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Proceedings of UASG 2021: Wings 4 Sustainability Unmanned Aerial System in Geomatics
Title
Proceedings of UASG 2021: Wings 4 Sustainability [electronic resource] : Unmanned Aerial System in Geomatics / edited by Kamal Jain, Vishal Mishra, Biswajeet Pradhan.
ISBN
9783031193095
Edition
1st ed. 2023.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2023.
Physical Description
1 online resource (XXII, 597 p.) 393 illus., 360 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ENIN.
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Format
Books / Online
Language
English
Added to Catalog
March 21, 2023
Series
Lecture Notes in Civil Engineering, 304
Contents
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.
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