Neural Network-Based Urban Change Monitoring with Deep-Temporal Multispectral and SAR Remote Sensing Data
Remote-sensing-driven urban change detection has been studied in many ways for decades for a wide field of applications, such as understanding socio-economic impacts, identifying new settlements, or analyzing trends of urban sprawl. Such kinds of analyses are usually carried out manually by selectin...
Main Authors: | Georg Zitzlsberger, Michal Podhorányi, Václav Svatoň, Milan Lazecký, Jan Martinovič |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/13/15/3000 |
Similar Items
-
rsdtlib: Remote sensing with deep-temporal data library
by: Georg Zitzlsberger, et al.
Published: (2023-05-01) -
Monitoring of Urban Changes With Multimodal Sentinel 1 and 2 Data in Mariupol, Ukraine, in 2022/23
by: Georg Zitzlsberger, et al.
Published: (2024-01-01) -
Multi-temporal InSAR for Urban Deformation Monitoring: Progress and Challenges
by: WU Songbo, et al.
Published: (2020-04-01) -
Signal theory methods in multispectral remote sensing /
by: 387920 Landgrebe, David A.
Published: (2003) -
Design of CGAN Models for Multispectral Reconstruction in Remote Sensing
by: Brais Rodríguez-Suárez, et al.
Published: (2022-02-01)