A review of earth artificial intelligence
In recent years, Earth system sciences are urgently calling for innovation on improving
accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in …
accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in …
[HTML][HTML] An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing
Ocean color measured from satellites provides daily global, synoptic views of spectral water-
leaving reflectances that can be used to generate estimates of marine inherent optical …
leaving reflectances that can be used to generate estimates of marine inherent optical …
Evaluation of river water quality index using remote sensing and artificial intelligence models
To restrict the entry of polluting components into water bodies, particularly rivers, it is critical
to undertake timely monitoring and make rapid choices. Traditional techniques of assessing …
to undertake timely monitoring and make rapid choices. Traditional techniques of assessing …
Improving accuracy estimation of Forest Aboveground Biomass based on incorporation of ALOS-2 PALSAR-2 and Sentinel-2A imagery and machine learning: A case …
The main objective of this research is to investigate the potential combination of Sentinel-2A
and ALOS-2 PALSAR-2 (Advanced Land Observing Satellite-2 Phased Array type L-band …
and ALOS-2 PALSAR-2 (Advanced Land Observing Satellite-2 Phased Array type L-band …
A global approach for chlorophyll-a retrieval across optically complex inland waters based on optical water types
Numerous algorithms have been developed to retrieve chlorophyll-a (Chla) concentrations
(mg m− 3) from Earth observation (EO) data collected over optically complex waters …
(mg m− 3) from Earth observation (EO) data collected over optically complex waters …
Drought assessment and monitoring through blending of multi-sensor indices using machine learning approaches for different climate regions
Drought triggered by a deficit of precipitation, is influenced by various environmental factors
such as temperature and evapotranspiration, and causes water shortage and crop failure …
such as temperature and evapotranspiration, and causes water shortage and crop failure …
Comparison of machine learning algorithms for retrieval of water quality indicators in case-II waters: A case study of Hong Kong
Anthropogenic activities in coastal regions are endangering marine ecosystems. Coastal
waters classified as case-II waters are especially complex due to the presence of different …
waters classified as case-II waters are especially complex due to the presence of different …
Application of machine learning in ocean data
R Lou, Z Lv, S Dang, T Su, X Li - Multimedia Systems, 2023 - Springer
In recent years, machine learning has become a hot research method in various fields and
has been applied to every aspect of our life, providing an intelligent solution to problems that …
has been applied to every aspect of our life, providing an intelligent solution to problems that …
Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations
Vegetation indices are important remotely sensed metrics for ecosystem monitoring and
land surface process assessment, among which Normalized Difference Vegetation Index …
land surface process assessment, among which Normalized Difference Vegetation Index …
Meteorological drought forecasting for ungauged areas based on machine learning: Using long-range climate forecast and remote sensing data
A high-resolution drought forecast model for ungauged areas was developed in this study.
The Standardized Precipitation Index (SPI) and Standardized Precipitation …
The Standardized Precipitation Index (SPI) and Standardized Precipitation …