Literature DB >> 35577092

UAV remote sensing applications in marine monitoring: Knowledge visualization and review.

Zongyao Yang1, Xueying Yu2, Simon Dedman3, Massimiliano Rosso4, Jingmin Zhu2, Jiaqi Yang2, Yuxiang Xia2, Yichao Tian2, Guangping Zhang2, Jingzhen Wang5.   

Abstract

With the booming development of information technology and the growing demand for remote sensing data, unmanned aerial vehicle (UAV) remote sensing technology has emerged. In recent years, UAV remote sensing technology has developed rapidly and has been widely used in the fields of military defense, agricultural monitoring, surveying and mapping management, and disaster and emergency response and management. Currently, increasingly serious marine biological and environmental problems are raising the need for effective and timely monitoring. Compared with traditional marine monitoring technologies, UAV remote sensing is becoming an important means for marine monitoring thanks to its flexibility, efficiency and low cost, while still producing systematic data with high spatial and temporal resolutions. This study visualizes the knowledge domain of the application and research advances of UAV remote sensing in marine monitoring by analyzing 1130 articles (from 1993 to early 2022) using a bibliometric approach and provides a review of the application of UAVs in marine management mapping, marine disaster and environmental monitoring, and marine wildlife monitoring. It aims to promote the extensive application of UAV remote sensing in the field of marine research.
Copyright © 2022 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Internet of things; Marine disasters; Marine litter; Marine management mapping; Marine megafauna; UAV systems

Mesh:

Year:  2022        PMID: 35577092     DOI: 10.1016/j.scitotenv.2022.155939

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Combining spectral and wavelet texture features for unmanned aerial vehicles remote estimation of rice leaf area index.

Authors:  Cong Zhou; Yan Gong; Shenghui Fang; Kaili Yang; Yi Peng; Xianting Wu; Renshan Zhu
Journal:  Front Plant Sci       Date:  2022-08-04       Impact factor: 6.627

  1 in total

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