Mapping Onshore CH4 Seeps in Western Siberian Floodplains Using Convolutional Neural Network

• Published in: Remote Sensing
• Main Authors: Irina Terentieva, Ilya Filippov, Aleksandr Sabrekov, Mikhail Glagolev
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2022
• Subjects: Western Siberia; seeps; floodplains; methane emission; convolutional neural networks; sentinel-2; mapping; ob river; Siberia
• Online Access: https://doi.org/10.3390/rs14112661

Onshore seeps are recognized as strong sources of methane (CH4), the second most important greenhouse gas. Seeps actively emitting CH4 were recently found in floodplains of West Siberian rivers. Despite the origin of CH4 in these seeps is not fully understood, they can make substantial contribution in regional greenhouse gas emission. We used high-resolution satellite Sentinel-2 imagery to estimate seep areas at a regional scale. Convolutional neural network based on U-Net architecture was implemented to overcome difficulties with seep recognition. Ground-based field investigations and unmanned aerial vehicle footage were coupled to provide reliable training dataset. The seep areas were estimated at 2885 km2 or 1.5% of the studied region; most seep areas were found within the Ob’ river floodplain. The overall accuracy of the final map reached 86.1%. Our study demonstrates that seeps are widespread throughout the region and provides a basis to estimate seep CH4 flux in entire Western Siberia.