At the UKHO, we use data science to gain valuable insight into the data sets we hold and further our understanding of the marine environment around us.

在UKHO，我們使用數據科學獲得對所擁有數據集的寶貴見解，并進一步了解周圍的海洋環境。

One of our latest projects combines satellite imagery and computer vision techniques to enable us to automate the creation of new coastline data.

我們的最新項目之一將衛星圖像和計算機視覺技術相結合，使我們能夠自動創建新的海岸線數據。

新的海岸線數據集 (A new coastline data set)

Automating the creation of coastline data was important to us for a variety of reasons. Firstly, we wanted to form the basis for performing global change detection. For us, this would help us to be more proactive in updating our portfolio of navigational charts.

出于多種原因，自動化海岸線數據創建對我們很重要。 首先，我們希望為執行全局變更檢測奠定基礎。 對于我們來說，這將幫助我們更加主動地更新導航圖產品組合。

Beyond navigation, this data could also help to support other activities carried out by customers and partners, including:

除了導航之外，這些數據還可以幫助支持客戶和合作伙伴進行的其他活動，包括：

• Monitoring the natural environment (including erosion, sedimentation, subsidence etc.)
  監測自然環境(包括侵蝕，沉積，沉降等)
• Developing tidal and coastal models (including currents, tides and ocean modelling)
  開發潮汐和沿海模型(包括洋流，潮汐和海洋模型)
• Supporting disaster resilience
  支持災難復原力

And finally, this would be a first step for us in producing much higher resolution data, that could then improve upon the accuracy and currency of other freely available coastline data sets.

最后，這將是我們生成更高分辨率數據的第一步，然后可以提高其他免費獲得的海岸線數據集的準確性和時效性。

This method needed to be fully automated, repeatable and able to cope with a variety of different coastline types found across the globe.

這種方法需要完全自動化，可重復使用，并且能夠應對全球范圍內各種不同的海岸線類型。

這個怎么運作 (How it works)

First, we gather free, open-source optical satellite imagery with 10x10m pixels (available in Earth Engine). Sometimes pixels in these images can be obscured by shadow and cloud. So, by collecting all images taken of an area over the course of a year, we were able to select the ‘best pixel’ for every individual pixel location. By combining all the best pixels, we created a single image of the whole area that was free from any obscurities.

首先，我們收集了10x10m像素的免費開放源光學衛星圖像(可在Earth Engine中獲得 )。 有時，這些圖像中的像素可能會被陰影和云遮蓋。 因此，通過收集一年中某個區域的所有圖像，我們能夠為每個像素位置選擇“最佳像素”。 通過結合所有最佳像素，我們創建了整個區域的單一圖像，沒有任何模糊感。

From this single image, we then identify areas of water by calculating what is called the ‘Normalised Difference Water Index’ (NDWI) : a remote sensing technique that uses the green and infrared bands to indicate the presence of water.

然后，從這幅單一圖像中，我們通過計算所謂的“歸一化差異水指數”(NDWI)來識別水域：這是一種使用綠色和紅外波段指示水的存在的遙感技術。

On further analysis of our results, we then discovered that we needed to account for localised variation. To overcome this issue we calculated the land/water threshold for small areas dynamically using a method called Otsu thresholding, which finds the optimum value between two groups of pixels.

在對結果進行進一步分析時，我們發現需要考慮局部變化。 為了克服這個問題，我們使用稱為Otsu閾值的方法動態計算了小區域的土地/水閾值 ，該方法在兩組像素之間找到了最佳值。

We then used the outputs from this pipeline to produce a vectorised image of the coastline using PostGIS.

然后，我們使用該管道的輸出，使用PostGIS生成海岸線的矢量化圖像。

結果 (The result)

The first data generated by this pipeline covers the British Isles (except for Rockall, which was too small given the resolution of the imagery!).

該管道生成的第一批數據涵蓋了不列顛群島(Rockall除外，考慮到圖像的分辨率，該數據太小了！)。

Below you can see a data set of the British Isles, created using a total of 4,084 Sentinel-2 images:

在下面，您可以查看不列顛群島的數據集，該數據集使用總共4,084個Sentinel-2圖像創建：

This is the first time that coastline has been automatically generated at the UKHO and the process is still being evaluated, developed and improved. As such, we are not producing this data for navigational purposes yet.

這是UKHO首次自動生成海岸線，并且該過程仍在評估，開發和改進中。 因此，我們尚未出于導航目的生成此數據。

To assess the success of our method, we compared our results to the widely-used NGA World Vector Shoreline (WVS) data set. The comparison showed that our methods captured better detail and accuracy in some instances, as you can see from the images below (where the WVS is shown in red and our results shown in blue):

為了評估我們方法的成功，我們將我們的結果與廣泛使用的NGA世界矢量海岸線(WVS)數據集進行了比較。 通過比較可以看出，在某些情況下，我們的方法捕獲了更好的細節和準確性，如您從下面的圖片中可以看到的(WVS以紅色顯示，我們的結果以藍色顯示)：

In addition to these results, we generated coastline in over 40 areas around the rest of the world to test the performance of the model in different geographic locations, to help us understand what areas need improvement.

除了這些結果之外，我們還在世界其他地區的40多個區域生成了海岸線，以測試模型在不同地理位置的性能，以幫助我們了解哪些區域需要改進。

訪問數據集 (Accessing the data set)

A data set of the British Isles is now available to access via the ADMIRALTY Marine Data Portal — our platform for marine data sets held by the UKHO. This data is currently in the alpha stage and further improvements are being made.

現在可以通過ADMIRALTY海洋數據門戶網站訪問英倫三島的數據集，這是UKHO持有的海洋數據集平臺。 該數據目前處于Alpha階段，并且正在進一步改進。

Access the coastline data set on the ADMIRALTY Marine Data Portal.

在ADMIRALTY海洋數據門戶上訪問海岸線數據集。

This article originally appeared on ukhodigital.blog.gov.uk

本文最初出現在 ukhodigital.blog.gov.uk