[HTML][HTML] Federated learning meets remote sensing
Remote sensing (RS) imagery provides invaluable insights into characterizing the Earth's
land surface within the scope of Earth observation (EO). Technological advances in capture …
land surface within the scope of Earth observation (EO). Technological advances in capture …
Mortality attributable to long-term exposure to ambient fine particulate matter: insights from the epidemiologic evidence for understudied locations
Epidemiologic cohort studies have consistently demonstrated that long-term exposure to
ambient fine particles (PM2. 5) is associated with mortality. Nevertheless, extrapolating …
ambient fine particles (PM2. 5) is associated with mortality. Nevertheless, extrapolating …
EAACI guidelines on environmental science in allergic diseases and asthma–leveraging artificial intelligence and machine learning to develop a causality model in …
Allergic diseases and asthma are intrinsically linked to the environment we live in and to
patterns of exposure. The integrated approach to understanding the effects of exposures on …
patterns of exposure. The integrated approach to understanding the effects of exposures on …
Improving remote sensing estimation of Secchi disk depth for global lakes and reservoirs using machine learning methods
Y Zhang, K Shi, X Sun, Y Zhang, N Li… - GIScience & Remote …, 2022 - Taylor & Francis
Secchi disk depth (SDD) is a simple but particularly important indicator for characterizing the
overall water quality status and assessing the long-term dynamics of water quality for …
overall water quality status and assessing the long-term dynamics of water quality for …
Spatial resolved surface ozone with Urban and rural differentiation during 1990–2019: a space–time bayesian neural network downscaler
Long-term exposure to ambient ozone (O3) can lead to a series of chronic diseases and
associated premature deaths, and thus population-level environmental health studies …
associated premature deaths, and thus population-level environmental health studies …
[HTML][HTML] Machine learning algorithms for high-resolution prediction of spatiotemporal distribution of air pollution from meteorological and soil parameters
This study uses machine learning (ML) models for a high-resolution prediction (0.1°× 0.1°) of
air fine particular matter (PM 2.5) concentration, the most harmful to human health, from …
air fine particular matter (PM 2.5) concentration, the most harmful to human health, from …
Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak
Atmospheric pollutant data retrieved through satellite sensors are continually used to assess
changes in air quality in the lower atmosphere. During the COVID-19 pandemic, several …
changes in air quality in the lower atmosphere. During the COVID-19 pandemic, several …
Long-term effects of PM2. 5 components on incident dementia in the northeastern United States
Growing evidence has linked long-term fine particulate matter (PM 2.5) exposure to
neurological disorders. Less is known about the individual effects of PM 2.5 components. A …
neurological disorders. Less is known about the individual effects of PM 2.5 components. A …
Surface water sodium (Na+) concentration prediction using hybrid weighted exponential regression model with gradient-based optimization
Undeniably, there is a link between water resources and people's lives and, consequently,
economic development, which makes them vital in health and the environment. Proper water …
economic development, which makes them vital in health and the environment. Proper water …
[HTML][HTML] Visibility-derived aerosol optical depth over global land from 1959 to 2021
H Hao, K Wang, C Zhao, G Wu… - Earth System Science …, 2024 - essd.copernicus.org
Long-term and high spatial resolution aerosol optical depth (AOD) data are essential for
climate change detection and attribution. Global ground-based AOD observations are …
climate change detection and attribution. Global ground-based AOD observations are …