  
Abhash Joshi ◽  
Sumeer Koirala
Keyword(s):  
Economic Development ◽  
High Resolution ◽  
Digital Terrain Model ◽  
Cost Effective ◽  
Interval Data ◽  
Development Planning ◽  
Airborne Lidar ◽  
Grid Data ◽  
Terrain Model ◽  
Surveying And Mapping

The high-resolution terrain model has varied usages including development planning, engineering works, environmental management, disaster management, urban planning, irrigation, geological study, archeological study and cadastral application. Currently, this data is not available for Nepal and it has also hindered the socio and economic development of the country. Airborne Lidar is economically cost-effective and viable means for topography related data collection. Lidar which is an acronym for Light Detection and Ranging is an active remote sensing technology in which Laser beams are used for surveying and mapping. The Survey Department of Nepal has taken initiative to prepare the High-Resolution DTM and Orthophoto of about 20,000 square kilometres of Nepal using Lidar surveying and mapping. Survey Department is conducting a LiDAR survey in the western terai regions of Nepal from Chitwan to Kanchanpur district. Airborne LiDAR survey data along with a very high resolution (0.15 m) orthophoto shall be generated. Further, processing of LiDAR points data will generate a highly precise digital terrain model of 1 m grid data having an accuracy of 0.25 m and finally 0.5 m contour interval data. This endeavor is one of the milestones in the surveying and mapping sector of Nepal and it will have far-reaching consequence in the social and economic development of Nepal.

scholarly journals Urban Feature Extraction from Merged Airborne LiDAR Data and Digital Camera Data

2021 ◽  
Vol 7 (2) ◽  
pp. 57-74
Author(s):  
Lamyaa Gamal EL-Deen Taha ◽  
A. I. Ramzi ◽  
A. Syarawi ◽  
A. Bekheet
Keyword(s):  
Neural Network ◽  
Digital Camera ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Surface Model ◽  
Digital Surface Model ◽  
3D Point Clouds ◽  
Digital Elevation ◽  
Surface Models ◽  
Elevation Model

Until recently, the most highly accurate digital surface models were obtained from airborne lidar. With the development of a new generation of large format digital photogrammetric aerial camera, a fully digital photogrammetric workflow became possible. Digital airborne images are sources for elevation extraction and orthophoto generation. This research concerned with the generation of digital surface models and orthophotos as applications from high-resolution images.  In this research, the following steps were performed. A Benchmark data of LIDAR and digital aerial camera have been used.  Firstly, image orientation, AT have been performed. Then the automatic digital surface model DSM generation has been produced from the digital aerial camera. Thirdly true digital ortho has been generated from the digital aerial camera also orthoimage will be generated using LIDAR digital elevation model (DSM). Leica Photogrammetric Suite (LPS) module of Erdsa Imagine 2014 software was utilized for processing. Then the resulted orthoimages from both techniques were mosaicked. The results show that automatic digital surface model DSM that been produced from digital aerial camera method has very high dense photogrammetric 3D point clouds compared to the LIDAR 3D point clouds. It was found that the true orthoimage produced from the second approach is better than the true orthoimage produced from the first approach. The five approaches were tested for classification of the best-orthorectified image mosaic using subpixel based (neural network) and pixel-based ( minimum distance and maximum likelihood).Multicues were extracted such as texture(entropy-mean),Digital elevation model, Digital surface model ,normalized digital surface model (nDSM) and intensity image. The contributions of the individual cues used in the classification have been evaluated. It was found that the best cue integration is intensity (pan) +nDSM+ entropy followed by intensity (pan) +nDSM+mean then intensity image +mean+ entropy after that DSM )image and two texture measures (mean and entropy) followed by the colour image. The integration with height data increases the accuracy. Also, it was found that the integration with entropy texture increases the accuracy. Resulted in fifteen cases of classification it was found that maximum likelihood classifier is the best followed by minimum distance then neural network classifier. We attribute this to the fine resolution of the digital camera image. Subpixel classifier (neural network) is not suitable for classifying aerial digital camera images. 

scholarly journals A method based on structure-from-motion photogrammetry to generate sub-millimetre-resolution digital elevation models for investigating rock breakdown features

2019 ◽  
Vol 7 (1) ◽  
pp. 45-66 ◽  
Author(s):  
Ankit Kumar Verma ◽  
Mary Carol Bourke
Keyword(s):  
High Resolution ◽  
Structure From Motion ◽  
Low Cost ◽  
Digital Elevation Models ◽  
Point Clouds ◽  
Experimental Conditions ◽  
Weathered Rock ◽  
Topographic Data ◽  
Digital Elevation ◽  
Dense Point

Abstract. We have generated sub-millimetre-resolution DEMs of weathered rock surfaces using SfM photogrammetry techniques. We apply a close-range method based on structure-from-motion (SfM) photogrammetry in the field and use it to generate high-resolution topographic data for weathered boulders and bedrock. The method was pilot tested on extensively weathered Triassic Moenkopi sandstone outcrops near Meteor Crater in Arizona. Images were taken in the field using a consumer-grade DSLR camera and were processed in commercially available software to build dense point clouds. The point clouds were registered to a local 3-D coordinate system (x, y, z), which was developed using a specially designed triangle-coded control target and then exported as digital elevation models (DEMs). The accuracy of the DEMs was validated under controlled experimental conditions. A number of checkpoints were used to calculate errors. We also evaluated the effects of image and camera parameters on the accuracy of our DEMs. We report a horizontal error of 0.5 mm and vertical error of 0.3 mm in our experiments. Our approach provides a low-cost method for obtaining very high-resolution topographic data on weathered rock surfaces (area < 10 m2). The results from our case study confirm the efficacy of the method at this scale and show that the data acquisition equipment is sufficiently robust and portable. This is particularly important for field conditions in remote locations or steep terrain where portable and efficient methods are required.

scholarly journals INTEGRATION OF POINT CLOUDS FROM TERRESTRIAL LASER SCANNING AND IMAGE-BASED MATCHING FOR GENERATING HIGH-RESOLUTION ORTHOIMAGES

2016 ◽  
Vol XLI-B5 ◽  
pp. 399-404 ◽  
Author(s):  
A. Salach ◽  
J.S. Markiewicza ◽  
D. Zawieska
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Digital Camera ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Historical Objects ◽  
Basic Objective ◽  
High Resolution Images

An orthoimage is one of the basic photogrammetric products used for architectural documentation of historical objects; recently, it has become a standard in such work. Considering the increasing popularity of photogrammetric techniques applied in the cultural heritage domain, this research examines the two most popular measuring technologies: terrestrial laser scanning, and automatic processing of digital photographs. The basic objective of the performed works presented in this paper was to optimize the quality of generated high-resolution orthoimages using integration of data acquired by a Z+F 5006 terrestrial laser scanner and a Canon EOS 5D Mark II digital camera. The subject was one of the walls of the “Blue Chamber” of the Museum of King Jan III’s Palace at Wilanów (Warsaw, Poland). The high-resolution images resulting from integration of the point clouds acquired by the different methods were analysed in detail with respect to geometric and radiometric correctness.

scholarly journals MULTI-TEMPORAL HIGH-RESOLUTION LANDSLIDE MONITORING BASED ON UAS PHOTOGRAMMETRY AND UAS LIDAR GEOINFORMATION

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 157-160
Author(s):  
C.-L. J. Hung ◽  
C.-W. Tseng ◽  
M.-J. Huang ◽  
C.-M. Tseng ◽  
K.-J. Chang
Keyword(s):  
High Resolution ◽  
Airborne Lidar ◽  
Annual Rainfall ◽  
Landslide Monitoring ◽  
Typhoon Morakot ◽  
Landslide Event ◽  
Wide Range ◽  
Hazardous Area ◽  
Multi Temporal ◽  
Rtk Gps

<p><strong>Abstract.</strong> Due to the high seismicity and high annual rainfall, numerous landslides occurred and caused severe impacts in Taiwan. Typhoon Morakot in 2009 brought extreme and long-time rainfall, and caused severe disasters. After 2009, numerous large scale deep-seated landslides may still creeping, however not necessary easily to inspect the activity. In recent years, the remote sensing technology improves rapidly, providing a wide range of image, essential and precious geoinformation. Accordingly, the Small unmanned aircraft system (sUAS) has been widely used in landslide monitoring and geomorphic change detection. This study used UAS to continuously monitor a landslide area in Baolai Village in southern Taiwan, which had a catastrophic landslide event triggered by heavy rainfall caused by Typhoon Morakot in 2009. In order to accesses the potential hazards, this study integrates UAS, field geomatic survey, terrestrial laser scanner (ground LiDAR), and UAS LiDAR for sequential data acquisition since 2015. Based on the methods we are able to construct multi-temporal and high resolution DTMs, so as to access the activity and to monitoring the creeping landslides. The data set are qualified from 21 ground control points (GCPs) and 11 check points (CPs) based on real-time kinematic-global positioning system (RTK-GPS) and VBS RTK-GPS (e-GNSS). More than 10 UAS flight missions for the study areas dated since 2015, for an area large than 5&amp;ndash;40 Km<sup>2</sup> with 8&amp;ndash;12 cm spatial resolution (GSD). Then, the datasets was compared with the airborne LiDAR data, to evaluate the quality and the interpretability of the dataset. Since early 2018, we integrate UAS LiDAR technology to scanning the sliding area. The density of the point cloud data sets are higher than 250 and 100 points/m2 for the total and ground point, respectively. The spatial distributions of geomorphologic changes were quantified firstly with the GCPS and CPs. The potential disaster was evaluated at different times, and the result reveals that most active regions were on the eastern side of the landslide. Significant changes in elevation were detected before the middle of 2017, however reactivated again since middle of 2018. The results of this study provide not only geoinfomatic datasets of hazardous area, but also for essential geomorphologic information/methods for other study, and for hazard mitigation and planning, as well.</p>

scholarly journals Advances in mapping sub-canopy snow depth with unmanned aerial vehicles using structure from motion and lidar techniques

2019 ◽  
Author(s):  
Phillip Harder ◽  
John W. Pomeroy ◽  
Warren D. Helgason
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Structure From Motion ◽  
Snow Depth ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Canadian Prairie ◽  
Widespread Application ◽  
Aerial Vehicles ◽  
Wide Range ◽  
Consistent Error

Abstract. Vegetation has a tremendous influence on snow processes and snowpack dynamics yet remote sensing techniques to resolve the spatial variability of sub-canopy snow depth are lacking. Unmanned Aerial Vehicles (UAV) have had recent widespread application to capture high resolution information on snow processes and are herein applied to the sub-canopy snow depth challenge. Previous demonstrations of snow depth mapping with UAV Structure from Motion (SfM) and airborne-lidar have focussed on non-vegetated surfaces or reported large errors in the presence of vegetation. In contrast, UAV-lidar systems have high-density point clouds, measure returns from a wide range of scan angles, and so have a greater likelihood of successfully sensing the sub-canopy snow depth. The effectiveness of UAV-lidar and UAV-SfM in mapping snow depth in both open and forested terrain was tested in a 2019 field campaign in the Canadian Rockies Hydrological Observatory, Alberta and at Canadian Prairie sites near Saskatoon, Saskatchewan, Canada. Only UAV-lidar could successfully measure the sub-canopy snow surface with reliable sub-canopy point coverage, and consistent error metrics (RMSE

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