Heavy Rain Episodes Identified by L-band InSAR and Limitations of Split-Spectrum Method in Indonesia
Abstract
Located in a tropical area with abundant precipitation, Indonesia is highly prone to heavy rain hazards, in particular landslides and floods. Thus, rainfall observation is vital. Nonetheless, the topography, the fund availability, as well as the archipelagic state of Indonesia may raise difficulties for in-situ observation, such as rain gauge and weather radar. Currently, the advance of radiometer satellites, such as the Global Precipitation Mission delivers rain estimation and has proven to show good association with in-situ observation on a monthly basis, not daily over the Indonesia area. Therefore, it is vital to have additional measurement methods. For the first time, we apply L-band Interferometric Synthetic Aperture Radar (InSAR) to observe heavy rain in Indonesia. From our three study cases, we successfully identified localized anomalies due to the dense water vapor during heavy rain in the InSAR images. The localized anomalies vary from 10.9 cm in West Java, 7.8 cm in East Kalimantan, and 7.7 cm in West Kalimantan. Furthermore, we utilize the split-spectrum method for our InSAR result; the high-water vapor occurrence in the troposphere associated with heavy rain should be identified in the non-dispersive term. Nevertheless, due to long temporal separation and thinner bandwidth, the split-spectrum method results display unsatisfactory results. We conclude that, while InSAR has the ability to identify heavy rain, having SSM to distinguish between non-dispersive and dispersive phases is not currently practical in Indonesia.
References
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Biggs, J., Anthony, E. Y., & Ebinger, C. J. (2009). Multiple inflation and deflation events at Kenyan volcanoes, East African Rift. Geology, 37(11), 979–982. https://doi.org/10.1130/G30133A.1
Brcic, R., Parizzi, A., Eineder, M., Bamler, R., & Meyer, F. (2011). Ionospheric effects in SAR interferometry: An analysis and comparison of methods for their estimation. International Geoscience and Remote Sensing Symposium (IGARSS), 1497–1500. https://doi.org/10.1109/IGARSS.2011.6049351
Costantini, M. (1998). A novel phase unwrapping method based on network programming. IEEE Transactions on geoscience and remote sensing, 36(3), 813-821.
Furuya, M., Suzuki, T., Maeda, J., & Heki, K. (2017). Midlatitude sporadic-E episodes viewed by L-band split-spectrum InSAR. Earth, Planets and Space, 69(1). https://doi.org/10.1186/s40623-017-0764-6
Furuya, M. (2011). Sar Interferometry. 1–24. Encyclopedia of Solid Earth Geophysics. Springer. https://doi.org/10.1007/978-90-481-8702-7
Gomba, G., Parizzi, A., De Zan, F., Eineder, M., & Bamler, R. (2016). Toward operational compensation of ionospheric effects in SAR interferograms: The split-spectrum method. IEEE Transactions on Geoscience and Remote Sensing, 54(3), 1446–1461. https://doi.org/10.1109/TGRS.2015.2481079
Halimatussadiah, A., Resosudarmo, B. P., & Widyawati, D. (2017). Social capital to induce a contribution to environmental collective action: results from a laboratory experiment in Indonesia. International Journal of Environment and Sustainable Development, 16(4), 397-414. https://doi.org/10.1504/IJESD.2017.087262
Hanssen, R. (1998). Atmospheric heterogeneities in ERS tandem SAR interferometry (Issue 98). Retrieved from http://doris.tudelft.nl/Literature/hanssen98i.html.
Hanssen, R. F. (2002). Radar Interferometry, Data Interpretation and Error Analysis. Springer Science & Business Media.
Jakowski, N., Heise, S., Stankov, S. M., & Tsybulya, K. (2006). Remote sensing of the ionosphere by space-based GNSS observations. Advances in Space Research, 38(11), 2337–2343. https://doi.org/10.1016/j.asr.2005.07.015
Jin, S., Wang, Q., & Dardanelli, G. (2022). A review on multi-GNSS for earth observation and emerging applications. Remote Sensing, 14(16), https://doi.org/10.3390/rs14163930
Jung, H. S., Lee, D. T., Lu, Z., & Won, J. S. (2013). Ionospheric correction of SAR interferograms by multiple-aperture interferometry. IEEE Transactions on Geoscience and Remote Sensing, 51(5), 3191–3199. https://doi.org/10.1109/TGRS.2012.2218660
Kinoshita, Y., Shimada, M., & Furuya, M. (2013). InSAR observation and numerical modeling of the water vapor signal during a heavy rain: A case study of the 2008 Seino event, central Japan. Geophysical Research Letters, 40(17), 4740–4744. https://doi.org/10.1002/grl.50891
Lee, H. (2015). General Rainfall Patterns in Indonesia and the Potential Impacts of Local Seas on Rainfall Intensity. Water, 7(12), 1751–1768. https://doi.org/10.3390/w7041751
Liang, C., Agram, P., Simons, M., & Fielding, E. J. (2019). Ionospheric correction of InSAR time series analysis of C-band sentinel-1 TOPS data. IEEE Transactions on Geoscience and Remote Sensing, 57(9), 6755–6773. https://doi.org/10.1109/TGRS.2019.2908494
Maeda, J., Suzuki, T., Furuya, M., & Heki, K. (2016). Imaging the midlatitude sporadic e plasma patches with a coordinated observation of spaceborne InSAR and GPS total electron content. Geophysical Research Letters, 43(4), 1419–1425. https://doi.org/10.1002/2015GL067585
Massonnet, D., Rossi, M., Carmona, C., Adragna, F., Peltzer, G., Feigl, K., & Rabaute, T. (1993). The displacement field of the Landers earthquake mapped by radar interferometry. nature, 364(6433), 138-142.
Mateus, P., Catalao, J., & Nico, G. (2017). Sentinel-1 Interferometric SAR mapping of precipitable water vapor over a country-spanning area. IEEE Transactions on Geoscience and Remote Sensing, 55(5), 2993–2999. https://doi.org/10.1109/TGRS.2017.2658342
Mateus, P., Nico, G., Tom, R., & Catal, J. (2012). on the Mitigation of Atmospheric Phase Delay Artefacts in Interferometric Sar Time Series. Retrieved from https://www.esa.int/
Meyer, F., Bamler, R., Jakowski, N., & Fritz, T. (2006). The potential of low-frequency SAR systems for mapping ionospheric TEC distributions. IEEE Geoscience and Remote Sensing Letters, 3(4), 560–564. https://doi.org/10.1109/LGRS.2006.882148
Okamoto, K., Ushio, T., Iguchi, T., Takahashi, N., & Iwanami, K. (2005). The Global Satellite Mapping of Precipitation (GSMaP) project. International Geoscience and Remote Sensing Symposium (IGARSS), 5(3), 3414–3416. https://doi.org/10.1109/IGARSS.2005.1526575
Permana, D. S., Hutapea, T. D., Praja, A. S., Paski, J. A. I., Makmur, E. E. S., Haryoko, U., Umam, I. H., Saepudin, M., & Adriyanto, R. (2019). The Indonesia In-House Radar Integration System (InaRAISE) of Indonesian Agency for Meteorology Climatology and Geophysics (BMKG): Development, Constraint, and Progress. IOP Conference Series: Earth and Environmental Science, 303(1). https://doi.org/10.1088/1755-1315/303/1/012051
Rosen, P. A., Hensley, S., & Chen, C. (2010). Measurement and mitigation of the ionosphere in L-band Interferometric SAR data. IEEE National Radar Conference - Proceedings, 1459–1463. https://doi.org/10.1109/RADAR.2010.5494385
Setiawan, N., & Furuya, M. (2021). Tropospheric dispersive phase anomalies during heavy rain detected by L-band InSAR and their interpretation. Earth, Planets and Space, 73(1). https://doi.org/10.1186/s40623-021-01470-9
Setiyoko, A., Osawa, T., & Nuarsa, W. (2019). Evaluation of GSMaP Precipitation Estimates Over Indonesia. International Journal of Environment and Geosciences, 3(1), 43. https://doi.org/10.24843/ijeg.2019.v03.i01.p04
Supari S., Sudibyakto S., Ettema, J., & Aldrian, E. (2012). Spatiotemporal characteristics of extreme rainfall events Over Java Island, Indonesia. Indonesian Journal of Geography, 44(1), 62-86.
Ushio, T., Sasashige, K., Kubota, T., Shige, S., Okamoto, K., Aonashi, K., Inoue, T., Takahashi, N., Iguchi, T., Kachi, M., Oki, R., Morimoto, T., & Kawasaki, Z. I. (2009). A kalman filter approach to the global satellite mapping of precipitation (GSMaP) from combined passive microwave and infrared radiometric data. Journal of the Meteorological Society of Japan, 87 A, 137–151. https://doi.org/10.2151/jmsj.87A.137
Yang, Z., Li, Z., Zhu, J., Wang, Y., & Wu, L. (2020). Use of SAR/InSAR in mining deformation monitoring, parameter inversion, and forward predictions: A review. IEEE Geoscience and Remote Sensing Magazine, 8(1), 71-90. https://doi.org/10.1109/MGRS.2019.2954824
Yasuda, T., & Furuya, M. (2015). Dynamics of surge-type glaciers in West Kunlun Shan, Northwestern Tibet. Journal of Geophysical Research: Earth Surface, 120(11), 2393–2405. https://doi.org/10.1002/2015JF003511
Published
2024-04-07
How to Cite
SETIAWAN, Naufal; FURUYA, Masato.
Heavy Rain Episodes Identified by L-band InSAR and Limitations of Split-Spectrum Method in Indonesia.
Geosfera Indonesia, [S.l.], v. 9, n. 1, p. 1-15, apr. 2024.
ISSN 2614-8528.
Available at: <https://jurnal.unej.ac.id/index.php/GEOSI/article/view/38154>. Date accessed: 20 nov. 2024.
doi: https://doi.org/10.19184/geosi.v9i1.38154.
Section
Original Research Articles
