Participatory ground data are complementary to satellite bark beetle detection

IF 2.5 3区 农林科学 Q1 FORESTRY
Davide Nardi, Aurora Bozzini, Giuseppe Morgante, Angelo Gaccione, Valerio Finozzi, Andrea Battisti
{"title":"Participatory ground data are complementary to satellite bark beetle detection","authors":"Davide Nardi, Aurora Bozzini, Giuseppe Morgante, Angelo Gaccione, Valerio Finozzi, Andrea Battisti","doi":"10.1186/s13595-023-01216-5","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Key message</h3><p>During pest outbreaks, mapping tools play an important role. Participatory projects can provide useful ground data, which have a high accuracy in detecting early-stage infestations and small spots of the European spruce bark beetle <i>Ips typographus</i>. However, satellite approaches are fundamental to clearly estimate infestation occurrence because ground data are spatially biased. Here, we show how a participatory approach involving nonspecialized staff and based on GIS-based app may contribute ground truth data that are fully complementary to satellite data.</p><h3 data-test=\"abstract-sub-heading\">Context</h3><p>In Europe, bark beetle outbreaks were recently triggered by windstorms and heat waves, with the European spruce bark beetle <i>Ips typographus</i>. as the most important pest species. Huge efforts are needed for continuous mapping and monitoring of affected areas, especially during an incipient large-scale infestation. This is particularly difficult in mountain landscapes because of the rugged topography.</p><h3 data-test=\"abstract-sub-heading\">Aims</h3><p>In addition to the use of remote sensing techniques, ground surveys are still an important source of data, providing detailed information on the symptoms of the affected trees and the stage of the attacks. Unfortunately, these surveys are extremely time demanding and require intensive field work. We wanted to assess how a participatory approach based on nonspecialized staff may contribute to data collection.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Georeferenced outbreak data were collected in the field in the Southern Alps (Italy) using a smartphone application based on ArcGIS platform. The survey was based on a participatory approach on a voluntary basis, involving citizens aware of forest practices. Visual analysis of satellite images was performed monthly to assess the visibility of reported infestations. Using a binomial model, we tested how the type of report (i.e., on-site/off-site), size of spot, stage of infestation, and their interactions affect detectability. In addition, spot occurrences within a study area were mapped for comparison with ground surveillance. Closeness to roads was tested between reported and unreported spots.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>WebGIS platform allowed us to retrieve near real-time information on bark beetle outbreaks and to compare the results with satellite imagery. Using visual analysis of satellite images, we detected only ~ 50% of the spots observed in the field, and detectability decreased dramatically for smaller and early-stage spots. Field observations were mostly concentrated near roads and covered only ~ 10% of the spots detected on satellite images.</p><h3 data-test=\"abstract-sub-heading\">Conclusion</h3><p>The participatory approach is particularly helpful in mapping early-stage and small infestations, while satellite images are better suited at covering large areas and detect large and advanced-stage spots. The integration of those approaches is promising, and it can greatly improve the overall understanding of bark beetle outbreaks under emergency situations. A greater effort in developing smart applications for ground detection will benefit future monitoring of forest pests.</p>","PeriodicalId":7994,"journal":{"name":"Annals of Forest Science","volume":"10 15","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Forest Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1186/s13595-023-01216-5","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FORESTRY","Score":null,"Total":0}
引用次数: 0

Abstract

Key message

During pest outbreaks, mapping tools play an important role. Participatory projects can provide useful ground data, which have a high accuracy in detecting early-stage infestations and small spots of the European spruce bark beetle Ips typographus. However, satellite approaches are fundamental to clearly estimate infestation occurrence because ground data are spatially biased. Here, we show how a participatory approach involving nonspecialized staff and based on GIS-based app may contribute ground truth data that are fully complementary to satellite data.

Context

In Europe, bark beetle outbreaks were recently triggered by windstorms and heat waves, with the European spruce bark beetle Ips typographus. as the most important pest species. Huge efforts are needed for continuous mapping and monitoring of affected areas, especially during an incipient large-scale infestation. This is particularly difficult in mountain landscapes because of the rugged topography.

Aims

In addition to the use of remote sensing techniques, ground surveys are still an important source of data, providing detailed information on the symptoms of the affected trees and the stage of the attacks. Unfortunately, these surveys are extremely time demanding and require intensive field work. We wanted to assess how a participatory approach based on nonspecialized staff may contribute to data collection.

Methods

Georeferenced outbreak data were collected in the field in the Southern Alps (Italy) using a smartphone application based on ArcGIS platform. The survey was based on a participatory approach on a voluntary basis, involving citizens aware of forest practices. Visual analysis of satellite images was performed monthly to assess the visibility of reported infestations. Using a binomial model, we tested how the type of report (i.e., on-site/off-site), size of spot, stage of infestation, and their interactions affect detectability. In addition, spot occurrences within a study area were mapped for comparison with ground surveillance. Closeness to roads was tested between reported and unreported spots.

Results

WebGIS platform allowed us to retrieve near real-time information on bark beetle outbreaks and to compare the results with satellite imagery. Using visual analysis of satellite images, we detected only ~ 50% of the spots observed in the field, and detectability decreased dramatically for smaller and early-stage spots. Field observations were mostly concentrated near roads and covered only ~ 10% of the spots detected on satellite images.

Conclusion

The participatory approach is particularly helpful in mapping early-stage and small infestations, while satellite images are better suited at covering large areas and detect large and advanced-stage spots. The integration of those approaches is promising, and it can greatly improve the overall understanding of bark beetle outbreaks under emergency situations. A greater effort in developing smart applications for ground detection will benefit future monitoring of forest pests.

Abstract Image

参与性地面数据是对树皮甲虫卫星探测的补充
在虫害暴发期间,测绘工具发挥着重要作用。参与式项目可以提供有用的地面数据,对欧洲云杉树皮甲虫早期侵染和小斑点的检测具有较高的准确性。然而,由于地面数据在空间上存在偏差,卫星方法对于清楚地估计虫害发生情况至关重要。在这里,我们展示了一种涉及非专业人员和基于gis的应用程序的参与式方法如何提供与卫星数据完全互补的地面真实数据。在欧洲,最近风暴和热浪引发了树皮甲虫的爆发,其中欧洲云杉树皮甲虫为Ips typographus。作为最重要的害虫种类。需要作出巨大努力,持续测绘和监测受影响地区,特别是在刚开始大规模虫害期间。这在山地景观中尤其困难,因为地形崎岖。目的除了使用遥感技术外,地面调查仍然是一个重要的数据来源,提供有关受影响树木症状和攻击阶段的详细信息。不幸的是,这些调查非常耗时,需要密集的现场工作。我们想评估基于非专业人员的参与性方法如何有助于数据收集。方法采用基于ArcGIS平台的智能手机应用程序采集意大利南阿尔卑斯地区野外暴发的地理参考数据。这项调查是以自愿参与的方式为基础的,让了解森林做法的公民参与。每月对卫星图像进行目视分析,以评估报告的虫害的可见度。使用二项模型,我们测试了报告类型(即现场/非现场),斑点大小,感染阶段及其相互作用如何影响可检测性。此外,还绘制了研究区内的现场分布图,以便与地面监测进行比较。在报告和未报告的地点之间测试了距离道路的远近。结果利用bgis平台检索树皮甲虫爆发的近实时信息,并将结果与卫星图像进行比较。通过对卫星图像的视觉分析,我们仅检测到现场观测到的约50%的斑点,并且对较小和早期斑点的检测率急剧下降。野外观测主要集中在道路附近,只覆盖了卫星图像上探测到的约10%的斑点。结论参与式方法对早期和小虫害的定位特别有帮助,而卫星图像更适合于覆盖大面积和检测大虫害和晚期虫害。这些方法的整合是有希望的,它可以大大提高对紧急情况下树皮甲虫爆发的整体认识。在开发地面探测智能应用方面的更大努力将有利于未来对森林害虫的监测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Annals of Forest Science
Annals of Forest Science 农林科学-林学
CiteScore
6.70
自引率
3.30%
发文量
45
审稿时长
12-24 weeks
期刊介绍: Annals of Forest Science is an official publication of the French National Institute for Agriculture, Food and Environment (INRAE) -Up-to-date coverage of current developments and trends in forest research and forestry Topics include ecology and ecophysiology, genetics and improvement, tree physiology, wood quality, and silviculture -Formerly known as Annales des Sciences Forestières -Biology of trees and associated organisms (symbionts, pathogens, pests) -Forest dynamics and ecosystem processes under environmental or management drivers (ecology, genetics) -Risks and disturbances affecting forest ecosystems (biology, ecology, economics) -Forestry wood chain (tree breeding, forest management and productivity, ecosystem services, silviculture and plantation management) -Wood sciences (relationships between wood structure and tree functions, and between forest management or environment and wood properties)
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信