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Proceedings of UASG 2021: Wings 4 Sustainability: Unmanned Aerial System in Geomatics 2023 ed. [Minkštas viršelis]

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  • Formatas: Paperback / softback, 597 pages, aukštis x plotis: 235x155 mm, 360 Illustrations, color; 33 Illustrations, black and white; XXII, 597 p. 393 illus., 360 illus. in color., 1 Paperback / softback
  • Serija: Lecture Notes in Civil Engineering 304
  • Išleidimo metai: 16-Mar-2024
  • Leidėjas: Springer International Publishing AG
  • ISBN-10: 3031193113
  • ISBN-13: 9783031193118
Kitos knygos pagal šią temą:
Proceedings of UASG 2021: Wings 4 Sustainability: Unmanned Aerial System in Geomatics 2023 ed.Didesnis paveikslėlis
  • Formatas: Paperback / softback, 597 pages, aukštis x plotis: 235x155 mm, 360 Illustrations, color; 33 Illustrations, black and white; XXII, 597 p. 393 illus., 360 illus. in color., 1 Paperback / softback
  • Serija: Lecture Notes in Civil Engineering 304
  • Išleidimo metai: 16-Mar-2024
  • Leidėjas: Springer International Publishing AG
  • ISBN-10: 3031193113
  • ISBN-13: 9783031193118
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9783031193118.html
Raktažodžiai:

This volume gathers the latest advances, innovations, and applications in the field of geographic information systems and unmanned aerial vehicle (UAV) technologies, as presented by leading researchers and engineers at the 2nd International Conference on Unmanned Aerial System in Geomatics (UASG), held in Roorkee, India on April 2-4, 2021. It covers highly diverse topics, including photogrammetry and remote sensing, surveying, UAV manufacturing, geospatial data sensing, UAV processing, visualization, and management, UAV applications and regulations, geo-informatics and geomatics. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaboration among different specialists.

Chapter 1: Comparison of DEM generated from UAV images and ICESat-1
Elevation Datasets with an assessment of the Cartographic Potential of
UAV-based Sensor Datasets.
Chapter 2: UAV to Cadastral Parcel Boundary
Translation and Synthetic UAV Image Generation Using Conditional-Generative
Adversarial Network.
Chapter 3: UAV-based terrain-following mapping using
LiDAR in high undulating catastrophic areas.
Chapter 4: Forest Fire
Detection from UAV Images using Fusion of Pre-trained Mobile CNN Features.-
Chapter 5: Deep Learning-based Improved Automatic Building Extraction from
Open-Source High-Resolution Unmanned Aerial Vehicle (UAV) Imagery.