Citizen science has become key to biodiversity monitoring but critically depends on accurate quality control that is scalable and tailored to the focal region. We developed FlorID, a free-to-use identification service for all native and many non-native plants of Switzerland. FlorID can identify >3000 species, using vision transformers trained on 1.5M photos, and ecological predictions from multilayer perceptrons, trained on 6.7M occurrence observations and 20 high-resolution environmental variables. Embedded in a free-to-use application programming interface, FlorID can be accessed directly, via webservice, and via FlorApp smartphone application. If multiple images and spatiotemporal location are available, FlorID correctly identifies 93% of field observations and has a top-5 accuracy of 99%. Ecological predictions boost identification success especially for native species with distinct distributions. By evaluating information on appearance and fine-grained ecology, FlorID is a blueprint for similar solutions targeting different taxa or regions, and a basis for developments like automated community inventories.

中文翻译：

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FlorID – 从照片和栖息地信息中对植物进行全国性的鉴定服务


公民科学已成为生物多样性监测的关键，但关键是取决于可扩展的、针对重点区域量身定制的准确质量控制。我们开发了 FlorID，这是一项免费使用的鉴定服务，适用于瑞士的所有本地和许多非本地植物。FlorID 可以使用在 1.5M 照片上训练的视觉转换器来识别 >3000 物种，并使用基于 6.7M 出现观察和 20 个高分辨率环境变量训练的多层感知器的生态预测。FlorID 嵌入在免费使用的应用程序编程接口中，可以通过网络服务和 FlorApp 智能手机应用程序直接访问。如果有多个图像和时空位置可用，则 FlorID 可以正确识别 93% 的外业观测值，并且前 5 名的准确率为 99%。生态预测可以提高识别成功率，尤其是对于分布不同的本地物种。通过评估外观和细粒度生态学信息，FlorID 是针对不同分类群或区域的类似解决方案的蓝图，也是自动化社区清单等开发的基础。