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关于小型无人航空器系统(UAS)作为北美陆地脊椎动物调查工具的功效的证据:一项系统综述。

Evidence on the efficacy of small unoccupied aircraft systems (UAS) as a survey tool for North American terrestrial, vertebrate animals: a systematic map.

作者信息

Elmore Jared A, Schultz Emma A, Jones Landon R, Evans Kristine O, Samiappan Sathishkumar, Pfeiffer Morgan B, Blackwell Bradley F, Iglay Raymond B

机构信息

Department of Wildlife, Fisheries and Aquaculture, Mississippi State University, Thompson Hall, Box 9690, Mississippi State, MS, 39762, USA.

Forestry and Environmental Conservation, Clemson University, Clemson, SC, 29634, USA.

出版信息

Environ Evid. 2023 Feb 13;12(1):3. doi: 10.1186/s13750-022-00294-8.

Abstract

BACKGROUND

Small unoccupied aircraft systems (UAS) are replacing or supplementing occupied aircraft and ground-based surveys in animal monitoring due to improved sensors, efficiency, costs, and logistical benefits. Numerous UAS and sensors are available and have been used in various methods. However, justification for selection or methods used are not typically offered in published literature. Furthermore, existing reviews do not adequately cover past and current UAS applications for animal monitoring, nor their associated UAS/sensor characteristics and environmental considerations. We present a systematic map that collects and consolidates evidence pertaining to UAS monitoring of animals.

METHODS

We investigated the current state of knowledge on UAS applications in terrestrial animal monitoring by using an accurate, comprehensive, and repeatable systematic map approach. We searched relevant peer-reviewed and grey literature, as well as dissertations and theses, using online publication databases, Google Scholar, and by request through a professional network of collaborators and publicly available websites. We used a tiered approach to article exclusion with eligible studies being those that monitor (i.e., identify, count, estimate, etc.) terrestrial vertebrate animals. Extracted metadata concerning UAS, sensors, animals, methodology, and results were recorded in Microsoft Access. We queried and catalogued evidence in the final database to produce tables, figures, and geographic maps to accompany this full narrative review, answering our primary and secondary questions.

REVIEW FINDINGS

We found 5539 articles from our literature searches of which 216 were included with extracted metadata categories in our database and narrative review. Studies exhibited exponential growth over time but have levelled off between 2019 and 2021 and were primarily conducted in North America, Australia, and Antarctica. Each metadata category had major clusters and gaps, which are described in the narrative review.

CONCLUSIONS

Our systematic map provides a useful synthesis of current applications of UAS-animal related studies and identifies major knowledge clusters (well-represented subtopics that are amenable to full synthesis by a systematic review) and gaps (unreported or underrepresented topics that warrant additional primary research) that guide future research directions and UAS applications. The literature for the use of UAS to conduct animal surveys has expanded intensely since its inception in 2006 but is still in its infancy. Since 2015, technological improvements and subsequent cost reductions facilitated widespread research, often to validate UAS technology to survey single species with application of descriptive statistics over limited spatial and temporal scales. Studies since the 2015 expansion have still generally focused on large birds or mammals in open landscapes of 4 countries, but regulations, such as maximum altitude and line-of-sight limitations, remain barriers to improved animal surveys with UAS. Critical knowledge gaps include the lack of (1) best practices for using UAS to conduct standardized surveys in general, (2) best practices to survey whole wildlife communities in delineated areas, and (3) data on factors affecting bias in counting animals from UAS images. Promising advances include the use of thermal sensors in forested environments or nocturnal surveys and the development of automated or semi-automated machine-learning algorithms to accurately detect, identify, and count animals from UAS images.

摘要

背景

由于传感器性能提升、效率提高、成本降低以及后勤保障优势,小型无人航空器系统(UAS)正在取代或补充载人飞机和地面调查用于动物监测。市面上有众多的UAS和传感器,且已被用于各种方法。然而,已发表的文献中通常未说明选择的理由或所使用的方法。此外,现有的综述并未充分涵盖过去和当前UAS在动物监测中的应用,也未涉及相关的UAS/传感器特性及环境因素。我们呈现了一幅系统地图,收集并整合了与UAS动物监测相关的证据。

方法

我们采用准确、全面且可重复的系统地图方法,调查了UAS在陆地动物监测应用方面的当前知识状态。我们使用在线出版物数据库、谷歌学术搜索相关的同行评审文献和灰色文献,以及学位论文,还通过专业合作网络和公开网站请求获取相关资料。我们采用分层方法排除文章,符合条件的研究是那些监测(即识别、计数、估算等)陆地脊椎动物的研究。提取的关于UAS、传感器、动物、方法和结果的元数据记录在Microsoft Access中。我们在最终数据库中查询并编目证据,以生成表格、图表和地理地图,作为本次全面叙述性综述的辅助,回答我们的主要和次要问题。

综述结果

我们在文献搜索中找到5539篇文章,其中216篇被纳入我们的数据库并进行叙述性综述,带有提取的元数据类别。研究数量随时间呈指数增长,但在2019年至2021年期间趋于平稳,主要在北美、澳大利亚和南极洲开展。每个元数据类别都有主要的聚类和空白,在叙述性综述中有描述。

结论

我们的系统地图对UAS与动物相关研究的当前应用进行了有益的综合,识别出主要的知识聚类(有充分代表性、适合通过系统综述进行全面综合的子主题)和空白(未报告或代表性不足、需要更多原始研究的主题),这些聚类和空白指导未来的研究方向和UAS应用。自2006年UAS用于动物调查以来,相关文献急剧增加,但仍处于起步阶段。自2015年以来,技术进步及随后的成本降低推动了广泛研究,这些研究通常是在有限的空间和时间尺度上应用描述性统计来验证UAS技术用于调查单一物种。2015年扩展后的研究总体上仍主要集中在4个国家开阔地带的大型鸟类或哺乳动物,但诸如最大高度和视线限制等规定仍是利用UAS改进动物调查的障碍。关键的知识空白包括:(1)一般使用UAS进行标准化调查的最佳实践;(2)在划定区域内调查整个野生动物群落的最佳实践;(3)影响从UAS图像中计数动物偏差的因素的数据。有前景的进展包括在森林环境或夜间调查中使用热传感器以及开发自动化或半自动化机器学习算法以准确从UAS图像中检测、识别和计数动物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49ea/11378819/4fba1b3676ef/13750_2022_294_Fig1_HTML.jpg

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