Are numerical weather model outputs helpful to reduce tropospheric delay signals in InSAR data? Y Kinoshita, M Furuya, T Hobiger, R Ichikawa Journal of Geodesy 87, 267-277, 2013 | 41 | 2013 |
Quantifying the effect of autonomous adaptation to global river flood projections: application to future flood risk assessments Y Kinoshita, M Tanoue, S Watanabe, Y Hirabayashi Environmental Research Letters 13 (1), 014006, 2018 | 39 | 2018 |
InSAR observation and numerical modeling of the water vapor signal during a heavy rain: A case study of the 2008 Seino event, central Japan Y Kinoshita, M Shimada, M Furuya Geophysical research letters 40 (17), 4740-4744, 2013 | 35 | 2013 |
On the importance of accurately ray-traced troposphere corrections for Interferometric SAR data T Hobiger, Y Kinoshita, S Shimizu, R Ichikawa, M Furuya, T Kondo, ... Journal of Geodesy 84, 537-546, 2010 | 34 | 2010 |
Detections and simulations of tropospheric water vapor fluctuations due to trapped lee waves by ALOS-2/PALSAR-2 ScanSAR interferometry Y Kinoshita, Y Morishita, Y Hirabayashi Earth, Planets and Space 69, 1-15, 2017 | 5 | 2017 |
Error Evaluation of L-Band InSAR Precipitable Water Vapor Measurements by Comparison with GNSS Observations in Japan K Matsuzawa, Y Kinoshita Remote Sensing 13 (23), 4866, 2021 | 4 | 2021 |
Localized delay signals detected by synthetic aperture radar interferometry and their simulation by WRF 4DVAR Y Kinoshita, M Furuya SOLA 13, 79-84, 2017 | 4 | 2017 |
Development of InSAR neutral atmospheric delay correction model by use of GNSS ZTD and its horizontal gradient Y Kinoshita IEEE Transactions on Geoscience and Remote Sensing 60, 1-14, 2022 | 3 | 2022 |
Slow slip event displacement on 2018 offshore Boso Peninsula detected by Sentinel-1 InSAR time-series analysis with numerical weather model assistance Y Kinoshita, R Furuta Geophysical Journal International 237 (1), 75-89, 2024 | | 2024 |
Assessing the performance of a hybrid InSAR atmospheric delay model combined with GNSS and ERA5 global atmospheric model Y Kinoshita AGU23, 2023 | | 2023 |
Landslide detection by deep learning based semantic segmentation using Sentinel-1 intensity images K Ito, Y Kinoshita | | 2023 |
Incorporating global atmospheric model products into the InSAR atmospheric delay model based on GNSS observations Y Kinoshita AGU Fall Meeting Abstracts 2022, G41A-05, 2022 | | 2022 |
Transient small displacement since the end of 2020 at Noto peninsula, Japan, revealed by Sentinel-1 InSAR time series analysis Y Kinoshita EGU General Assembly Conference Abstracts, EGU22-7145, 2022 | | 2022 |
Progress of developing InSAR atmospheric delay correction model based on GNSS ZTD and Its gradient Y Kinoshita AGU Fall Meeting Abstracts 2021, G45A-0386, 2021 | | 2021 |
Atmospheric noise mitigation in SAR interferometry: Current state of progress Y Kinoshita Proceedings of the 14th SEGJ International Symposium, Tokyo, Japan, 18–21 …, 2021 | | 2021 |
Developing InSAR atmospheric delay correction model based on GEONET ZTD and its gradient Y Kinoshita EGU General Assembly Conference Abstracts, EGU21-8146, 2021 | | 2021 |
Detecting surface displacement associated with the 2018 slow slip event off Boso peninsula by use of Sentinel-1 InSAR with atmospheric correction Y Kinoshita, T Nimura, R Furuta AGU Fall Meeting Abstracts 2019, T43G-0398, 2019 | | 2019 |
Source estimation of the large seasonal displacement using InSAR time series analysis. T Nimura, Y Kinoshita, R Furuta Geophysical Research Abstracts 21, 2019 | | 2019 |
InSAR atmospheric correction using precipitable water vapor information estimated from Himawari-8 geostationary meteorological satellite Y Kinoshita, T Nimura, R Furuta | | 2018 |
InSAR atmospheric correction using Himawari-8 Geostationary Meteorological Satellite Y Kinoshita, T Nimura, R Furuta AGU Fall Meeting Abstracts 2017, G23A-0883, 2017 | | 2017 |