MethaneMapper: Spectral Absorption aware Hyperspectral Transformer for Methane Detection

• URL: http://arxiv.org/abs/2304.02767v1
• Date: Wed, 5 Apr 2023 22:15:18 GMT
• Title: MethaneMapper: Spectral Absorption aware Hyperspectral Transformer for Methane Detection
• Authors: Satish Kumar, Ivan Arevalo, ASM Iftekhar, B S Manjunath
• Abstract summary: Methane is the chief contributor to global climate change. We propose a novel end-to-end spectral absorption wavelength aware transformer network, MethaneMapper, to detect and quantify the emissions. MethaneMapper achieves 0.63 mAP in detection and reduces the model size (by 5x) compared to the current state of the art.
• Score: 13.247385727508155
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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

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