出現紀錄

Pl@ntNet observations

最新版本 由 Pl@ntNet 發佈於 2023年2月8日 Pl@ntNet
首頁:
連結
發布日期:
2023年2月8日
Published by:
Pl@ntNet
授權條款:
CC-BY 4.0

下載最新版本的 Darwin Core Archive (DwC-A) 資源,或資源詮釋資料的 EML 或 RTF 文字檔。

DwC-A資料集 下載 1,714,213 紀錄 在 English 中 (320 MB) - 更新頻率: 無計畫更新
元數據EML檔 下載 在 English 中 (16 KB)
元數據RTF文字檔 下載 在 English 中 (11 KB)

說明

Pl@ntNet is a participatory botanical observation platform allowing to identify plants from photos (using deep learning) and to share the observations with the community. The platform has three main front-ends: Pl@ntNet androïd (http://bit.ly/1K4D1eU), Pl@ntNet iOS (http://apple.co/2cMtWgu) and Pl@ntNet web (https://identify.plantnet.org/). Pl@ntNet was founded in 2010 by a consortium of four French research organisms (CIRAD, Inria, INRAE and IRD) and is now open to other members. More information about Pl@ntNet project can be found at https://plantnet.org/. The observations in this collection are the ones for which the authors agree to share the associated pictures under a creative common licence and for which the species name is considered as valid.

資料紀錄

此資源出現紀錄的資料已發佈為達爾文核心集檔案(DwC-A),其以一或多組資料表構成分享生物多樣性資料的標準格式。 核心資料表包含 1,714,213 筆紀錄。

亦存在 1 筆延伸集的資料表。延伸集中的紀錄補充核心集中紀錄的額外資訊。 每個延伸集資料表中資料筆數顯示如下。

Occurrence (核心)
1714213
Multimedia 
2131755

此 IPT 存放資料以提供資料儲存庫服務。資料與資源的詮釋資料可由「下載」單元下載。「版本」表格列出此資源的其它公開版本,以便利追蹤其隨時間的變更。

版本

以下的表格只顯示可公開存取資源的已發布版本。

如何引用

研究者應依照以下指示引用此資源。:

AFFOUARD A, JOLY A, LOMBARDO J, CHAMP J, GOEAU H, CHOUET M, GRESSE H, BONNET P (2023): Pl@ntNet observations. v1.8. Pl@ntNet. Dataset/Occurrence. https://ipt.plantnet.org/resource?r=observations&v=1.8

權利

研究者應尊重以下權利聲明。:

此資料的發布者及權利單位為 Pl@ntNet。 This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License.

GBIF 註冊

此資源已向GBIF註冊,並指定以下之GBIF UUID: 7a3679ef-5582-4aaa-81f0-8c2545cafc81。  Pl@ntNet 發佈此資源,並經由GBIF France同意向GBIF註冊成為資料發佈者。

關鍵字

Occurrence; Observation; Occurrence

聯絡資訊

資源建立者:
-

Antoine AFFOUARD
Engineer
Inria
LIRMM
34095 Montpellier
FR
Julien CHAMP
Research Engineer
Inria
LIRMM
34095 Montpellier
FR
Hervé GOEAU
Researcher
CIRAD, AMAP Joint Research Unit
Cirad, Umr Amap - TA A-51/ps1, Bd de La Lironde
34398 Montpellier Cedex 5 (France)
FR
Mathias CHOUET
Engineer
Inria
LIRMM
34095 Montpellier
FR
Hugo GRESSE
Engineer
Inria
LIRMM
34095 Montpellier
FR
Pierre BONNET
Botanist
CIRAD, AMAP Joint Research Unit
Cirad, Umr Amap - TA A-51/ps1, Bd de La Lironde
34398 Montpellier Cedex 5 (France)
FR
http://agents.cirad.fr/index.php/Pierre+BONNET

可回覆此資源相關問題者:

Pierre BONNET
Botanist
CIRAD, AMAP Joint Research Unit
Cirad, Umr Amap - TA A-51/ps1, Bd de La Lironde
34398 Montpellier Cedex 5 (France)
FR
http://agents.cirad.fr/index.php/Pierre+BONNET

元數據填寫者:
-

Antoine AFFOUARD
Engineer
Inria
LIRMM
34095 Montpellier
FR

與此資源的相關者:

Antoine AFFOUARD
程式設計師
Engineer
Inria
LIRMM
34095 Montpellier
FR

地理涵蓋範圍

Plant observations from Pl@ntNet network come from all around the world.

界定座標範圍 緯度南界 經度西界 [-90, -180], 緯度北界 經度東界 [90, 180]

分類群涵蓋範圍

Pl@ntNet observations focus on plants.

Kingdom Plantae (Plant)

計畫資料

PlantNet is a participatory botanical observation platform allowing to identify plants from photos (using deep learning) and share observations with the community. This resource contains illustrated observations explicitly shared by PlantNet users under a Creative Common license.

計畫名稱 Pl@ntNet Observations
辨識碼 observations
經費來源 PlantNet is an open consortium founded by four French research organizations (CIRAD, Inria, INRAE, IRD) and supported by Agropolis Fondation. The two main funding resources are: (i) the annual contribution of the members of the consortium, (ii) donations from the end-users of PlantNet application (>10 million users).
研究區域描述 Entire world

參與計畫的人員:

Antoine AFFOUARD
程式設計師
Alexis JOLY
Pierre BONNET

取樣方法

No sampling protocol, opportunistic observations by Pl@ntNet users.

研究範圍 Entire world, Plantae.
品質控管 The validation is based on three main criteria: - the identification confidence score greater than a given threshold, the score being inferred from (i) the output of the automated identification algorithm (categorical probability) and (ii) the species names proposed by the members - the contributor has a reputation score higher than a given threshold - the species name matches the checklist considered as the most trusted one for the country where the observation was done

方法步驟描述:

  1. This collection contains observations of plants shared by Pl@ntNet users using one the three Pl@ntNet applications (androïd, iOS, web, more information here: https://plantnet.org/). The following filters were applied: - image license cc-* - is geolocated - is valid (identification score > threshold) - from a user with an enabled account - with a known species name (valid or synonym) in Pl@ntNet - species name != Cannabis - date_observation > 0 - must be in one of the WGSRPD polygon level 3 and the binomial species name (without author) must match a species of the corresponding Kew checklist

引用文獻

  1. Joly, A., Goëau, H., Bonnet, P., Bakić, V., Barbe, J., Selmi, S., ... & Yahiaoui I., Carré J., Mouysset E., Molino J.-f., Boujemaa B., Barthélémy D., (2014). Interactive plant identification based on social image data. Ecological Informatics, 23, 22-34. https://doi.org/10.1016/j.ecoinf.2013.07.006
  2. Joly, A., Bonnet, P., Goëau, H., Barbe, J., Selmi, S., Champ, J., Dufour-Kowalski, S., Affouard, A., Carré, J., Molino, J.-f., Boujemaa, N., & Barthélémy D., (2016). A look inside the Pl@ntNet experience. Multimedia Systems, 22(6), 751-766. https://doi.org/10.1007/s00530-015-0462-9
  3. Goëau, H., Bonnet, P., Joly, A., 2017. Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017). CLEF: Conference and Labs of the Evaluation Forum, Sep 2017, Dublin, Ireland. ⟨hal-01629183⟩ https://hal.archives-ouvertes.fr/hal-01629183
  4. Affouard, A., Goëau, H., Bonnet, P., Lombardo, J. C., & Joly, A., (2017). Pl@ntNet app in the era of deep learning. ICLR: International Conference on Learning Representations, Apr 2017, Toulon, France. ⟨hal-01629195⟩ https://hal.archives-ouvertes.fr/hal-01629195

額外的詮釋資料

替代的識別碼 7a3679ef-5582-4aaa-81f0-8c2545cafc81
https://ipt.plantnet.org/resource?r=observations