Cargando…
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...
Autores principales: | Růžička, Vít, Mateo-Garcia, Gonzalo, Gómez-Chova, Luis, Vaughan, Anna, Guanter, Luis, Markham, Andrew |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656523/ https://www.ncbi.nlm.nih.gov/pubmed/37978332 http://dx.doi.org/10.1038/s41598-023-44918-6 |
Ejemplares similares
-
Global flood extent segmentation in optical satellite images
por: Portalés-Julià, Enrique, et al.
Publicado: (2023) -
Characterizing Clutter in the Context of Detecting Weak Gaseous Plumes in Hyperspectral Imagery
por: Burr, Tom, et al.
Publicado: (2006) -
Semantic Segmentation of Sorghum Using Hyperspectral Data Identifies Genetic Associations
por: Miao, Chenyong, et al.
Publicado: (2020) -
Predicting the Detectability of Thin Gaseous Plumes in Hyperspectral Images Using Basis Vectors
por: Anderson, Kevin K., et al.
Publicado: (2010) -
Semantic Segmentation of Hyperspectral Remote Sensing Images Based on PSE-UNet Model
por: Li, Jiaju, et al.
Publicado: (2022)