STAC specification is getting closer to the ver 1.0 milestone, and as such the first virtual Cloud Native Geospatial Sprint is being organized next week. An outreach day is planned on Sep 8th with a series of talks and tutorials for everyone. Read more about the sprint in this blog post by our Technology Fellow Chris Holmes. A new addition to the sprint is a data labeling contest!

STAC規范越來越接近1.0版本的里程碑，因此，下周將組織第一個虛擬Cloud Native Geospatial Sprint 。 計劃在9月8日舉辦外展日，并為每個人提供一系列講座和教程。 在我們的技術研究員克里斯·霍姆斯(Chris Holmes)的博客中閱讀有關沖刺的更多信息。 sprint的新成員是數據標簽競賽！

If you have followed our blogs, we have written many times on the importance of open-access and high-quality labels on satellite imagery for building geospatial machine learning models. A scalable solution to generate labels for a large number of imagery is to run crowdsourcing campaigns and encourage the community to contribute to open-access training data catalogs.

如果您關注我們的博客 ，我們已經多次撰寫了關于衛星圖像上開放獲取和高質量標簽對于構建地理空間機器學習模型的重要性的文章。 為大量圖像生成標簽的可擴展解決方案是運行眾包活動并鼓勵社區為開放獲取培訓數據目錄做出貢獻。

我們在貼什么標簽？ (What are we labeling?)

While multispectral satellite imagery provide valuable and timely observations globally, the presence of clouds in the imagery makes them unusable for monitoring land surface. Indeed, some regions around the world are covered by clouds almost daily. So, it’s essential to be able to detect clouds in the imagery and mask them before running any analysis.

盡管多光譜衛星影像可在全球范圍內提供有價值且及時的觀測結果，但影像中云的存在使它們無法用于監視地面。 實際上，世界上某些地區幾乎每天都被烏云遮蓋。 因此，在執行任何分析之前，必須能夠檢測出圖像中的云并對其進行遮罩，這一點至關重要。

We have decided to run a data labeling contest for identifying cloud (and background) pixels in Sentinel-2 scenes to enable the development of an accurate cloud detection model from multispectral data. Several scenes from Digital Earth Africa’s (DEA) Sentinel-2 catalog have been selected. DEA’s team has converted all of the Sentinel-2 imagery across Africa to COG and hosted them on AWS (check it out here).

我們已決定舉辦一次數據標簽競賽，以識別Sentinel-2場景中的云(和背景)像素，從而能夠從多光譜數據中開發出準確的云檢測模型。 從非洲數字地球(DEA)的Sentinel-2目錄中選擇了幾個場景。 DEA的團隊已將整個非洲的所有Sentinel-2圖像轉換為COG，并將其托管在AWS上( 在此處查看 )。

After the completion of the contest, the resulting training dataset will be hosted on Radiant MLHub with a CC BY 4.0 license for public access.

競賽結束后，最終的訓練數據集將以CC BY 4.0許可證托管在Radiant MLHub上 ，以供公眾訪問。

我們如何標記圖像？ (How are we going to label imagery?)

Azavea’s GroundWork platform is being used for the contest. Their team has already ingested a set of Sentinel-2 scenes from DEA’s catalog and created several projects that will be shared with participants. Each scene will be divided into 512 x 512 pixel tasks on GroundWork, and participants can choose to label any of them or automatically get assigned to a task.

Azavea的GroundWork平臺正在用于比賽。 他們的團隊已經從DEA的目錄中提取了一組Sentinel-2場景，并創建了幾個項目，這些項目將與參與者共享。 每個場景將在GroundWork上劃分為512 x 512像素的任務，參與者可以選擇標記其中的任何一個或自動分配給任務。

In each task, you should label cloud and background pixels and ensure that all pixels are assigned to either of the two classes before submitting them. You will receive detailed instructions from GroundWork’s team on how to use the tool and identify cloudy pixels.

在每個任務中，應標記云像素和背景像素，并確保在提交所有像素之前將其分配給兩個類中的任何一個。 您將收到GroundWork團隊的詳細說明，以了解如何使用該工具和識別模糊像素。

計分 (Scoring)

We have defined a score to rank your contribution in the contest based on a combination of the number of tasks you finish and their complexity. For example, tasks that have no cloudy pixels are much easier to label compared to tasks that have many small patches of altocumulus cloud.

我們已經定義了一個分數，可以根據您完成的任務數量及其復雜程度來對您在比賽中的貢獻進行排名。 例如，與具有許多小積云的任務相比，沒有渾濁像素的任務更容易標記。

S: Your score

S：你的分數

N_tasks: Number of tasks completed (completed is defined as all pixels labeled)

N_tasks：已完成的任務數(已完成的定義為所有標有像素的像素)

N_polygons: Number of polygons completed overall (polygons of both cloud and background classes will be counted)

N_polygons：整體完成的多邊形數量(將同時計算云類和背景類的多邊形)

f_cloud: fraction of cloud-labeled pixels in a completed task

f_cloud：已完成任務中云標記像素的比例

f_background: fraction of background-labeled pixels in a completed task

f_background：完成的任務中帶有背景標簽的像素的比例

For example, if you finish two tasks, one of them with a single cloudy polygon covering 30% of the task, and another one with two cloudy polygons covering 40% of the task, your score will be:

例如，如果您完成了兩個任務，其中一個任務覆蓋了任務的30％，一個多云多邊形，而另一個任務覆蓋了任務的40％，兩個多云多邊形，您的得分將是：

獲獎情況 (Awards)

A number of awards will be presented to top contributors of the contest:

競賽的主要貢獻者將獲得許多獎項：

• Top Labeler — $2000 plus an open 50cm SkySat Image, tasked by the winner.

  頂級貼標機-2000美元，外加50厘米的開放式SkySat圖像 ，由獲勝者負責。

• 2nd and 3rd place labelers — Jacket or $200
  第二和第三名貼標機—夾克或$ 200
• Top Labeler from an African Country (who is not in the top 3 prizes) — Jacket or $200
  非洲國家/地區的最佳貼標機(不是前三名)–夾克或$ 200
• Top Woman Labeler (who is not in the top 3 prizes) — Jacket or $200
  頂級女性貼標機(不在前三名中)-夾克或$ 200
• Next 5 top labelers — Hoodie or $60
  接下來的5個頂級貼標商-連帽衫或$ 60
• Anyone with a minimum score of 10 on the leaderboard — t-shirt or $20
  排行榜上最低分數為10的任何人-T恤或$ 20

Read more about all the awards of the Cloud Native Geospatial Sprint here.

在此處閱讀有關Cloud Native Geospatial Sprint的所有獎項的更多信息。

如何參加？ (How to participate?)

Fill out this form, and you will receive an email from GroundWork on Sep 8th at 10am PDT (5pm UTC) notifying you about the projects that are ready to be labeled. Depending on the completion rate of projects, we will add more projects throughout the contest.

填寫此表格，您將在9月8日美國太平洋夏令時間上午10點(世界標準時間下午5點)收到GroundWork發出的電子郵件，通知您有關已準備好貼標簽的項目。 根據項目的完成率，我們將在比賽中添加更多項目。

You will have until 11:59pm PDT on Sep 15th (6:59am UTC on Sep 16th) to participate and label imagery. After that the leaderboard will be closed and awardees will be selected.

您將在美國夏令時(PDT)9月15日晚上11:59(UTC時間9月16日上午6:59)之前參與并標記圖像。 之后，排行榜將被關閉，獲獎者將被選中。

松弛通道 (Slack Channel)

We have created a new channel on Radiant MLHub’s slack named, #stac-6-labeling-contest, for participants to share their experience with each other. If you are already on our slack workspace, search for the channel and join. If not you can join the workspace using this link, and then join the channel.

我們在Radiant MLHub的閑暇處創建了一個名為＃stac-6-labeling-contest的新頻道，供參與者彼此分享經驗。 如果您已經在我們的閑置工作空間中，請搜索頻道并加入。 如果不是，您可以使用此鏈接加入工作區，然后加入頻道。

Finally, this wouldn’t have been possible without the support of our sponsors. Thanks to Planet, Microsoft, Azavea, and Radiant Earth Foundation for sponsoring this event.

最后，沒有我們的贊助商的支持，這是不可能的。 感謝Planet，Microsoft，Azavea和Radiant Earth Foundation贊助了此活動。

Looking forward to seeing many of you in the contest!

期待在比賽中與大家見面！