82 citations as recorded by crossref.

1. Taking Artificial Intelligence Into Space Through Objective Selection of Hyperspectral Earth Observation Applications: To bring the “brain” close to the “eyes” of satellite missions A. Wijata et al. 10.1109/MGRS.2023.3269979
2. A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B Z. He et al. 10.5194/amt-17-2937-2024
3. Global assessment of oil and gas methane ultra-emitters T. Lauvaux et al. 10.1126/science.abj4351
4. SSRMF: A sparse spectral reconstruction enhanced matched filter for improving point-source methane emission detection in complex terrain K. Li et al. 10.1016/j.isprsjprs.2025.04.034
5. Quantifying particulate matter optical properties and flow rate in industrial stack plumes from the PRISMA hyperspectral imager G. Calassou et al. 10.5194/amt-17-57-2024
6. Toward a versatile spaceborne architecture for immediate monitoring of the global methane pledge Y. Wang et al. 10.5194/acp-23-5233-2023
7. Multisatellite Data Depicts a Record-Breaking Methane Leak from a Well Blowout L. Guanter et al. 10.1021/acs.estlett.4c00399
8. Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data H. Wang et al. 10.3390/rs16061023
9. US oil and gas system emissions from nearly one million aerial site measurements E. Sherwin et al. 10.1038/s41586-024-07117-5
10. Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission C. Chan Miller et al. 10.5194/amt-17-5429-2024
11. Single-blind validation of space-based point-source detection and quantification of onshore methane emissions E. Sherwin et al. 10.1038/s41598-023-30761-2
12. Strength in numbers: how the different satellite systems used to monitor methane emissions from space have different, yet complementary, capabilities to help the oil and gas industry meet its decarbonisation goals J. Gauthier 10.1071/AJ21080
13. Detecting and quantifying methane emissions from oil and gas production: algorithm development with ground-truth calibration based on Sentinel-2 satellite imagery Z. Zhang et al. 10.5194/amt-15-7155-2022
14. Reconstructing and quantifying methane emissions from the full duration of a 38-day natural gas well blowout using space-based observations J. Maasakkers et al. 10.1016/j.rse.2021.112755
15. Onshore methane emissions measurements from the oil and gas industry: a scoping review C. Vollrath et al. 10.1088/2515-7620/ad3129
16. Forecasting Rice Status for a Food Crisis Early Warning System Based on Satellite Imagery and Cellular Automata in Malang, Indonesia . Sujarwo et al. 10.3390/su14158972
17. The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps G. Hurtt et al. 10.1088/1748-9326/ac7407
18. Spectrometric imaging of sub-hourly methane emission dynamics from coal mine ventilation M. Knapp et al. 10.1088/1748-9326/acc346
19. Methane point source quantification using MethaneAIR: a new airborne imaging spectrometer A. Chulakadabba et al. 10.5194/amt-16-5771-2023
20. Daily detection and quantification of methane leaks using Sentinel-3: a tiered satellite observation approach with Sentinel-2 and Sentinel-5p S. Pandey et al. 10.1016/j.rse.2023.113716
21. Global Tracking and Quantification of Oil and Gas Methane Emissions from Recurrent Sentinel-2 Imagery T. Ehret et al. 10.1021/acs.est.1c08575
22. Automated detection of atmospheric NO2 plumes from satellite data: a tool to help infer anthropogenic combustion emissions D. Finch et al. 10.5194/amt-15-721-2022
23. CELNet: A comprehensive efficient learning network for atmospheric plume identification from remotely sensed methane concentration images F. Chen et al. 10.1016/j.rse.2025.114828
24. Satellites Detect Abatable Super-Emissions in One of the World’s Largest Methane Hotspot Regions I. Irakulis-Loitxate et al. 10.1021/acs.est.1c04873
25. Satellite-Based Seasonal Fingerprinting of Methane Emissions from Canadian Dairy Farms Using Sentinel-5P P. Prajesh et al. 10.3390/cli13070135
26. High Spatial and Temporal Resolution Simulations of Methane Column Loadings Due to Routine Emissions and Emission Events in Oil and Gas Regions L. Huang et al. 10.1021/acsestair.4c00021
27. An Effective Quantification of Methane Point-Source Emissions with the Multi-Level Matched Filter from Hyperspectral Imagery M. Liang et al. 10.3390/rs17050843
28. Understanding the potential of Sentinel-2 for monitoring methane point emissions J. Gorroño et al. 10.5194/amt-16-89-2023
29. Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observations T. Scarpelli et al. 10.5194/acp-22-3235-2022
30. CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery A. Vaughan et al. 10.5194/amt-17-2583-2024
31. S2MetNet: A novel dataset and deep learning benchmark for methane point source quantification using Sentinel-2 satellite imagery A. Radman et al. 10.1016/j.rse.2023.113708
32. Natural Hydrogen in the Northern Perth Basin, WA Australia: Geospatial Analysis and Detection in Soil Gas for Early Exploration V. Vidavskiy et al. 10.11648/j.jenr.20241302.15
33. Geostationary satellite observations of extreme and transient methane emissions from oil and gas infrastructure M. Watine-Guiu et al. 10.1073/pnas.2310797120
34. Satellites Detect a Methane Ultra-emission Event from an Offshore Platform in the Gulf of Mexico I. Irakulis-Loitxate et al. 10.1021/acs.estlett.2c00225
35. Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space A. Thorpe et al. 10.1126/sciadv.adh2391
36. First Investigation of Long-Term Methane Emissions from Wastewater Treatment Using Satellite Remote Sensing S. Mehrdad et al. 10.3390/rs16234422
37. High-spectral-resolution Fabry-Pérot interferometers overcome fundamental limitations of present volcanic gas remote sensing techniques J. Kuhn et al. 10.3389/feart.2023.1039093
38. Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al. 10.5194/acp-23-7503-2023
39. Sensitivity and Uncertainty in Matched-Filter-Based Gas Detection With Imaging Spectroscopy J. Fahlen et al. 10.1109/TGRS.2024.3440174
40. Advancing the Arctic Methane Permafrost Challenge (AMPAC) With Future Satellite Missions A. Bartsch et al. 10.1109/JSTARS.2025.3538897
41. Current potential of CH4 emission estimates using TROPOMI in the Middle East M. Liu et al. 10.5194/amt-17-5261-2024
42. Improving quantification of methane point source emissions from imaging spectroscopy Z. Pei et al. 10.1016/j.rse.2023.113652
43. Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane D. Jacob et al. 10.5194/acp-22-9617-2022
44. Application of Google Earth Engine to Monitor Greenhouse Gases: A Review D. Wilson et al. 10.3390/data10010008
45. Automated detection and monitoring of methane super-emitters using satellite data B. Schuit et al. 10.5194/acp-23-9071-2023
46. Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion J. McNorton et al. 10.5194/acp-22-5961-2022
47. Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer B. Rouet-Leduc & C. Hulbert 10.1038/s41467-024-47754-y
48. Detecting Methane Emissions from Space Over India: Analysis Using EMIT and Sentinel-5P TROPOMI Datasets A. Siddiqui et al. 10.1007/s12524-024-01925-y
49. Widespread Frequent Methane Emissions From the Oil and Gas Industry in the Permian Basin J. Veefkind et al. 10.1029/2022JD037479
50. Assessing the Relative Importance of Satellite-Detected Methane Superemitters in Quantifying Total Emissions for Oil and Gas Production Areas in Algeria S. Naus et al. 10.1021/acs.est.3c04746
51. Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images P. Joyce et al. 10.5194/amt-16-2627-2023
52. Linear integrated mass enhancement: A method for estimating hotspot emission rates from space-based plume observations J. Hakkarainen et al. 10.1016/j.rse.2025.114623
53. Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al. 10.1038/s41598-023-41914-8
54. Towards Supporting Satellite Design Through the Top-Down Approach: A General Model for Assessing the Ability of Future Satellite Missions to Quantify Point Source Emissions L. Yao et al. 10.3390/rs16234503
55. Methane emissions from the Nord Stream subsea pipeline leaks S. Harris et al. 10.1038/s41586-024-08396-8
56. Single-blind test of nine methane-sensing satellite systems from three continents E. Sherwin et al. 10.5194/amt-17-765-2024
57. Advancements in satellite-based methane point source monitoring: A systematic review F. Mohammadimanesh et al. 10.1016/j.isprsjprs.2025.03.020
58. Разработка статистических моделей оценки концентрации метана в приземном слое атмосферы по материалам космической съемки в зимний период Н. Попов & В. Малинников 10.33764/2411-1759-2025-30-3-77-85
59. Permafrost carbon emissions in a changing Arctic K. Miner et al. 10.1038/s43017-021-00230-3
60. 煤炭行业甲烷排放卫星遥感研究进展与展望 秦. Qin Kai et al. 10.3788/AOS231293
61. U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers J. Bruno et al. 10.5194/amt-17-2625-2024
62. Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action Z. Chen et al. 10.5194/acp-23-5945-2023
63. An explainable MHSA enabled deep architecture with dual-scale convolutions for methane source classification using remote sensing K. Bansal & A. Tripathi 10.1016/j.envsoft.2024.106178
64. Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins L. Shen et al. 10.5194/acp-22-11203-2022
65. kMetha-Mamba: K-means clustering mamba for methane plumes segmentation Y. Liu et al. 10.1016/j.jag.2025.104664
66. Analysis of a tiered top-down approach using satellite and aircraft platforms to monitor oil and gas facilities in the Permian basin Á. Esparza et al. 10.1016/j.rser.2023.113265
67. Global Methane Retrieval, Monitoring, and Quantification in Hotspot Regions Based on AHSI/ZY-1 Satellite T. Lu et al. 10.3390/atmos16050510
68. Monitoring oil and gas field CH4 leaks by Sentinel-5P and Sentinel-2 B. He et al. 10.1016/j.fuel.2024.133889
69. Using satellites to uncover large methane emissions from landfills J. Maasakkers et al. 10.1126/sciadv.abn9683
70. Discovery of Large Methane Emissions Using a Complementary Method Based on Multispectral and Hyperspectral Data X. Cai et al. 10.3390/atmos16050532
71. Mapping methane plumes at very high spatial resolution with the WorldView-3 satellite E. Sánchez-García et al. 10.5194/amt-15-1657-2022
72. A data-efficient deep transfer learning framework for methane super-emitter detection in oil and gas fields using the Sentinel-2 satellite S. Zhao et al. 10.5194/acp-25-4035-2025
73. Increased methane emissions from oil and gas following the Soviet Union’s collapse T. He et al. 10.1073/pnas.2314600121
74. Relating Multi-Scale Plume Detection and Area Estimates of Methane Emissions: A Theoretical and Empirical Analysis S. Pandey et al. 10.1021/acs.est.4c07415
75. Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak M. Dogniaux et al. 10.5194/amt-17-2777-2024
76. Semantic segmentation of methane plumes with hyperspectral machine learning models V. Růžička et al. 10.1038/s41598-023-44918-6
77. Space-based observations of tropospheric ethane map emissions from fossil fuel extraction J. Brewer et al. 10.1038/s41467-024-52247-z
78. Frequency and Spatial Domain Injection Network for Methane Plumes Semantic Segmentation Y. Liu et al. 10.1109/TGRS.2024.3523022
79. Joint Use of in-Scene Background Radiance Estimation and Optimal Estimation Methods for Quantifying Methane Emissions Using PRISMA Hyperspectral Satellite Data: Application to the Korpezhe Industrial Site N. Nesme et al. 10.3390/rs13244992
80. Quantifying NOxpoint sources with Landsat and Sentinel-2 satellite observations of NO2plumes D. Varon et al. 10.1073/pnas.2317077121
81. Current Status of Satellite Remote Sensing-Based Methane Emission Monitoring Technologies M. Kim et al. 10.9719/EEG.2024.57.5.513
82. Retrieval of Atmospheric XCH4 via XGBoost Method Based on TROPOMI Satellite Data W. Zhang et al. 10.3390/atmos16030279