[HTML][HTML] Towards the next generation of Geospatial Artificial Intelligence
Abstract Geospatial Artificial Intelligence (GeoAI), as the integration of geospatial studies
and AI, has become one of the fastest-developing research directions in spatial data science …
and AI, has become one of the fastest-developing research directions in spatial data science …
A novel approach to estimate land surface temperature from landsat top-of-atmosphere reflective and emissive data using transfer-learning neural network
Abstract Land Surface Temperature (LST) is a crucial parameter in studies of urban heat
islands, climate change, evapotranspiration, hydrological cycles, and vegetation monitoring …
islands, climate change, evapotranspiration, hydrological cycles, and vegetation monitoring …
Knowledge-guided Machine Learning: Current Trends and Future Prospects
This paper presents an overview of scientific modeling and discusses the complementary
strengths and weaknesses of ML methods for scientific modeling in comparison to process …
strengths and weaknesses of ML methods for scientific modeling in comparison to process …
FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning
Recent studies have highlighted significant fairness issues in Graph Transformer (GT)
models, particularly against subgroups defined by sensitive features. Additionally, GTs are …
models, particularly against subgroups defined by sensitive features. Additionally, GTs are …
Estimating Human Mobility Responses to Social Disruptions Through Spatio-Temporal Deep Generative Learning Methods
H Bao - 2024 - search.proquest.com
Estimating human mobility is an important task in diverse societal domains, including public
health, public safety, transportation, agriculture, environmental science, etc. This thesis …
health, public safety, transportation, agriculture, environmental science, etc. This thesis …
Advances in methodology and generation of all-weather land surface temperature products from polar-orbiting and geostationary satellites: A comprehensive review
Land surface temperature (LST) is crucial for understanding surface energy budgets,
hydrological cycling, and land–atmosphere interactions. However, cloud cover leads to …
hydrological cycling, and land–atmosphere interactions. However, cloud cover leads to …
[PDF][PDF] A comprehensive review
Land surface temperature (LST) is crucial for understanding surface energy budgets,
hydrological cycling, and land–atmosphere interactions. However, cloud cover leads to …
hydrological cycling, and land–atmosphere interactions. However, cloud cover leads to …