GeoAI Data and Processing in Applied Sciences

Dear Colleagues,

Geospatial artificial intelligence (GeoAI) has become more essential 1) in extracting valuable information from spatial big data and 2) in combining the biggest innovations of technologies used in geospatial sciences and engineering, remote sensing, geoscience information systems, and artificial intelligence (e.g., machine learning, deep learning). The GeoAI technology provides a very important advantage by enabling us to incorporate large amounts of spatiotemporal big spatial data with computational efficiency and flexibility in algorithm. The objectives of this Special Issue are to create a multidisciplinary forum of discussion on recent advances in the research fields of GeoAI for applied sciences and to find new techniques and applications in geospatial sciences and engineering, applied geology, applied biology, applied ecology, applied hydrology, applied environmentology, etc. Potential topics include, but are not limited to:

• GeoAI data product
• Validation of GeoAI data product
• GeoAI data processing
• Model development for GeoAI data
• Modeling and mapping using GeoAI data
• Change detection, target detection and target recognition using GeoAI data
• Applications and innovative use of GeoAI data for geospatial sciences and engineering
• Applications and innovative use of GeoAI data for remote sensing
• Applications and innovative use of GeoAI data for geoscience information system
• Applications and innovative use of GeoAI data for applied geology
• Applications and innovative use of GeoAI data for applied biology
• Applications and innovative use of GeoAI data for applied ecology
• Applications and innovative use of GeoAI data for applied hydrology
• Applications and innovative use of GeoAI data for applied environmentology

Prof. Dr. Hyung-Sup Jung
Prof. Dr. Saro Lee
Guest Editors

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