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...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser:	Růžička, V, Mateo-Garcia, G, Gómez-Chova, L, Vaughan, A, Guanter, L, Markham, A
Format:	Journal article
Sprache:	English
Veröffentlicht:	Springer Nature 2023

Ähnliche Einträge

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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