Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS

• Other Authors: Lee, Chang-Wook (Editor), Han, Hyangsun (Editor), Lee, Hoonyol (Editor), Park, Yu-Chul (Editor)
• Format: Electronic Book Chapter
• Language: English
• 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: DOAB: download the publication; DOAB: description of the publication

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