Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS

Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS

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 a...

Full description

Saved in:
Bibliographic Details
Other Authors: Lee, Chang-Wook (Editor), Han, Hyangsun (Editor), Lee, Hoonyol (Editor), Park, Yu-Chul (Editor)
Format: Book Chapter
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Environmental science, engineering & technology
groundwater potential
specific capacity
machine learning
boosted tree
ensemble models
prototype selection
river pollution
supervised classification
WSN
probabilistic method
Monte Carlo simulation
physical slope model
Mt. Umyeon landslides
Seoul
synthetic aperture radar
land subsidence
GIS
time-series
Jakarta
land subsidence susceptibility mapping
time-series InSAR
StaMPS processing
seismic vulnerability map
DPM method
Sentinel-1
seismic literacy
neural networks
urban vegetation
urban open spaces
Monterrey Metropolitan Area
sustainable development
deep learning
transfer learning
artificial intelligence
remote sensing
earth observation
DInSAR
change detection
space data science
Online Access:Get Fullteks
DOAB: description of the publication
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Physical Description:1 electronic resource (165 p.)
ISBN:books978-3-0365-1603-5
9783036516042
9783036516035
Access:Open Access

Similar Items