scholarly journals Knud Rasmussen Glacier Status Analysis Based on Historical Data and Moving Detection Using RPAS

2021 ◽  
Vol 11 (2) ◽  
pp. 754
Author(s):  
Karel Pavelka ◽  
Jaroslav Šedina ◽  
Karel Pavelka
Keyword(s):  
Three Dimensional ◽  
Image Data ◽  
Point Clouds ◽  
Multiscale Model ◽  
Satellite System ◽  
Flow Speed ◽  
Middle Part ◽  
Google Earth ◽  
Aerial Images ◽  
Aerial Photos

This article discusses partial results of an international scientific expedition to Greenland that researched the geography, geodesy, botany, and glaciology of the area. The results here focus on the photogrammetrical results obtained with the eBee drone in the eastern part of Greenland at the front of the Knud Rasmussen Glacier and the use of archive image data for monitoring the condition of this glacier. In these short-term visits to the site, the possibility of using a drone is discussed and the results show not only the flow speed of the glacier but also the shape and structure from a height of up to 200 m. From two overflights near the glacier front at different times, it was possible to obtain the speed of the glacier flow and the distribution of velocities in the glacier stream. The technology uses a comparison of two point clouds derived from a set of aerial photos taken with the eBee drone, and calculating the M3C2 (Multiscale Model-to-Model Cloud Comparison) distances with CloudCompare software. The results correlate with other measurement methods like accurate and long-term measurement with Global Navigation Satellite System (GNSS), satellite radar, or ground geodetical technology. The resulting speed from the drone data reached in the middle part of the glacier, was approximately 12–15m per day. The second part of the paper focuses on the analysis of modern satellite images of the Knud Rasmussen Glacier from Google Earth (Landsat series 1984–2016) and Sentinel 2a, and a comparison with historical aerial images from 1932 to 1933. Historical images were processed photogrammetrically into a three-dimensional (3D) model. Finally, orthogonalized image data from three systems (drone photos, historical aerial photos, and satellite data) were compared in the ArcGIS software. This allows us to analyze glacier changes over time in the time span from 1932 to 2020, with the caveat that from 1933 to 1983 we did not have data at our disposal. The result shows that more significant changes in the area of this glacier occurred after 2011. The main aim of this article is to research the use of photogrammetric methods for monitoring the condition and parameters of glaciers based on non-traditional technology, such as drones or new processing of historical photos.

Kinect Depth Data Segmentation Based on Gauss Mixture Model Clustering

2013 ◽  
Vol 760-762 ◽  
pp. 1556-1561
Author(s):  
Ting Wei Du ◽  
Bo Liu
Keyword(s):  
Mixture Model ◽  
Point Cloud ◽  
Three Dimensional ◽  
Image Data ◽  
Point Clouds ◽  
Gaussian Mixture ◽  
Depth Image ◽  
Cloud Data ◽  
Mixture Model Clustering ◽  
Gauss Mixture

Indoor scene understanding based on the depth image data is a cutting-edge issue in the field of three-dimensional computer vision. Taking the layout characteristics of the indoor scenes and more plane features in these scenes into account, this paper presents a depth image segmentation method based on Gauss Mixture Model clustering. First, transform the Kinect depth image data into point cloud which is in the form of discrete three-dimensional point data, and denoise and down-sample the point cloud data; second, calculate the point normal of all points in the entire point cloud, then cluster the entire normal using Gaussian Mixture Model, and finally implement the entire point clouds segmentation by RANSAC algorithm. Experimental results show that the divided regions have obvious boundaries and segmentation quality is above normal, and lay a good foundation for object recognition.

scholarly journals Evaluating Elevation Change Thresholds between Structure-from-Motion DEMs Derived from Historical Aerial Photos and 3DEP LiDAR Data

2020 ◽  
Vol 12 (10) ◽  
pp. 1625
Author(s):  
Peter Chirico ◽  
Jessica DeWitt ◽  
Sarah Bergstresser
Keyword(s):  
Structure From Motion ◽  
Three Dimensional ◽  
The United States ◽  
Aerial Images ◽  
Elevation Change ◽  
Aerial Photos ◽  
Digital Elevation ◽  
Elevation Changes ◽  
Vertical Accuracy ◽  
Accuracy Assessments

This study created digital terrain models (DTMs) from historical aerial images using Structure from Motion (SfM) for a variety of image dates, resolutions, and photo scales. Accuracy assessments were performed on the SfM DTMs, and they were compared to the United States Geological Survey’s three-dimensional digital elevation program (3DEP) light detection and ranging (LiDAR) DTMs to evaluate geomorphic change thresholds based on vertical accuracy assessments and elevation change methodologies. The results of this study document a relationship between historical aerial photo scales and predicted vertical accuracy of the resultant DTMs. The results may be used to assess geomorphic change thresholds over multi-decadal timescales depending on spatial scale, resolution, and accuracy requirements. This study shows that if elevation changes of approximately ±1 m are to be mapped, historical aerial photography collected at 1:20,000 scale or larger would be required for comparison to contemporary LiDAR derived DTMs.

scholarly journals Comparison of different methods to assess the distribution of alien plants along the road network and use of Google Street View panoramas interpretation in Sicily (Italy) as a case study

2021 ◽  
Vol 9 ◽  
Author(s):  
Giulio Barone ◽  
Gianniantonio Domina ◽  
Emilio Di Gristina
Keyword(s):  
Road Network ◽  
Google Earth ◽  
Alien Plants ◽  
Aerial Images ◽  
Photo Interpretation ◽  
Aerial Photos ◽  
Google Street View ◽  
The Road ◽  
Street View ◽  
Complete Survey

The survey by foot in the field is compared to the survey from a car, the photo-interpretation of Google Street View (GSV) panoramas continuously and at intervals of 1.5 km and the photo-interpretation of Google Earth aerial images on a 10 km stretch of road in Sicily. The survey by foot was used as reference for the other methods. The interpretation of continuous GSV panoramas gave similar results as the assessment by car in terms of the number of species identified and their location, but with lower cost. The interpretation online of aerial photos allowed the identification of a limited number of taxa, but gave a good localisation for them. Interpretation of GSV panoramas, each of 1.5 km, allowed the recognition of twice as many taxa as the interpretation of aerial photos and taking half the time, but did not allow a complete localisation. None of these methods alone seems sufficient to carry out a complete survey. A mixture of different techniques, which may vary according to the available resources and the goal to be achieved, seems to be the best compromise. To further test the capabilities of the survey using the interpretation of GSV panoramas every 1.5 km along the roads, we proceeded to study the alien plants along 3500 km of the road network on the island of Sicily. This survey identified only 10% of the known species for the region, but allowed us to trace the distribution of invasive species whose distribution is currently poorly recorded.

scholarly journals COMPREHENSIVE COMPARISON OF TWO IMAGE-BASED POINT CLOUDS FROM AERIAL PHOTOS WITH AIRBORNE LIDAR FOR LARGE-SCALE MAPPING

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 557-565 ◽  
Author(s):  
E. Widyaningrum ◽  
B. G. H. Gorte
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Topographic Map ◽  
Aerial Photos ◽  
3D Data ◽  
Comparison Results ◽  
Global Matching ◽  
3D Information

The integration of computer vision and photogrammetry to generate three-dimensional (3D) information from images has contributed to a wider use of point clouds, for mapping purposes. Large-scale topographic map production requires 3D data with high precision and accuracy to represent the real conditions of the earth surface. Apart from LiDAR point clouds, the image-based matching is also believed to have the ability to generate reliable and detailed point clouds from multiple-view images. In order to examine and analyze possible fusion of LiDAR and image-based matching for large-scale detailed mapping purposes, point clouds are generated by Semi Global Matching (SGM) and by Structure from Motion (SfM). In order to conduct comprehensive and fair comparison, this study uses aerial photos and LiDAR data that were acquired at the same time. Qualitative and quantitative assessments have been applied to evaluate LiDAR and image-matching point clouds data in terms of visualization, geometric accuracy, and classification result. The comparison results conclude that LiDAR is the best data for large-scale mapping.

scholarly journals How to Build a 2D and 3D Aerial Multispectral Map?—All Steps Deeply Explained

2021 ◽  
Vol 13 (16) ◽  
pp. 3227
Author(s):  
André Vong ◽  
João P. Matos-Carvalho ◽  
Piero Toffanin ◽  
Dário Pedro ◽  
Fábio Azevedo ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Point Clouds ◽  
Three Dimensions ◽  
Aerial Images ◽  
Reconstruction Process ◽  
Processing Power ◽  
Initial Stage ◽  
Aerial Platforms ◽  
Cost Efficient ◽  
Three Dimensional Models

The increased development of camera resolution, processing power, and aerial platforms helped to create more cost-efficient approaches to capture and generate point clouds to assist in scientific fields. The continuous development of methods to produce three-dimensional models based on two-dimensional images such as Structure from Motion (SfM) and Multi-View Stereopsis (MVS) allowed to improve the resolution of the produced models by a significant amount. By taking inspiration from the free and accessible workflow made available by OpenDroneMap, a detailed analysis of the processes is displayed in this paper. As of the writing of this paper, no literature was found that described in detail the necessary steps and processes that would allow the creation of digital models in two or three dimensions based on aerial images. With this, and based on the workflow of OpenDroneMap, a detailed study was performed. The digital model reconstruction process takes the initial aerial images obtained from the field survey and passes them through a series of stages. From each stage, a product is acquired and used for the following stage, for example, at the end of the initial stage a sparse reconstruction is produced, obtained by extracting features of the images and matching them, which is used in the following step, to increase its resolution. Additionally, from the analysis of the workflow, adaptations were made to the standard workflow in order to increase the compatibility of the developed system to different types of image sets. Particularly, adaptations focused on thermal imagery were made. Due to the low presence of strong features and therefore difficulty to match features across thermal images, a modification was implemented, so thermal models could be produced alongside the already implemented processes for multispectral and RGB image sets.

scholarly journals AUTOMATED ALIGNMENT OF LOCAL POINT CLOUDS IN DIGITAL BUILDING MODELS

2019 ◽  
Vol XLII-5/W2 ◽  
pp. 35-39
Author(s):  
T. Kaiser ◽  
C. Clemen ◽  
H.-G. Maas
Keyword(s):  
Three Dimensional ◽  
Image Data ◽  
Point Clouds ◽  
Data Sets ◽  
Control Points ◽  
Building Models ◽  
Local Point ◽  
Synthetic Test ◽  
Transformation Parameters ◽  
Automated Alignment

<p><strong>Abstract.</strong> For the correct usage and analysis within a BIM environment, image-based point clouds that were created with Structure from Motion (SfM) tools have to be transformed into the building coordinate system via a seven parameter Helmert Transformation. Usually control points are used for the estimation of the transformation parameters. In this paper we present a novel, highly automated approach to calculate these transformation parameters without the use of control points. The process relies on the relationship between wall respectively plane information of the BIM and three-dimensional line data that is extracted from the image data. In a first step, 3D lines are extracted from the oriented input images using the tool Line3D++. These lines are defined by the 3D coordinates of the start and end points. Afterwards the lines are matched to the planes originating from the BIM model representing the walls, floors and ceilings. Besides finding a suitable functional and stochastic model for the observation equations and the adjustment calculation, the most critical aspect is finding a correct match for the lines and the planes. We therefore developed a RANSAC-inspired matching algorithm to get a correct assignment between elements of the two data sources. Synthetic test data sets have been created for evaluating the methodology.</p>

scholarly journals The Implications of M3C2 Projection Diameter on 3D Semi-Automated Rockfall Extraction from Sequential Terrestrial Laser Scanning Point Clouds

2020 ◽  
Vol 12 (11) ◽  
pp. 1885 ◽  
Author(s):  
Paul-Mark DiFrancesco ◽  
David Bonneau ◽  
D. Jean Hutchinson
Keyword(s):  
Laser Scanning ◽  
Rock Slope ◽  
Spatial Information ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Multiscale Model ◽  
Computation Method ◽  
Highly Active ◽  
Optimal Projection

Rockfall inventories are essential to quantify a rockfall activity and characterize the hazard. Terrestrial laser scanning and advancements in processing algorithms have resulted in three-dimensional (3D) semi-automatic extraction of rockfall events, permitting detailed observations of evolving rock masses. Currently, multiscale model-to-model cloud comparison (M3C2) is the most widely used distance computation method used in the geosciences to evaluate 3D changing features, considering the time-sequential spatial information contained in point clouds. M3C2 operates by computing distances using points that are captured within a projected search cylinder, which is locally oriented. In this work, we evaluated the effect of M3C2 projection diameter on the extraction of 3D rockfalls and the resulting implications on rockfall volume and shape. Six rockfall inventories were developed for a highly active rock slope, each utilizing a different projection diameter which ranged from two to ten times the point spacing. The results indicate that the greatest amount of change is extracted using an M3C2 projection diameter equal to, or slightly larger than, the point spacing, depending on the variation in point spacing. When the M3C2 projection diameter becomes larger than the changing area on the rock slope, the change cannot be identified and extracted. Inventory summaries and illustrations depict the influence of spatial averaging on the semi-automated rockfall extraction, and suggestions are made for selecting the optimal projection diameter. Recommendations are made to improve the methods used to semi-automatically extract rockfall from sequential point clouds.

scholarly journals Knud Rasmussen Glacier Status Analysis Based on Historical Data and Moving Detection Using RPAS

2020 ◽  
Author(s):  
Karel Pavelka ◽  
Jaroslav Šedina ◽  
Karel Pavelka jr.
Keyword(s):  
3D Model ◽  
Historical Data ◽  
Flow Speed ◽  
Google Earth ◽  
Aerial Images ◽  
Short Term ◽  
Glacier Front ◽  
Glacier Flow ◽  
Status Analysis

This article discusses an international scientific expedition to Greenland that researched geography, geodesy, botany, and glaciology of the area. The results here focus on the geodetic and glaciological results obtained with the eBee drone in the eastern part of Greenland at the front of the Knud Rasmussen glacier. From two overflights nearby the glacier front, it was possible to obtain the speed of the glacier flow and the distribution of velocities in the glacier stream. The results correlate with other measurement methods and this technology has been shown as feasible. Of course, there are more accurate and long-term options or devices for monitoring the flow of glaciers. In this case of short-term visits to the site, the possibility of using a drone is interesting and the results show not only the flow speed of the glacier, but also the shape and structure from a height of up to 200m. The second part of the paper focuses on the analysis of modern satellite images of the Knud Rasmussen glacier from Google Earth (Landsat series 1984-2016) and a comparison with historical aerial images from 1932-1933. Experimentally, historical images were processed photogrammetrically into a 3D model.

scholarly journals Derivation of Three-Dimensional Displacement Vectors from Multi-Temporal Long-Range Terrestrial Laser Scanning at the Reissenschuh Landslide (Tyrol, Austria)

2018 ◽  
Vol 10 (11) ◽  
pp. 1688 ◽  
Author(s):  
Jan Pfeiffer ◽  
Thomas Zieher ◽  
Magnus Bremer ◽  
Volker Wichmann ◽  
Martin Rutzinger
Keyword(s):  
Long Range ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Satellite System ◽  
Image Correlation ◽  
Mountain Areas ◽  
Icp Algorithm ◽  
Displacement Vectors ◽  
Multi Temporal

Deep-seated gravitational slope deformations (DSGSDs) endanger settlements and infrastructure in mountain areas all over the world. To prevent disastrous events, their activity needs to be continuously monitored. In this paper, the movement of the Reissenschuh DSGSD in the Schmirn valley (Tyrol, Austria) is quantified based on point clouds acquired with a Riegl VZ®-6000 long-range laser scanner in 2016 and 2017. Geomorphological features (e.g., block edges, terrain ridges, scarps) travelling on top of the landslide are extracted from the acquired point clouds using morphometric attributes based on locally computed eigenvectors and -values. The corresponding representations of the extracted features in the multi-temporal data are exploited to derive 3D displacement vectors based on a workflow exploiting the iterative closest point (ICP) algorithm. The subsequent analysis reveals spatial patterns of landslide movement with mean displacements in the order of 0.62 ma − 1 , corresponding well with measurements at characteristic points using a differential global navigation satellite system (DGNSS). The results are also compared to those derived from a modified version of the well-known image correlation (IMCORR) method using shaded reliefs of the derived digital terrain models. The applied extended ICP algorithm outperforms the raster-based method particularly in areas with predominantly vertical movement.

scholarly journals Three Dimensional Reconstruction of Botanical Trees with Simulatable Geometry

2021 ◽  
Vol 4 (3) ◽  
pp. 1-16
Author(s):  
Ed Quigley ◽  
Winnie Lin ◽  
Yilin Zhu ◽  
Ronald Fedkiw
Keyword(s):  
Physical Simulation ◽  
State Of The Art ◽  
Three Dimensional ◽  
Image Data ◽  
Point Clouds ◽  
Future Research ◽  
Geometric Accuracy ◽  
Rigid Body Model ◽  
Dimensional Reconstruction ◽  
Pros And Cons

We tackle the challenging problem of creating full and accurate three dimensional reconstructions of botanical trees with the topological and geometric accuracy required for subsequent physical simulation, e.g. in response to wind forces. Although certain aspects of our approach would benefit from various improvements, our results exceed the state of the art especially in geometric and topological complexity and accuracy. Starting with two dimensional RGB image data acquired from cameras attached to drones, we create point clouds, textured triangle meshes, and a simulatable and skinned cylindrical articulated rigid body model. We discuss the pros and cons of each step of our pipeline, and in order to stimulate future research we make the raw and processed data from every step of the pipeline as well as the final geometric reconstructions publicly available.

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