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Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS
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This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.
This book is included in DOAB.
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Keywords
- artificial intelligence
- boosted tree
- change detection
- deep learning
- DInSAR
- DPM method
- earth observation
- ensemble models
- Environmental science, engineering & technology
- GIS
- groundwater potential
- Jakarta
- land subsidence
- land subsidence susceptibility mapping
- Machine learning
- Monte Carlo simulation
- Monterrey Metropolitan Area
- Mt. Umyeon landslides
- neural networks
- physical slope model
- probabilistic method
- prototype selection
- Remote sensing
- river pollution
- seismic literacy
- seismic vulnerability map
- Sentinel-1
- Seoul
- space data science
- specific capacity
- StaMPS processing
- supervised classification
- Sustainable development
- synthetic aperture radar
- Technology, engineering, agriculture
- time-series
- time-series InSAR
- transfer learning
- urban open spaces
- urban vegetation
- WSN
Links
DOI: 10.3390/books978-3-0365-1603-5Editions