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iNaturalist

iNaturalist

iNaturalist

Education免费v1.0.20
App Store
评分

3.9

491 条评分

星级

★★★★☆

最近更新

2026年5月5日

发布日期

2024年9月9日

更新内容

v1.0.20

Try the iNaturalist app! Quick identification: Point your camera at a plant, animal, or other organism to get an instant identification. More ways to observe: Press and hold the camera button for more observation options, like recording sounds and adding multiple photos. Keep up with other naturalists: Check your notifications to see when other people in the iNaturalist community add identifications or ask questions about your observations. Set your preferences: If you're a longtime user and want your app experience to feel more like earlier versions of iNaturalist, you can! Go into Settings, enable Advanced Mode, then select "Edit Observation" in the middle section. Thank you for using iNaturalist! Please let us know what you think about the app by using the Feedback form available in the main menu.

应用信息

开发者
iNaturalist
分类
Education
价格
免费
版本
1.0.20
App ID
6475737561

简介

Point the camera at plants, animals, & fungi to see species suggestions while you’re outside, or import photos from your library. iNaturalist helps millions of people like you learn more about nature using AI suggestions backed up by a global community of knowledgeable nature lovers. iNaturalist goes far beyond AI identifications—your observations are reviewed by real people and shared for science to help protect species. KEY FEATURES Identify species from anywhere in the world Keep a record of species you see Contribute to science by sharing your observations Explore and protect biodiversity Connect with and learn from other nature enthusiasts iNaturalist’s nonprofit mission is to connect people to nature and advance science and conservation. iNaturalist is freely available thanks to generous support from our community of donors. Explore and learn even more at https://www.inaturalist.org.

下载量预测

专业 · 预览

预估总下载量

36K25K70K
保守估计乐观估计

1K

低 / 月

2K

预估 / 月

4K

高 / 月

基于491 条评分
假设评分率1.4%
应用年龄20 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。