Semantic segmentation of methane plumes with hyperspectral machine learning models

Semantic segmentation of methane plumes with hyperspectral machine learning models

Methane is the second most important greenhouse gas contributor to climate change; at the same time its reduction has been denoted as one of the fastest pathways to preventing temperature growth due to its short atmospheric lifetime. In particular, the mitigation of active point-sources associated w...

Descripció completa

Dades bibliogràfiques
Autors principals:	Růžička, V, Mateo-Garcia, G, Gómez-Chova, L, Vaughan, A, Guanter, L, Markham, A
Format:	Journal article
Idioma:	English
Publicat:	Springer Nature 2023

Ítems similars

Semantic segmentation of methane plumes with hyperspectral machine learning models
per: Vít Růžička, et al.
Publicat: (2023-11-01)

CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
per: A. Vaughan, et al.
Publicat: (2024-05-01)

Exploiting the entire near-infrared spectral range to improve the detection of methane plumes with high-resolution imaging spectrometers
per: J. Roger, et al.
Publicat: (2024-02-01)

Mapping methane plumes at very high spatial resolution with the WorldView-3 satellite
per: E. Sánchez-García, et al.
Publicat: (2022-03-01)

Semantic Segmentation in Satellite Hyperspectral Imagery by Deep Learning
per: Jon Alvarez Justo, et al.
Publicat: (2025-01-01)

Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data
per: Gómez-Chova, L, et al.
Publicat: (2006)

The Improvement of Methane Plume Detection with High-Resolution Satellite-Based Imaging Spectrometers
per: Javier Roger, et al.
Publicat: (2024-01-01)

CHRIS/PROBA toolbox for hyperspectral and multiangular data exploitations
per: Alonso, L, et al.
Publicat: (2009)

Correction of systematic spatial noise in push-broom hyperspectral sensors: application to CHRIS/PROBA images.
per: Gómez-Chova, L, et al.
Publicat: (2008)

Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data - art. no. 63650Z
per: Gomez-Chova, L, et al.
Publicat: (2006)

CHRIS/PROBA TOOLBOX FOR HYPERSPECTRAL AND MULTIANGULAR DATA EXPLOITATIONS
per: Alonso, L, et al.
Publicat: (2009)

Cloud detection for CHRIS/Proba hyperspectral images
per: Gómez-Chova, L, et al.
Publicat: (2005)

COMPARISON OF ESTIMATION METHODS TO QUANTIFY METHANE PLUME CONCENTRATION AT HIGH SPATIAL RESOLUTION FROM HYPERSPECTRAL IMAGES
per: N. Nesme, et al.
Publicat: (2021-06-01)

New Cloud Detection Algorithm for Multispectral and Hyperspectral Images: Application to ENVISAT/MERIS and PROBA/CHRIS Sensors
per: Gomez-Chova, L, et al.
Publicat: (2006)

Coupled retrieval of aerosol optical thickness, columnar water vapor and surface reflectance maps from ENVISAT/MERIS data over land
per: Guanter, L, et al.
Publicat: (2008)

Analysis of the spatial and temporal variability of aerosol optical thickness and columnar water vapor from MERIS data
per: Guanter, L, et al.
Publicat: (2007)

Learning semantic segmentation of large-scale point clouds with random sampling
per: Hu, Q, et al.
Publicat: (2021)

Fully‐connected semantic segmentation of hyperspectral and LiDAR data
per: Hakan Aytaylan, et al.
Publicat: (2019-04-01)

Separating and quantifying facility-level methane emissions with overlapping plumes for spaceborne methane monitoring
per: Y. Pang, et al.
Publicat: (2025-01-01)

Class-aware feature attention-based semantic segmentation on hyperspectral images.
per: Prabu Sevugan, et al.
Publicat: (2025-01-01)

Semantic segmentation of hyperspectral images using convolutional neural networks and the attention mechanism
per: D.N. Gribanov, et al.
Publicat: (2024-12-01)

Global flood extent segmentation in optical satellite images
per: Enrique Portalés-Julià, et al.
Publicat: (2023-11-01)

Methane Plume Emissions Associated With Puget Sound Faults in the Cascadia Forearc
per: H. Paul Johnson, et al.
Publicat: (2022-01-01)

Methane Seeps and Independent Methane Plumes in the South China Sea Offshore Taiwan
per: Susan Mau, et al.
Publicat: (2020-07-01)

Shallow-Guided Transformer for Semantic Segmentation of Hyperspectral Remote Sensing Imagery
per: Yuhan Chen, et al.
Publicat: (2023-06-01)

CEU-Net: ensemble semantic segmentation of hyperspectral images using clustering
per: Nicholas Soucy, et al.
Publicat: (2023-04-01)

FUSION OF LIDAR AND HYPERSPECTRAL DATA FOR SEMANTIC SEGMENTATION OF FOREST TREE SPECIES
per: E. Tusa, et al.
Publicat: (2020-08-01)

Semantic Segmentation of Sorghum Using Hyperspectral Data Identifies Genetic Associations
per: Chenyong Miao, et al.
Publicat: (2020-01-01)

Distribution of Methane Plumes on Cascadia Margin and Implications for the Landward Limit of Methane Hydrate Stability
per: Susan G. Merle, et al.
Publicat: (2021-03-01)

Onboard Cloud Detection and Atmospheric Correction With Efficient Deep Learning Models
per: Cesar Aybar, et al.
Publicat: (2024-01-01)

RandLA-Net: efficient semantic segmentation of large-scale point clouds
per: Hu, Q, et al.
Publicat: (2020)

Convolutional Neural Network Algorithms for Semantic Segmentation of Volcanic Ash Plumes Using Visible Camera Imagery
per: José Francisco Guerrero Tello, et al.
Publicat: (2022-09-01)

Semantic Segmentation of Hyperspectral Remote Sensing Images Based on PSE-UNet Model
per: Jiaju Li, et al.
Publicat: (2022-12-01)

Estimating and understanding crop yields with explainable deep learning in the Indian Wheat Belt
per: Aleksandra Wolanin, et al.
Publicat: (2020-01-01)

Characterizing Clutter in the Context of Detecting Weak Gaseous Plumes in Hyperspectral Imagery
per: Brian McVey, et al.
Publicat: (2006-11-01)

AEROSOL PLUMES CHARACTERIZATION BY HYPERSPECTRAL IMAGES COUPLED WITH SENTINEL-2 PRODUCTS
per: G. Calassou, et al.
Publicat: (2020-08-01)

Insights Into Mantle Plume Geochemistry From Machine Learning
per: William M. White, et al.
Publicat: (2025-01-01)

A Systematic Literature Review on Machine Learning and Deep Learning Methods for Semantic Segmentation
per: Ali Sohail, et al.
Publicat: (2022-01-01)

Deformable Transformer and Spectral U-Net for Large-Scale Hyperspectral Image Semantic Segmentation
per: Tianjian Zhang, et al.
Publicat: (2024-01-01)

A Novel Technique for Semantic Segmentation of Hyperspectral Images Using Multi-View Features
per: Reaya Grewal, et al.
Publicat: (2024-06-01)