Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer
Curbing methane emissions is among the most effective actions that can be taken to slow
down global warming. However, monitoring emissions remains challenging, as detection …
down global warming. However, monitoring emissions remains challenging, as detection …
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 …
same time its reduction has been denoted as one of the fastest pathways to preventing …
Geostationary satellite observations of extreme and transient methane emissions from oil and gas infrastructure
We demonstrate geostationary satellite monitoring of large transient methane point sources
with the US Geostationary Operational Environmental Satellites (GOES). GOES provides …
with the US Geostationary Operational Environmental Satellites (GOES). GOES provides …
[HTML][HTML] PRISMethaNet: A novel deep learning model for landfill methane detection using PRISMA satellite data
Methane (CH4) is one of the most significant greenhouse gases responsible for about one-
third of climate warming since preindustrial times, originating from various sources. Landfills …
third of climate warming since preindustrial times, originating from various sources. Landfills …
Machine learning for methane detection and quantification from space-a survey
Methane ($ CH_4 $) is a potent anthropogenic greenhouse gas, contributing 86 times more
to global warming than Carbon Dioxide ($ CO_2 $) over 20 years, and it also acts as an air …
to global warming than Carbon Dioxide ($ CO_2 $) over 20 years, and it also acts as an air …
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
We present a deep learning model, CH4Net, for automated monitoring of methane super-
emitters from Sentinel-2 data. When trained on images of 21 methane super-emitters from …
emitters from Sentinel-2 data. When trained on images of 21 methane super-emitters from …
Methane plumes detection on prisma l1 images with the adjusted spectral matched filter and wind data
Reducing methane emissions is essential to tackle climate change. Here, we address the
problem of detecting automatically point source methane leaks using high resolution …
problem of detecting automatically point source methane leaks using high resolution …
STARCOP: 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 …
same time its reduction has been denoted as one of the fastest pathways to preventing …
Methane Emissions Monitoring Using Geostationary Satellites
Satellite imaging has proven to be crucial to monitor methane emissions and help reduce
them. In this paper, we propose an automatic practical methodology to use time series from …
them. In this paper, we propose an automatic practical methodology to use time series from …
Model Adjusted Matched Filter for Methane Plume Detection on Prisma Hyperspectral Images
Reducing methane emissions is essential to tackle climate change. Here, we address the
problem of detecting automatically point source methane leaks using high resolution …
problem of detecting automatically point source methane leaks using high resolution …