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，我们使用数据科学获得对所拥有数据集的宝贵见解，并进一步了解周围的海洋环境。

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

我们的最新项目之一将卫星图像和计算机视觉技术相结合，使我们能够自动创建新的海岸线数据。

新的海岸线数据集 (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.

出于多种原因，自动化海岸线数据创建对我们很重要。 首先，我们希望为执行全局变更检测奠定基础。 对于我们来说，这将帮助我们更加主动地更新导航图产品组合。

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

除了导航之外，这些数据还可以帮助支持客户和合作伙伴进行的其他活动，包括：

• Monitoring the natural environment (including erosion, sedimentation, subsidence etc.)
  监测自然环境(包括侵蚀，沉积，沉降等)
• Developing tidal and coastal models (including currents, tides and ocean modelling)
  开发潮汐和沿海模型(包括洋流，潮汐和海洋模型)
• Supporting disaster resilience
  支持灾难复原力

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，这将是我们生成更高分辨率数据的第一步，然后可以提高其他免费获得的海岸线数据集的准确性和时效性。

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

这种方法需要完全自动化，可重复使用，并且能够应对全球范围内各种不同的海岸线类型。

这个怎么运作 (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，我们收集了10x10m像素的免费开放源光学卫星图像(可在Earth Engine中获得 )。 有时，这些图像中的像素可能会被阴影和云遮盖。 因此，通过收集一年中某个区域的所有图像，我们能够为每个像素位置选择“最佳像素”。 通过结合所有最佳像素，我们创建了整个区域的单一图像，没有任何模糊感。

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，从这幅单一图像中，我们通过计算所谓的“归一化差异水指数”(NDWI)来识别水域：这是一种使用绿色和红外波段指示水的存在的遥感技术。

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.

在对结果进行进一步分析时，我们发现需要考虑局部变化。 为了克服这个问题，我们使用称为Otsu阈值的方法动态计算了小区域的土地/水阈值 ，该方法在两组像素之间找到了最佳值。

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

然后，我们使用该管道的输出，使用PostGIS生成海岸线的矢量化图像。

结果 (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!).

该管道生成的第一批数据涵盖了不列颠群岛(Rockall除外，考虑到图像的分辨率，该数据太小了！)。

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

在下面，您可以查看不列颠群岛的数据集，该数据集使用总共4,084个Sentinel-2图像创建：

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.

这是UKHO首次自动生成海岸线，并且该过程仍在评估，开发和改进中。 因此，我们尚未出于导航目的生成此数据。

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):

为了评估我们方法的成功，我们将我们的结果与广泛使用的NGA世界矢量海岸线(WVS)数据集进行了比较。 通过比较可以看出，在某些情况下，我们的方法捕获了更好的细节和准确性，如您从下面的图片中可以看到的(WVS以红色显示，我们的结果以蓝色显示)：

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.

除了这些结果之外，我们还在世界其他地区的40多个区域生成了海岸线，以测试模型在不同地理位置的性能，以帮助我们了解哪些区域需要改进。

访问数据集 (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.

现在可以通过ADMIRALTY海洋数据门户网站访问英伦三岛的数据集，这是UKHO持有的海洋数据集平台。 该数据目前处于Alpha阶段，并且正在进一步改进。

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

在ADMIRALTY海洋数据门户上访问海岸线数据集。

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

本文最初出现在 ukhodigital.blog.gov.uk