mlsanityData to 7 Oct 2026

MethaneMapper: Spectral Absorption aware Hyperspectral Transformer for Methane Detection

arXiv 2304.02767 ↗First posted 5 Apr 2023eess.IV cs.CV cs.LGcited by 12

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Abstract (arXiv)

Methane (CH4) 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

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 15 of its 53 references that are in the map. First posted on arXiv 5 Apr 2023.

Builds on

15 of 53 references.

References · 15

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3 more
  1. 2020StressNet: Detecting Stress in Thermal Videoscited by 6
  2. 2022LOCL: Learning Object-Attribute Composition using Localizationcited by 3
  3. 2023In-situ Water quality monitoring in Oil and Gas operationscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 7; 2026: 3.

12 papers.