Peatlands, constituting over half of terrestrial wetland ecosystems across the globe, hold critical ecological significance and are large stores of carbon (C). Irish oceanic raised bogs are a rare peatland ecosystem offering numerous ecosystem services, including C storage, biodiversity support and water regulation. However, they have been degraded over the centuries due to artificial drainage, followed by peat extraction, afforestation and agriculture. This has an overall negative impact on the functioning of peatlands, shifting them from a moderate C sink to a large C source. Recognizing the importance of these ecosystems, efforts are underway for conservation (rewetting and rehabilitation), while accurately accounting for C stock and greenhouse gas (GHG) emissions. However, the implementation of these efforts requires accurate identification and mapping of artificial drainage ditches. This study utilized very high‐resolution (25 cm) aerial imagery, and a deep learning (U‐Net) approach to map the visible artificial drainage (unobstructed by vegetation or infill) in raised bogs at a national scale. The results show that artificial drainage is widespread, with ~20 000 km of drains mapped. The overall accuracy of the model was 80% on an independent testing dataset. The data were also used to derive the Fracditch which was 0.03 (fraction of artificial drainage on industrial peat extraction sites). This is lower than IPCC Tier 1 Fracditch and can aid in IPCC Tier 2 reporting for Ireland. This is the first study to map drains with diverse sizes and patterns on Irish‐raised bogs using optical aerial imagery and deep learning methods. The map will serve as an important baseline dataset for evaluating the artificial drainage ditch conditions. It will prove useful for sustainable management, conservation and refined estimations of GHG emissions. The model's capacity for generalization implies its potential in mapping artificial drains in peatlands at a regional and global scale, thereby enhancing the comprehension of the global effects of artificial drainage ditches on peatlands.

中文翻译：

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绘制泥炭地人工排水沟——使用亚米级航空图像和深度学习方法对爱尔兰沼泽进行全国范围的评估

泥炭地占全球陆地湿地生态系统的一半以上，具有重要的生态意义，并且是大量的碳 (C) 储存库。爱尔兰海洋凸起沼泽是一种罕见的泥炭地生态系统，提供众多生态系统服务，包括碳储存、生物多样性支持和水调节。然而，几个世纪以来，由于人工排水以及随后的泥炭开采、造林和农业，它们已经退化。这对泥炭地的功能产生了总体负面影响，使其从中等碳汇转变为大型碳源。认识到这些生态系统的重要性，正在努力进行保护（再润湿和恢复），同时准确计算碳库和温室气体（GHG）排放。然而，这些努力的实施需要准确识别和绘制人工排水沟。这项研究利用超高分辨率（25 厘米）航空图像和深度学习 (U-Net) 方法来绘制全国范围内凸起沼泽中可见的人工排水系统（不受植被或填充物阻碍）。结果表明，人工排水十分普遍，已绘制出约 20,000 公里的排水沟。该模型在独立测试数据集上的总体准确率为 80%。该数据还用于推导压裂沟为 0.03（工业泥炭开采场地人工排水的比例）。这低于 IPCC Tier 1 Frac沟并可以协助爱尔兰进行 IPCC 第 2 级报告。这是第一项利用光学航空图像和深度学习方法绘制爱尔兰沼泽上不同尺寸和图案的排水沟的研究。该图将作为评估人工排水沟状况的重要基线数据集。事实证明，它对于温室气体排放的可持续管理、保护和精确估算很有用。该模型的泛化能力意味着其在区域和全球范围内绘制泥炭地人工排水沟的潜力，从而增强对人工排水沟对泥炭地的全球影响的理解。