Remote Sensing of Environment and Disaster Laboratory

Institute of Industrial Science, The University of Tokyo, Japan

Integration of SBAS-InSAR Time-series Data
into Maintenance Prioritization of Linear Rail Infrastructure In Bangladesh
Poster audio guide:
ポスターの音声ガイド:

Khin Myat Kyaw 1*, Wataru Takeuchi 1
1 Institute of Industrial Science, The University of Tokyo, Japan

Japanese

photo

EnglishAbstract: Inspection and maintenance of rail infrastructure is still a challenging task for decision makers as it is resource-intensive work. It has been identified that
Interferometric Synthetic Aperture Radar (InSAR) technique can detect the millimeter-level motion of the ground and this technique was regarded as one of the potential
tools in structural health monitoring (SHM). Dhaka-Kasiani-Gopalganj Railway, which connects the capital city Dhaka to Gopalganj city in the southern part ofBangladesh (~150 km long), is chosen as case study. Annual instability rate along railway line was estimated by SBAS-InSAR time-series analysis with Sentinel-1A datain ascending orbit from Jan 2020 to Oct 2023. Numerical atmospheric model ERA5 was applied for tropospheric delay correction in InSAR analysis. InSAR-basedinstability data was integrated into existing geological background and land cover patterns to perform correlation analysis so that potential damage locations can beidentified along the railway line. This study aims to help expand the application of InSAR data into engineering practices in linear rail infrastructure inspection andmaintenance prioritization.
Key Words: railway, sentinel-1, InSAR, maintenance, geology, land coverI. Introduction

II. Methodology

Previous studies have shown that InSAR can be used in structural
health monitoring in combination with conventional site-based
monitoring system (Chang et al., 2014; Macchiarulo et al., 2022).
However, there is limited evidence of InSAR application in SHM ofinfrastructure network in developing countries where maintenanceprioritization is a demanding topic along with quality-concerned
deterioration assessment. This study aims to help expand theapplication of InSAR data into engineering practices in linear rail
infrastructure health monitoring.

Table1. Data used in SBAS TSInSAR analysis

これまでの研究では、干渉SARは従来の現場ベースのモニタリングシステムと組み合わせて構造ヘルスモニタリングに使用できることが示されています(Chang et al., 2014;Macchiarulo et al., 2022)。しかし、開発途上国では、インフラ網のSHMにおける干渉SAR適用のエビデンスは限られており、品質に配慮した劣化評価とともに、メンテナンスの優先順位付けが厳しい課題となっています。 この研究は、インサルデータの応用をリニアレールインフラの健全性監視におけるエンジニアリング手法に拡大することを目的としています。

Fig1. Research Framework.

Fig2. Embankment constructions (google street view).

III. Results and Discussion
Fig3. Interferogram Network~ 150 km longFig4. Interferogram Network (from ISCE).

Wright et.al. (2004)
Kasiani Station

Fig3. Railway line superimposed on geology map.

Near Chapta Station

Fig5. Field visit to Kasiani and Chapta Station.

Fig8. Time-series displacement plot for location A, B and C.

Fig6. LOS velocity rate from SBAS-InSAR.

Fig9. Correlation evaluation between InSAR, land cover and geology.

• SBAS-InSAR result shows an agreement with LOS-projected GPS data (Fig-7) and field visit (Fig-5 & Fig-8).
Location A (Kasiani Station Fig-5 left, built area, no elevated embankment) → LOS velocity ~ +10 mm/yr (Fig-8)
Location B&C (near Chapta Station Fig-5 right, crop land, ~10m elevated embankment) → LOS velocity >-20 mm/yr.

• InSAR exhibits LOS displacement rate ranging from -60 to +20 mm/yr along railway line (Fig-6 & Fig-8).
• InSAR result indicates that railway line passing paddy field area has a high potential of instability (Fig-9 left).
“Crops” land cover type ~ -20 mm/yr.
• High rate of LOS displacement rate reported on “Alluvial silt and clay” soil type, followed by “Deltaic silt” and “Marshclay and peat” type (Fig-7 right).

Fig7. Validation with GPS data.

Fig10. Pixel count for different LOS displacement.

• Application of InSAR results in SHM
Threshold velocity Fig-10 (prioritization → resources)> ±20 mm/yr, (red) (~ 30% of total pixel count)between ±10 and ±20mm/yr (orange)< ±10 mm/yr (blue)• Multi-looked ~ 30x30m resolution for InSAR result.
• Future work → detailed analysis on current damage
condition in correlation with InSAR result.

For further details, contact: Khin Myat Kyaw, Bw-605, 6-1, Komaba 4-chome, Meguro, Tokyo 153-8505 JAPAN (URL: http://wtlab.iis.u-tokyo.ac.jp/ E-mail: khin22@iis.u-tokyo.ac.jp)