公民科学数据来源的一致性如何?一项使用免费自动图像识别应用程序进行木本植物识别的探索性研究

IF 1.7 3区 农林科学 Q2 FORESTRY Canadian Journal of Forest Research Pub Date : 2023-09-18 DOI:10.1139/cjfr-2023-0203
Kenneth A. Anyomi
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引用次数: 0

摘要

人工智能的快速发展导致了自动图像识别手机应用程序的激增。这增加了公众对生物数据收集、鉴定和分析的参与。虽然这对生物数据监测领域有好处,但目前尚不清楚来自不同应用程序的id是否一致。本探索性工作的目的是验证两个广泛使用的免费应用程序(PlantNet和iNaturalist应用程序)在植物物种鉴定中的准确性和一致性。本工作通过扫描Niagara Escarpment生物圈保护区和安大略省汉密尔顿皇家植物园的Bruce trail的叶片样本进行。结果表明,在属水平上木本植物的鉴定一致性达90%以上。在物种水平上,PlantNet应用程序的准确率为79%(即100个物种中有79个被正确识别),而iNaturalist应用程序的准确率为44%。加强在南安大略省数据库中的物种代表性可能有助于特别是桦木科,蔷薇科和松科的物种。建议将应用程序的补充使用作为一种警告措施,以减少物种水平木本植物识别错误的可能性,并将应用程序与实地指南结合使用。
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How consistent are citizen science data sources, an exploratory study using free automated image recognition apps for woody plant identification
Rapid advances in artificial intelligence have led to an upsurge in automated image recognition phone apps. This has increased public involvement in the collection, identification (ID) and analysis of biological data. While this is good for the field of biological data monitoring, it is not clear how consistent IDs are from different apps. The goal of this exploratory work is to verify the accuracy and consistency in plant species identification from two widely used and free apps i.e. PlantNet and iNaturalist app. This work was conducted by scanning leaf samples along Bruce trail in the Niagara Escarpment Biosphere reserve and the Royal Botanical Gardens arboretum, in Hamilton Ontario. Results show over 90% consistency in the identification of woody plants at the level of genus. At the species level, PlantNet app demonstrated 79% accuracy (i.e. 79 out of 100 species correctly identified) while the iNaturalist app demonstrated 44% accuracy. Enhancing species representation in the database for southern Ontario might help particularly species in the family Betulaceae, Rosaceae and Pinaceae. Complementary use of the apps is recommended as a cautionary measure to reduce the likelihood of error in species-level woody plant identification as well as using apps in conjunction with field guide.
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来源期刊
CiteScore
4.20
自引率
9.10%
发文量
109
审稿时长
3 months
期刊介绍: Published since 1971, the Canadian Journal of Forest Research is a monthly journal that features articles, reviews, notes and concept papers on a broad spectrum of forest sciences, including biometrics, conservation, disturbances, ecology, economics, entomology, genetics, hydrology, management, nutrient cycling, pathology, physiology, remote sensing, silviculture, social sciences, soils, stand dynamics, and wood science, all in relation to the understanding or management of ecosystem services. It also publishes special issues dedicated to a topic of current interest.
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