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使用谷歌街景对自由流浪狗种群的估计:一项方法学研究
Guillermo Porras1, Elvis W Diaz1, Micaela De la Puente-León1
1Zoonotic Disease Research Lab, One Health Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru.
PloS one
|July 31, 2025
概括
使用谷歌街景 (GSV) 估计自由流浪狗种群提供了一个有前途的远程方法,特别是在城市环境中. 这种公民科学方法通过为疾病控制计划提供关键数据来帮助公共卫生.
科学领域:
- 兽医公共卫生 兽医公共卫生
- 地理空间分析是什么
- 公民科学 公民科学
背景情况:
- 对狗种群的准确定量知识对于控制狂犬病等动物传播疾病至关重要.
- 传统的狗种群估计方法是资源密集型,耗时且潜在危险的.
- 开发高效可靠的远程估计技术对于公共卫生倡议至关重要.
研究的目的:
- 评估谷歌街景 (GSV) 作为远程传感工具用于估计自由流浪狗种群的有效性.
- 为了比较基于GSV的狗计数与传统的门对门 (D2D) 调查数据.
- 评估公民科学方法对狗种群估计的可行性.
主要方法:
- 通过社交媒体招募和培训公民科学家,使用GSV图像识别和计数自由流浪的狗.
- 收集了秘鲁20个城市和6个郊区社区的GSV数据.
- 使用相关性指标和负二项式模型来比较GSV计数与D2D调查数据.
主要成果:
- 公民科学家通过GSV识别了862只狗,经过调整后估计有1022只自由流浪的狗.
- 在城市地区的GSV和D2D计数之间发现了强烈的正相关性 (r=0.85,p<0.001).
- 在城市周边地区观察到较弱的相关性 (r=0.36,p=0.478),由于图像可用性存在挑战.
结论:
- 谷歌街景,结合公民科学,为估计狗种群提供了一种可行且有前途的方法,特别是在城市环境中.
- 这种遥感方法可以补充传统方法,为资源有限的环境中疾病控制计划提供有价值的数据.
- GSV的有效性可能因社区类型和高分辨率图像的可用性而异.
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