Generating UAV high-resolution topographic data within a FOSS photogrammetric workflow using high-performance computing clusters

[1]  Carlos Cabo,et al.  Structure from Motion Photogrammetry in Forestry: a Review , 2019, Current Forestry Reports.

[2]  Kiyun Yu,et al.  Bundle Block Adjustment with 3D Natural Cubic Splines , 2009, Sensors.

[3]  Daniel Steininger,et al.  A VERSATILE UAV NEAR REAL-TIME MAPPING SOLUTION FOR DISASTER RESPONSE – CONCEPT, IDEAS AND IMPLEMENTATION , 2020 .

[4]  Richard Szeliski,et al.  Towards Internet-scale multi-view stereo , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Young-Joon Kim,et al.  Flight Time Estimation for Continuous Surveillance Missions Using a Multirotor UAV , 2019, Energies.

[6]  Liang-Jun Zhu,et al.  GDAL/OGR and Geospatial Data IO Libraries , 2020 .

[7]  Xin Wang,et al.  Structure from motion for ordered and unordered image sets based on random k-d forests and global pose estimation , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

[8]  J. Gonçalves,et al.  UAV photogrammetry for topographic monitoring of coastal areas , 2015 .

[9]  Yu Chen,et al.  Graph-Based Parallel Large Scale Structure from Motion , 2020, Pattern Recognit..

[10]  Olee Hoi Ying Lam,et al.  Scale Drone Mapping on K8S: Auto-scale Drone Imagery Processing on Kubernetes-orchestrated On-premise Cloud-computing Platform , 2020, GISTAM.

[11]  David G. Lowe,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.

[12]  Mark A. Fonstad,et al.  Topographic structure from motion: a new development in photogrammetric measurement , 2013 .

[13]  Ewelina Rupnik,et al.  Improving FOSS photogrammetric workflows for processing large image datasets , 2017, Open Geospatial Data, Software and Standards.

[14]  Dirk Merkel,et al.  Docker: lightweight Linux containers for consistent development and deployment , 2014 .

[15]  M. Caldara,et al.  Channel Changes and Controlling Factors over the Past 150 Years in the Basento River (Southern Italy) , 2020 .

[16]  S. Lane,et al.  Remote survey of large-scale braided, gravel-bed rivers using digital photogrammetry and image analysis , 2003 .

[17]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[18]  Greg Thain,et al.  Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor , 2018, PLoS Comput. Biol..

[19]  Vanessa Sochat,et al.  Singularity: Scientific containers for mobility of compute , 2017, PloS one.

[20]  Wilfried Philips,et al.  Speeding Up Structure from Motion on Large Scenes Using Parallelizable Partitions , 2010, ACIVS.

[21]  Subhashis Banerjee,et al.  Divide and Conquer: Efficient Large-Scale Structure from Motion Using Graph Partitioning , 2014, ACCV.

[22]  Robbie Austrums,et al.  Subaerial gravel size measurement using topographic data derived from a UAV‐SfM approach , 2017 .

[23]  John D. Bolten,et al.  Near Real-Time Flood Monitoring and Impact Assessment Systems , 2017 .

[24]  Andrew W. Fitzgibbon,et al.  Bundle Adjustment - A Modern Synthesis , 1999, Workshop on Vision Algorithms.

[25]  Unal Okyay,et al.  Airborne lidar change detection: An overview of Earth sciences applications , 2019, Earth-Science Reviews.

[26]  V. N. Adrov,et al.  HIGH PERFORMANCE PHOTOGRAMMETRIC PROCESSING ON COMPUTER CLUSTERS , 2012 .

[27]  F. Cavalcante,et al.  Trace metals speciation in sediments of the Basento River (Italy) , 2011 .

[28]  Julien Michel,et al.  Orfeo ToolBox: open source processing of remote sensing images , 2017, Open Geospatial Data, Software and Standards.

[29]  Song Ji,et al.  Parallel Processing Architecture of Remotely Sensed Image Processing System Based on Cluster , 2009, 2009 2nd International Congress on Image and Signal Processing.

[30]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[31]  Yong Zhang,et al.  Block Partitioning and Merging for Processing Large-Scale Structure From Motion Problems in Distributed Manner , 2019, IEEE Access.

[32]  An Approach for Managing Hybrid Supercomputer Resources in Photogrammetric Tasks , 2018 .

[33]  Jong Geol Park,et al.  Near Real-Time Flood Volume Estimation From MODIS Time-Series Imagery in the Indus River Basin , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[34]  E. Rupnik,et al.  MicMac – a free, open-source solution for photogrammetry , 2017, Open Geospatial Data, Software and Standards.

[35]  Miloš Rusnák,et al.  Template for high-resolution river landscape mapping using UAV technology , 2018 .

[36]  Scott M. Sawyer,et al.  Cluster-based 3D reconstruction of aerial video , 2012, 2012 IEEE Conference on High Performance Extreme Computing.

[37]  Gary R. Bradski,et al.  ORB: An efficient alternative to SIFT or SURF , 2011, 2011 International Conference on Computer Vision.

[38]  Koushil Sreenath,et al.  Staging energy sources to extend flight time of a multirotor UAV , 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[39]  Richard Szeliski,et al.  Modeling the World from Internet Photo Collections , 2008, International Journal of Computer Vision.

[40]  Marco Dubbini,et al.  Using Unmanned Aerial Vehicles (UAV) for High-Resolution Reconstruction of Topography: The Structure from Motion Approach on Coastal Environments , 2013, Remote. Sens..

[41]  J. Travelletti,et al.  UAV-based remote sensing of the Super-Sauze landslide : evaluation and results. , 2012 .

[42]  Ke Lu,et al.  Parallel programing templates for remote sensing image processing on GPU architectures: design and implementation , 2014, Computing.

[43]  Gamini Dissanayake,et al.  L2-SIFT: SIFT feature extraction and matching for large images in large-scale aerial photogrammetry , 2014 .

[44]  F. Scholten,et al.  Operational Parallel Processing in Digital Photogrammetry - Strategy and Results using Different Multi-Line Cameras , 2004 .

[45]  Yongjun Zhang,et al.  DIGITAL PHOTOGRAMMETRY GRID ( DPGRID ) AND ITS APPLICATION , 2011 .

[46]  Wanshou Jiang,et al.  Efficient structure from motion for large-scale UAV images: A review and a comparison of SfM tools , 2020 .

[47]  S. Ullman.  The interpretation of structure from motion , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[48]  Yuriy Vagapov,et al.  Review of Unmanned Aircraft System Technologies to Enable Beyond Visual Line of Sight (BVLOS) Operations , 2018, 2018 X International Conference on Electrical Power Drive Systems (ICEPDS).

[49]  Carlos Castillo,et al.  Image-based surface reconstruction in geomorphometry - merits, limits and developments , 2016 .

[50]  Luc Rolland,et al.  Development of Small UAS Beyond-Visual-Line-of-Sight (BVLOS) Flight Operations: System Requirements and Procedures , 2018 .