[HTML][HTML] Deep learning in remote sensing applications: A meta-analysis and review
Deep learning (DL) algorithms have seen a massive rise in popularity for remote-sensing
image analysis over the past few years. In this study, the major DL concepts pertinent to …
image analysis over the past few years. In this study, the major DL concepts pertinent to …
Deep learning in environmental remote sensing: Achievements and challenges
Various forms of machine learning (ML) methods have historically played a valuable role in
environmental remote sensing research. With an increasing amount of “big data” from earth …
environmental remote sensing research. With an increasing amount of “big data” from earth …
Reconstructing 1-km-resolution high-quality PM2. 5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications
Exposure to fine particulate matter (PM 2.5) can significantly harm human health and
increase the risk of death. Satellite remote sensing allows for generating spatially …
increase the risk of death. Satellite remote sensing allows for generating spatially …
Deep learning for geophysics: Current and future trends
Recently deep learning (DL), as a new data‐driven technique compared to conventional
approaches, has attracted increasing attention in geophysical community, resulting in many …
approaches, has attracted increasing attention in geophysical community, resulting in many …
Full-coverage map** and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China
Ozone (O 3) is an important trace and greenhouse gas in the atmosphere, posing a threat to
the ecological environment and human health at the ground level. Large-scale and long …
the ecological environment and human health at the ground level. Large-scale and long …
[HTML][HTML] Ground-level gaseous pollutants (NO, SO, and CO) in China: daily seamless map** and spatiotemporal variations
Gaseous pollutants at the ground level seriously threaten the urban air quality environment
and public health. There are few estimates of gaseous pollutants that are spatially and …
and public health. There are few estimates of gaseous pollutants that are spatially and …
Improved 1 km resolution PM2.5 estimates across China using enhanced space–time extremely randomized trees
Fine particulate matter with aerodynamic diameters≤ 2.5 µ m (PM 2.5) has adverse effects
on human health and the atmospheric environment. The estimation of surface PM 2.5 …
on human health and the atmospheric environment. The estimation of surface PM 2.5 …
PM2.5 Prediction Based on Random Forest, XGBoost, and Deep Learning Using Multisource Remote Sensing Data
In recent years, air pollution has become an important public health concern. The high
concentration of fine particulate matter with diameter less than 2.5 µm (PM2. 5) is known to …
concentration of fine particulate matter with diameter less than 2.5 µm (PM2. 5) is known to …
[HTML][HTML] The ChinaHighPM10 dataset: generation, validation, and spatiotemporal variations from 2015 to 2019 across China
Respirable particles with aerodynamic diameters≤ 10 µm (PM 10) have important impacts
on the atmospheric environment and human health. Available PM 10 datasets have coarse …
on the atmospheric environment and human health. Available PM 10 datasets have coarse …
Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data
Fine particulate matter (PM2. 5) chemical composition has strong and diverse impacts on the
planetary environment, climate, and health. These effects are still not well understood due to …
planetary environment, climate, and health. These effects are still not well understood due to …