Methane (CH$_4$) is the chief contributor to global climate change. Recent Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) has been very useful in quantitative mapping of methane emissions. Existing methods for analyzing this data are sensitive to local terrain conditions, often require manual inspection from domain experts, prone to significant error and hence are not scalable. To address these challenges, we propose a novel end-to-end spectral absorption wavelength aware transformer network, MethaneMapper, to detect and quantify the emissions. MethaneMapper introduces two novel modules that help to locate the most relevant methane plume regions in the spectral domain and uses them to localize these accurately. Thorough evaluation shows that MethaneMapper achieves 0.63 mAP in detection and reduces the model size (by 5x) compared to the current state of the art. In addition, we also introduce a large-scale dataset of methane plume segmentation mask for over 1200 AVIRIS-NG flight lines from 2015-2022. It contains over 4000 methane plume sites. Our dataset will provide researchers the opportunity to develop and advance new methods for tackling this challenging green-house gas detection problem with significant broader social impact. Dataset and source code are public

翻译：甲烷（CH$_4$）是全球气候变化的主要贡献者。近年来的机载可见光/红外成像光谱仪-下一代（AVIRIS-NG）在甲烷排放的定量测绘中发挥了重要作用。现有分析这些数据的方法对局部地形条件敏感，通常需要领域专家进行人工检查，容易产生显著误差，因此难以扩展。为应对这些挑战，我们提出了一种新颖的端到端光谱吸收波长感知Transformer网络——MethaneMapper，用于检测和量化排放。MethaneMapper引入了两个创新模块，帮助定位光谱域中最相关的甲烷羽流区域，并利用这些区域实现精确空间定位。通过全面评估，MethaneMapper在检测任务中实现了0.63的mAP，并将模型规模相比当前最先进方法缩减了5倍。此外，我们还引入了一个大规模数据集，包含2015年至2022年间超过1200条AVIRIS-NG飞行航线的甲烷羽流分割掩膜，涵盖4000多个甲烷羽流站点。该数据集将为研究人员提供机会，开发和推进解决这一具有显著社会影响的温室气体检测难题的新方法。数据集和源代码均已公开。