說明
Dataset of species records extracted from video footage recorded by remotely operated vehicles (ROVs) in the marine protected area Kosterhavets nationalpark on the Swedish west-coast. The original movies were collected during 1997-2023. This data set is based on videos of 70 transects across slopes and rock walls in the National Park at depths between 7-105 m. Species records were extracted from the movies using Yolov8 model, while depth information was extracted with the easyOCR python package from the ROV video overlays. Original videos are archived and accessible at Tjärnö Marine Laboratory’s (Univerisity of Gothenburg). The analysis was performed using the Swedish platform for subsea image analysis (www.subsim.se). We acknowledge the support of the technical officers and ROV pilots at Tjärnö Marine Laboratory, in particular Tomas Lundälv, Roger Johannesson, and Joel White.
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 72,369 筆紀錄。
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。:
Nilsson C (2024). Koster historical biodiversity assessment. Version 1.4. Wildlife.ai. Occurrence dataset. https://ipt.gbif.org.nz/resource?r=koster_historical_assessment&v=1.4
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 Wildlife.ai。 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: 51d0bd32-e215-45ea-a04d-47a474336125。 Wildlife.ai 發佈此資源，並經由GBIF New Zealand同意向GBIF註冊成為資料發佈者。
關鍵字
Occurrence; Machine Observations; YOLOv8; Benthic Invertebrates; Koster; Hard Substrate; Marine Biology; Marine Biodiversity; Marine Ecology; Subtidal Zone; Observation; Machine Observations; YOLOv8; Benthic Invertebrates; Koster; Hard Substrate; Marine Biology; Marine Biodiversity; Marine Ecology; Subtidal Zone
聯絡資訊
- 元數據提供者 ●
- 出處 ●
- 連絡人 ●
- 研究主持人
- Researcher
- Anders Zornsgatan 34B
- 0730682795
https://orcid.org/0009-0005-6356-2152
- 連絡人
- Research Engineer
- Laboratorievägen 10
- +46 31-786 96 03
- 程式設計師
- Researcher
- 程式設計師
- Data Scientist
- Västra Hamngatan 8
- 擁有者
- Researcher
- Medicinaregatan 7B
- +4676-618 38 27
地理涵蓋範圍
Data collected from the area west of the island of Yttre Vattenholmen. For additional information, feel free to contact authors.
| 界定座標範圍 | 緯度南界 經度西界 [58.9, 11.1], 緯度北界 經度東界 [58.9, 11.1] |
|---|
時間涵蓋範圍
| 起始日期 / 結束日期 | 1997-08-27 / 2023-10-09 |
|---|
計畫資料
Biodiversity assessment of distribution size and relative abundance of 17 unique benthic invertebrate taxa. Assessment made by applying a YOLOv8 model trained on image data from ROV footage of the study site to 70 ROV transects from 1997-2023.
| 計畫名稱 | Depth Learning - Using Deep-Learning Object Detection Software to Investigate Spatiotemporal Vertical Ecological Trends on a Submarine Canyon Wall in Northern Skagerrak |
|---|---|
| 研究區域描述 | Rock walls and slopes from 7-105m in the area west of the island of Yttre Vattenholmen. |
參與計畫的人員:
取樣方法
Sampling was performed by ROV from Tjärnö Marine Laboratory. Transects were taken for various purposes and are non-standardized. Thus, time spent at each depth and distance to substrate may vary. Transects are defined as consecutive filming of the study site until departure and may have depths removed if the ROV was not filming the habitat of interest for this study (hard substrate) at these depths. Additionally, inconsistency may exist between substrate depths and ROV depths where the ROV was not filming perpendicular to the seafloor. For further information, contact Joel White or Christian Nilsson.
| 研究範圍 | Archived ROV footage from the area west of Yttre Vattenholmen was utilized. All footage available with sufficient depth information was utilized. Footage was collected for various purposes, therefore sampling frequency & temporal resolution varies. |
|---|---|
| 品質控管 | Average maxcount per depth (organismQuantity) was added to provide insight regarding false positives. If individualCount for an observation is significantly higher than organismQuantity a false positive may be possible. For further information, contact Christian Nilsson. |
方法步驟描述:
- ROV depth for each image frame of videos was extracted from the video overlay using the EasyOCR python package. Depth was connected to YOLOv8 model observations through frame number in R, after which maximum and mean individual count was summarized from each transect for each taxon.
引用文獻
- Koster historical invertebrate model - SUBSIM 17tx. (model used to generate annotations) https://doi.org/10.5281/zenodo.13589902
額外的詮釋資料
| 替代的識別碼 | 51d0bd32-e215-45ea-a04d-47a474336125 |
|---|---|
| https://ipt.gbif.org.nz/resource?r=koster_historical_assessment |