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Tropospheric Atmospheric Heterogeneities of ALOS-2 Interferograms in the Greater Bay Area

Authors :
Peng Liu
Xiaofei Chen
Source :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11777-11793 (2024)
Publication Year :
2024
Publisher :
IEEE, 2024.

Abstract

L-band advanced land observing satellite-2 (ALOS-2) images are a good source of radar data with better coherence than C-band images. However, significant ionospheric effects are often associated with L-band interferograms. In addition, the tropospheric delay can also be severe in subtropical coastal environments. In this work, different methods are adopted, adapted, or proposed to evaluate the tropospheric signals in ALOS-2 interferograms in the Shenzhen region. Ionospheric effects are estimated by the split spectrum method. Tropospheric delays are estimated through their height dependence or numerical weather prediction models. In addition to the conventional weighting methods that consider distance, variation, and Gaussian models, a stepwise approach to estimate tropospheric signals from height or to scale numerical weather models is proposed in this study. A combination of spectrometer observation and air mass trajectories is also proposed to assess topography-independent tropospheric signals, specifically the moderate resolution imaging spectroradiometer (MODIS) water vapor fields and the Hybrid Single-Particle Lagrangian Integrated Trajectory model. Meanwhile, possible cloud and wind patterns are observed from interferogram. This work demonstrates the feasibility of stepwise estimation of stratified signals using height information or numerical weather models. It also shows the potential for air mass trajectories to move water vapor fields to mitigate the influence of time difference between SAR and spectrometer acquisition times.

Details

Language :
English
ISSN :
19391404 and 21511535
Volume :
17
Database :
Directory of Open Access Journals
Journal :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.5fd08d79dde43788ad70d5befd4a4eb
Document Type :
article
Full Text :
https://doi.org/10.1109/JSTARS.2024.3414111