数字农科院2.0

Surveying Wild Animals From Satellites, M.anned Aircraft And Unmanned A erial Systems (Uass): A Review

文献类型： 外文期刊

作者： Wang, DL; Shao, QQ; Yue, HY

作者机构：

关键词： very-high-resolution satellites; unmanned aircraft systems; wild animal surveys; remote sensing

期刊名称： REMOTE SENSING

ISSN： 2072-4292

年卷期： 2019 年 11 卷 11 期

页码：

收录情况： JCR（2021版） ; EI（2021版）

摘要： This article reviews studies regarding wild animal surveys based on multiple platforms, including satellites, manned aircraft, and unmanned aircraft systems (UASs), and focuses on the data used, animal detection methods, and their accuracies. We also discuss the advantages and limitations of each type of remote sensing data and highlight some new research opportunities and challenges. Submeter very-high-resolution (VHR) spaceborne imagery has potential in modeling the population dynamics of large (>0.6 m) wild animals at large spatial and temporal scales, but has difficulty discerning small (<0.6 m) animals at the species level, although high-resolution commercial satellites, such as WorldView-3 and -4, have been able to collect images with a ground resolution of up to 0.31 m in panchromatic mode. This situation will not change unless the satellite image resolution is greatly improved in the future. Manned aerial surveys have long been employed to capture the centimeter-scale images required for animal censuses over large areas. However, such aerial surveys are costly to implement in small areas and can cause significant disturbances to wild animals because of their noise. In contrast, UAS surveys are seen as a safe, convenient and less expensive alternative to ground-based and conventional manned aerial surveys, but most UASs can cover only small areas. The proposed use of UAS imagery in combination with VHR satellite imagery would produce critical population data for large wild animal species and colonies over large areas. The development of software systems for automatically producing image mosaics and recognizing wild animals will further improve survey efficiency.

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