Articles | Volume 10, issue 1
https://doi.org/10.5194/essd-10-653-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-653-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
28 Mar 2018
| 28 Mar 2018
Vista-LA: Mapping methane-emitting infrastructure in the Los Angeles megacity
Valerie Carranza
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
now at: University of
California, Riverside, Riverside, CA 92521, USA
Talha Rafiq
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Joint Institute for Regional Earth System
Science and Engineering, University of California, Los
Angeles, CA 90024, USA
now at: University of
California, Riverside, Riverside, CA 92521, USA
Isis Frausto-Vicencio
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
now at: University of
California, Riverside, Riverside, CA 92521, USA
Francesca M. Hopkins
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
now at: University of
California, Riverside, Riverside, CA 92521, USA
Kristal R. Verhulst
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Joint Institute for Regional Earth System
Science and Engineering, University of California, Los
Angeles, CA 90024, USA
Preeti Rao
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
now at: University
of Michigan, Ann Arbor, MI 48109, USA
Riley M. Duren
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Charles E. Miller
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
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Cited
17 citations as recorded by crossref.
- Wind Dispersal of Natural and Biomimetic Maple Samaras G. Nave et al. https://doi.org/10.3390/biomimetics6020023
- MAM-YOLOv9: A Multiattention Mechanism Network for Methane Emission Facility Detection in High-Resolution Satellite Remote Sensing Images Y. Xing et al. https://doi.org/10.1109/TGRS.2025.3545034
- The Facility Level and Area Methane Emissions inventory for the Greater Toronto Area (FLAME-GTA) N. Mostafavi Pak et al. https://doi.org/10.1016/j.atmosenv.2021.118319
- GHG action zone identification at the local level: Emissions inventory and spatial distribution as methodologies for policies and plans M. Marchi et al. https://doi.org/10.1016/j.jclepro.2022.135783
- Biochar mitigates methane emissions from organic mulching in urban soils: Evidence from a long-term mesocosm experiment I. Kayes et al. https://doi.org/10.1016/j.jenvman.2025.124525
- Synthesis of Methane Observations Across Scales: Strategies for Deploying a Multitiered Observing Network D. Cusworth et al. https://doi.org/10.1029/2020GL087869
- The Hestia fossil fuel CO2 emissions data product for the Los Angeles megacity (Hestia-LA) K. Gurney et al. https://doi.org/10.5194/essd-11-1309-2019
- Artificial Intelligence Approach for Estimating Dairy Methane Emissions S. Jeong et al. https://doi.org/10.1021/acs.est.1c08802
- Seasonal spatial variations of urban methane concentrations in a medium-sized city determined by easily measure variables V. Fusé et al. https://doi.org/10.1016/j.uclim.2023.101798
- Wind Profiling in the Lower Atmosphere from Wind-Induced Perturbations to Multirotor UAS J. González-Rocha et al. https://doi.org/10.3390/s20051341
- Spatio‐temporally Resolved Methane Fluxes From the Los Angeles Megacity V. Yadav et al. https://doi.org/10.1029/2018JD030062
- A declining trend of methane emissions in the Los Angeles basin from 2015 to 2020 V. Yadav et al. https://doi.org/10.1088/1748-9326/acb6a9
- Southern California megacity CO2, CH4, and CO flux estimates using ground- and space-based remote sensing and a Lagrangian model J. Hedelius et al. https://doi.org/10.5194/acp-18-16271-2018
- Identification and source attribution of halocarbon emitters with longwave-infrared spectral imaging D. Tratt et al. https://doi.org/10.1016/j.rse.2021.112398
- Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution M. Omara et al. https://doi.org/10.5194/essd-15-3761-2023
- Attribution of methane point source emissions using airborne imaging spectroscopy and the Vista-California methane infrastructure dataset T. Rafiq et al. https://doi.org/10.1088/1748-9326/ab9af8
- The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps G. Hurtt et al. https://doi.org/10.1088/1748-9326/ac7407
17 citations as recorded by crossref.
- Wind Dispersal of Natural and Biomimetic Maple Samaras G. Nave et al. https://doi.org/10.3390/biomimetics6020023
- MAM-YOLOv9: A Multiattention Mechanism Network for Methane Emission Facility Detection in High-Resolution Satellite Remote Sensing Images Y. Xing et al. https://doi.org/10.1109/TGRS.2025.3545034
- The Facility Level and Area Methane Emissions inventory for the Greater Toronto Area (FLAME-GTA) N. Mostafavi Pak et al. https://doi.org/10.1016/j.atmosenv.2021.118319
- GHG action zone identification at the local level: Emissions inventory and spatial distribution as methodologies for policies and plans M. Marchi et al. https://doi.org/10.1016/j.jclepro.2022.135783
- Biochar mitigates methane emissions from organic mulching in urban soils: Evidence from a long-term mesocosm experiment I. Kayes et al. https://doi.org/10.1016/j.jenvman.2025.124525
- Synthesis of Methane Observations Across Scales: Strategies for Deploying a Multitiered Observing Network D. Cusworth et al. https://doi.org/10.1029/2020GL087869
- The Hestia fossil fuel CO2 emissions data product for the Los Angeles megacity (Hestia-LA) K. Gurney et al. https://doi.org/10.5194/essd-11-1309-2019
- Artificial Intelligence Approach for Estimating Dairy Methane Emissions S. Jeong et al. https://doi.org/10.1021/acs.est.1c08802
- Seasonal spatial variations of urban methane concentrations in a medium-sized city determined by easily measure variables V. Fusé et al. https://doi.org/10.1016/j.uclim.2023.101798
- Wind Profiling in the Lower Atmosphere from Wind-Induced Perturbations to Multirotor UAS J. González-Rocha et al. https://doi.org/10.3390/s20051341
- Spatio‐temporally Resolved Methane Fluxes From the Los Angeles Megacity V. Yadav et al. https://doi.org/10.1029/2018JD030062
- A declining trend of methane emissions in the Los Angeles basin from 2015 to 2020 V. Yadav et al. https://doi.org/10.1088/1748-9326/acb6a9
- Southern California megacity CO2, CH4, and CO flux estimates using ground- and space-based remote sensing and a Lagrangian model J. Hedelius et al. https://doi.org/10.5194/acp-18-16271-2018
- Identification and source attribution of halocarbon emitters with longwave-infrared spectral imaging D. Tratt et al. https://doi.org/10.1016/j.rse.2021.112398
- Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution M. Omara et al. https://doi.org/10.5194/essd-15-3761-2023
- Attribution of methane point source emissions using airborne imaging spectroscopy and the Vista-California methane infrastructure dataset T. Rafiq et al. https://doi.org/10.1088/1748-9326/ab9af8
- The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps G. Hurtt et al. https://doi.org/10.1088/1748-9326/ac7407
Saved (final revised paper)
Latest update: 28 May 2026
Short summary
We present a GIS-based approach to mapping methane emissions in areas with dense, complex source mixtures. The Vista-LA database classifies >33 000 potential methane-emitting features concentrated on <1% of the land area in California's South Coast Air Basin. The database is used for planning and analysis of atmospheric measurements, including airborne remote sensing campaigns and on-road mobile surveys focused on methane "hot-spot" detection, and development of a regional emissions inventory.
We present a GIS-based approach to mapping methane emissions in areas with dense, complex source...
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