Automatic Interferogram Selection for SBAS-InSAR Based on Deep Convolutional Neural Networks
The small baseline subset of spaceborne interferometric synthetic aperture radar (SBAS-InSAR) technology has become a classical method for monitoring slow deformations through time series analysis with an accuracy in the centimeter or even millimeter range. Thereby, the selection of high-quality int...
Enregistré dans:
Auteurs principaux: | Yufang He, Guangzong Zhang, Hermann Kaufmann, Guochang Xu |
---|---|
Format: | article |
Langue: | EN |
Publié: |
MDPI AG
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/a3de4dda87704f40ab06f4137a1c5d10 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Accuracy verification and evaluation of small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) for monitoring mining subsidence
par: Qiuxiang Tao, et autres
Publié: (2021) -
InSAR Monitoring of Arctic Landfast Sea Ice Deformation Using L-Band ALOS-2, C-Band Radarsat-2 and Sentinel-1
par: Zhaohua Chen, et autres
Publié: (2021) -
Bangladeshi Native Vehicle Classification Based on Transfer Learning with Deep Convolutional Neural Network
par: Md Mahibul Hasan, et autres
Publié: (2021) -
Unmanned Aerial System-Based Weed Mapping in Sod Production Using a Convolutional Neural Network
par: Jing Zhang, et autres
Publié: (2021) -
Accuracy Verification and Correction of D-InSAR and SBAS-InSAR in Monitoring Mining Surface Subsidence
par: Yang Chen, et autres
Publié: (2021)