Assessment of Ground Deformation and Landslide Susceptibility Using InSAR and Hypsometric Data in Jayapura City, Papua

Authors

  • Nur Ayu Anas Geological Engineering Study Program, Faculty of Engineering, Cenderawasih University, Jl. Kampwolker, Yabansai, Heram, Jayapura, Papua 99351 https://orcid.org/0009-0004-3593-4898
  • Harsan Ingot Hasudungan Civil Engineering Study Program, Faculty of Engineering, Cenderawasih University, Papua, 99351, Indonesia
  • Rahmat Indrajati Geological Engineering Study Program, Faculty of Engineering, Cenderawasih University, Papua, 99351, Indonesia and Papua Regional Chapter of the Indonesian Association of Geologists (IAGI), Papua, 99351, Indonesia.
  • Marcelino N. Yonas Mineral Engineering Study Program, Faculty of Engineering, Cenderawasih University, Papua, 99351, Indonesia.
  • Harnanti Y. Hutami Geophysical Engineering Department, Faculty of Industry and Technology, Institut Teknologi Sumatera 35365, Indonesia

DOI:

https://doi.org/10.70561/geocelebes.v9i2.45404

Keywords:

Deformation, Hypsometric, Landslide Susceptibility, SAR Interferometry

Abstract

Ground deformation and landslides are major geohazards affecting Jayapura City, Papua, due to its active tectonic setting and steep topography. This study aims to assess the correlation between surface deformation and landslide susceptibility using a combination of Interferometric Synthetic Aperture Radar (InSAR) and hypsometric analysis. Sentinel-1A SAR data from ascending and descending tracks, combined with DEMNAS elevation data, were used to detect deformation patterns and evaluate geomorphological maturity through hypsometric parameters. The results reveal significant deformation patterns, including subsidence up to –0.77 m and uplift up to +0.25 m, predominantly concentrated in sub-watersheds Sw2, Sw3, and Sw4. Hypsometric analysis indicates that most sub-watersheds are in the mature geomorphological stage (HI between 0.476 and 0.495), except Sw14, which is classified as young (HI = 0.501). Validation with the landslide inventory further confirms this correlation: 75% of documented landslides occurred in areas of high deformation, while 25% were associated with moderate deformation, and none in low or stable zones. These findings provide essential insights for disaster risk reduction, highlighting priority areas for slope stabilization, land-use management, and early warning systems.

References

Abrauw, R. D. (2017). Wilayah rawan longsor di Kota Jayapura. Jurnal Geografi Lingkungan Tropik, 1(1), 2. https://doi.org/10.7454/jglitrop.v1i1.4

Ahmad, M. S., Lisa, M., & Khan, S. (2024). Assessment and mapping of landslides in steep mountainous terrain using PS-InSAR: A case study of Karimabad Valley in Chitral. Kuwait Journal of Science, 51(1), 100137. https://doi.org/10.1016/j.kjs.2023.09.007

Alaska Satellite Facility Distributed Active Archive Center (ASF DAAC). (2025). Sentinel-1 data search and download portal. University of Alaska Fairbanks. https://search.asf.alaska.edu/

Alonso-Díaz, A., Casado-Rabasco, J., Solla, M., & Lagüela, S. (2023). Using InSAR and GPR Techniques to Detect Subsidence: Application to the Coastal Area of “A Xunqueira” (NW Spain). Remote Sensing, 15(15), 3729. https://doi.org/10.3390/rs15153729

Arabameri, A., Pradhan, B., Rezaei, K., & Lee, C.-W. (2019). Assessment of landslide susceptibility using statistical- and artificial intelligence-based FR-RF integrated model and multiresolution DEMs. Remote Sensing, 11(9), 999. https://doi.org/10.3390/rs11090999

Ardan. (2024). Jayapura Hujan Deras, Akibatkan Longsor dan Banjir. Radio Republik Indonesia Jayapura (RRI). https://www.rri.co.id/daerah/1199068/jayapura-hujan-deras-akibatkan-longsor-dan-banjir

Aristizábal, E., & Korup, O. (2025). Linking Landslide Patterns to Transient Landscapes in the Northern Colombian Andes. Journal of Geophysical Research: Earth Surface, 130(3), e2024JF008027. https://doi.org/10.1029/2024JF008027

Badan Informasi Geospasial. (2018). DEMNAS. Bada Informasi Geospasial. https://tanahair.indonesia.go.id/portal-web/unduh/demnas

Bianchini, S., Solari, L., Bertolo, D., Thuegaz, P., & Catani, F. (2021). Integration of satellite interferometric data in civil protection strategies for landslide studies at a regional scale. Remote Sensing, 13(10), 1881. https://doi.org/10.3390/rs13101881

Brengman, C. M. J., & Barnhart, W. D. (2021). Identification of Surface Deformation in InSAR Using Machine Learning. Geochemistry, Geophysics, Geosystems, 22(3), 1–15. https://doi.org/10.1029/2020GC009204

Cai, J., Zhang, L., Dong, J., Guo, J., Wang, Y., & Liao, M. (2023). Automatic identification of active landslides over wide areas from time-series InSAR measurements using Faster RCNN. International Journal of Applied Earth Observation and Geoinformation, 124(November), 103516. https://doi.org/10.1016/j.jag.2023.103516

Casagli, N., Intrieri, E., Tofani, V., Gigli, G., & Raspini, F. (2023). Landslide detection, monitoring and prediction with remote-sensing techniques. Nature Reviews Earth and Environment, 4(1), 51–64. https://doi.org/10.1038/s43017-022-00373-x

Chatterjee, S., Ansari, K., Biswas, M., Mukherjee, S., & Kavitha, B. (2024). Morphometry and active tectonics of the Konkan coast, western India. Evolving Earth, 2(January), 100041. https://doi.org/10.1016/j.eve.2024.100041

Dai, K., Deng, J., Xu, Q., Li, Z., Shi, X., Hancock, C., Wen, N., Zhang, L., & Zhuo, G. (2022). Interpretation and sensitivity analysis of the InSAR line of sight displacements in landslide measurements. GIScience and Remote Sensing, 59(1), 1226–1242. https://doi.org/10.1080/15481603.2022.2100054

Diercks, M.-L., Grützner, C., Welte, J., & Ustaszewski, K. (2023). Challenges of geomorphologic analysis of active tectonics in a slowly deforming karst landscape (W Slovenia and NE Italy). Geomorphology, 440(November), 108894. https://doi.org/10.1016/j.geomorph.2023.108894

Dong, J., Guo, Y., Mei, Y., & Gao, K. (2025). Deformation monitoring and safety stability evaluation study of high-altitude limestone dumps. PLoS ONE, 20(2 February), 1–27. https://doi.org/10.1371/journal.pone.0318589

European Space Agency. (2014). Sentinel-1 SAR data. Copernicus Open Access Hub. https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-1

Evarukdijati. (2019a). Banjir dan Tanah Longsor melanda kota jayapura. Antara News. https://papua.antaranews.com/berita/475037/banjir-dan-tanah-longsor-melanda-kota-jayapura

Evarukdijati. (2019b). Longsor di Kawasan Ampera Kota Jayapura, empat orang meninggal. https://www.antaranews.com/berita/811167/longsor-di-kawasan-ampera-kota-jayapura-empat-orang-meninggal

Evarukdijati. (2022). Tanah longsor menyebabkan tujuh orang meninggal di Kota Jayapura. Antara News.

Fan, B., Luo, G., Hellwich, O., Shi, X., Yuan, X., Ma, X., Shang, M., & Wang, Y. (2024). Monitoring Creeping Landslides with InSAR in a Loess-covered Mountainous Area in the Ili Valley, Central Asia. PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 92(3), 235–251. https://doi.org/10.1007/s41064-024-00292-0

Farolfi, G., Del Soldato, M., Bianchini, S., & Casagli, N. (2019). A procedure to use GNSS data to calibrate satellite PSI data for the study of subsidence:an example from the north-western Adriatic coast (Italy). European Journal of Remote Sensing, 52(sup4), 54–63. https://doi.org/10.1080/22797254.2019.1663710

Gao, X., Wang, B., Dai, W., & Liu, Y. (2025). A landslide susceptibility assessment method using SBAS-InSAR to optimize Bayesian network. Frontiers in Environmental Science, 13(February), 1–25. https://doi.org/10.3389/fenvs.2025.1522949

Gera, S., & Agegnehu, N. (2021). Landslide Susceptible Mapping using InSAR and GIS Techniques: A Case Study at Debresina Area, Ethiopia. Journal of Geology and Geophysics, 10(3), 988. https://www.longdom.org/open-access-pdfs/landslide-susceptible-mapping-using-insar-and-gis-techniques-overview-of-debresina-area-ethiopia.pdf

Gu, Z.-K., Yao, X., Yao, C.-C., & Li, C.-G. (2021). Mapping of geomorphic dynamic parameters for analysis of landslide hazards: A case of Yangbi river basin on the upper Lancang-Mekong of China. Journal of Mountain Science, 18(9), 2402–2411. https://doi.org/10.1007/s11629-021-6795-2

Guo, H., & Martínez-Graña, A. M. (2024). Susceptibility of Landslide Debris Flow in Yanghe Township Based on Multi-Source Remote Sensing Information Extraction Technology (Sichuan, China). Land, 13(2), 206. https://doi.org/10.3390/land13020206

Gururani, K., Kothyari, G. C., & Kotlia, B. S. (2023). Morphotectonic assessment of the Gaula river basin, Kumaun lesser Himalaya, Uttarakhand. Quaternary Science Advances, 12(October), 100115. https://doi.org/10.1016/j.qsa.2023.100115

Guvel, Ş. P., Akgul, M. A., & Akkoyunlu, M. F. (2023). Monitoring and Evaluation of 2015 Devrek Zonguldak Landslide within the scope of Flood Risk Assessment by Landsat-8 Satellite Data. Doğal Afetler ve Çevre Dergisi, 9(1), 81–89. https://doi.org/10.21324/dacd.1152670

Hang, P. T. T., Shakirov, R., Thom, B. V., Dung, L. V., Syrbu, N., Hieu, T. T., Anh, P. T. N., Yen, T. H., Maltseva, E., Kholmogorov, A., Tuyen, N. H., & An, V. H. (2025). Assessment of the Tectonic Activity of the Muong La–Bac Yen–Cho Bo Fault (Northwest Vietnam) by Analysis of Geomorphological Indices. GeoHazards, 6(2), 16. https://doi.org/10.3390/geohazards6020016

Hu, X., Sun, Z., Wang, Z., Huang, X., Zhou, M., He, S., Xiao, H., Liu, D., Yang, Y., & Xu, W. (2025). InSAR-based deep learning prediction model for multi-type landslides displacement and failure time in Zigui, Three Gorges Area, China. Landslides, (2025). https://doi.org/10.1007/s10346-025-02613-9

Juna. (2025). 900 Unit Perumahan Grand Royal Residen II akan Dibangun di Holtekamp. Cenderawasih Pos. https://cenderawasihpos.jawapos.com/ekonomi-bisnis/04/02/2025/900-unit-perumahan-grand-royal-residen-ii-akan-dibangun-di-holtekamp/%0A

Katharina. (2021). Jayapura Rawan Longsor, Warga Harus Waspada. Kumparan. https://kumparan.com/bumi-papua/jayapura-rawan-longsor-warga-harus-waspada-1vE0VmMh3zo/full

Keller, E. A., & Pinter, N. (2002). Active Tectonics Earthquakes, Uplift, and Landscape. In Prentice Hall earth science series (second edi). Prentice Hall. https://doi.org/10.2113/gseegeosci.iii.3.463

Khattab, M. I., Abotalib, A. Z., Othman, A., & Selim, M. K. (2023). Evaluation of multiple digital elevation models for hypsometric analysis in the watersheds affected by the opening of the Red Sea. The Egyptian Journal of Remote Sensing and Space Science, 26(4), 1020–1035. https://doi.org/10.1016/j.ejrs.2023.11.011

Kothyari, H. C., Kothyari, G. C., Joshi, R. C., Gururani, K., Nandy, S., & Patidar, A. K. (2024). Assessment of fluvial response to landslide susceptibility and transient response of tectonically active upper Alaknanda River basin of Uttarakhand Himalaya, India. Quaternary Science Advances, 15(September), 100221. https://doi.org/10.1016/j.qsa.2024.100221

Lau, R., Seguí, C., Waterman, T., Chaney, N., & Veveakis, M. (2024). InSAR-informed in situ monitoring for deep-seated landslides: insights from El Forn (Andorra). Natural Hazards and Earth System Sciences, 24(10), 3651–3661. https://doi.org/10.5194/nhess-24-3651-2024

Leloltery, A. (2025). BPBD Papua: Longsor Jalan Ring Road Kota Jayapura Perlu Penanganan Serius. Antara News. https://papua.antaranews.com/berita/735782/bpbd-papua-longsor-jalan-ring-road-kota-jayapura-perlu-penanganan-serius

Li, C., Yi, B., Gao, P., Li, H., Sun, J., Chen, X., & Zhong, C. (2021). Valuable clues for dcnn-based landslide detection from a comparative assessment in the wenchuan earthquake area. Sensors, 21(15), 5191. https://doi.org/10.3390/s21155191

Liem, N. V., Dat, N. P., Dieu, B. T., Phai, V. V., Trinh, P. T., Vinh, H. Q., & Phong, T. V. (2016). Assessment of Geomorphic Processes and Active Tectonics in Con Voi Mountain Range Area (Northern Vietnam) Using the Hypsometric Curve Analysis Method. Vietnam Journal of Earth Sciences, 38(2), 202–216. https://doi.org/10.15625/0866-7187/38/2/8602

Lin, N., Ding, K., Tan, L., Li, B., Yang, K., Wang, C., Wang, B., Li, N., & Yang, R. (2025). Dynamic landslide susceptibility mapping on time-series InSAR and explainable machine learning: a case study at Wushan in the Three Gorges Reservoir area, China. Advances in Space Research, 75(12), 8439–8465. https://doi.org/10.1016/j.asr.2025.03.067

Makrari, S., Sharma, G., Taloor, A. K., Singh, M. S., Sarma, K. K., & Aggarwal, S. P. (2022). Assessment of the geomorphic indices in relation to tectonics along selected sectors of Borpani River Basin, Assam using Cartosat DEM data. Geosystems and Geoenvironment, 1(3), 100068. https://doi.org/10.1016/j.geogeo.2022.100068

Miao, F., Ruan, Q., Wu, Y., Qian, Z., Kong, Z., & Qin, Z. (2023). Landslide Dynamic Susceptibility Mapping Base on Machine Learning and the PS-InSAR Coupling Model. Remote Sensing, 15(22), 5427. https://doi.org/10.3390/rs15225427

Mondini, A. C., Santangelo, M., Rocchetti, M., Rossetto, E., Manconi, A., & Monserrat, O. (2019). Sentinel-1 SAR amplitude imagery for rapid landslide detection. Remote Sensing, 11(7), 0760. https://doi.org/10.3390/rs11070760

Mulyasari, R., Brahmantyo, B., & Supartoyo. (2017). Morphometric analysis of relative tectonic activity in the Baturagung Mountain, Central Java, Indonesia. IOP Conference Series: Earth and Environmental Science, 71(1), 012006. https://doi.org/10.1088/1755-1315/71/1/012006

Nikoonejad, A., Pourkermani, M., Asadi, A., & Almasian, M. (2015). Hypsometric Properties of South Zagros Fold-Thrust Belt Basins: A Case Study in Namdan Basin in SW Iran. Open Journal of Geology, 5(10), 701–717. https://doi.org/10.4236/ojg.2015.510062

Novellino, A., Cesarano, M., Cappelletti, P., Di Martire, D., Di Napoli, M., Ramondini, M., Sowter, A., & Calcaterra, D. (2021). Slow-moving landslide risk assessment combining Machine Learning and InSAR techniques. Catena, 203(August), 105317. https://doi.org/10.1016/j.catena.2021.105317

Ntokos, D. (2025). Unveiling tectonic activity through lithological-erosional interplay with the Τectonic Processes Index Tδ. Journal of Asian Earth Sciences, 291(September), 106680. https://doi.org/10.1016/j.jseaes.2025.106680

Othman, A. A., Gloaguen, R., Andreani, L., & Rahnama, M. (2018). Improving landslide susceptibility mapping using morphometric features in the Mawat area, Kurdistan Region, NE Iraq: Comparison of different statistical models. Geomorphology, 319, 147–160. https://doi.org/10.1016/j.geomorph.2018.07.018

Pamanggori. (2024). Longsor menimpa Pasar Ikan Dok 9 Namun Tidak Ada Korban Jiwa. Noken Live. https://www.nokenlive.com/2024/12/18/longsor-menimpa-pasar-ikan-dok-9-namun-tidak-ada-korban-jiwa/

Patel, D. K., Thakur, T. K., Saini, S., Patel, A., Bhatt, S. C., Kumar, A., Kumar, R., & Husain, F. M. (2024). Morphometric indices assessment: Implications for active tectonics in the upper Narmada Basin, central India. Physics and Chemistry of the Earth, 136(December), 103746. https://doi.org/10.1016/j.pce.2024.103746

Piroton, V., Schlögel, R., Barbier, C., & Havenith, H.-B. (2020). Monitoring the recent activity of landslides in the Mailuu-Suu valley (Kyrgyzstan) using radar and optical remote sensing techniques. Geosciences, 10(5), 164. https://doi.org/10.3390/geosciences10050164

Rabii, F., Achour, H., Rebai, N., & Jallouli, C. (2017). Hypsometric integral for the identification of neotectonic and lithology differences in low tectonically active area (Utica-Mateur region, north-eastern Tunisia). Geocarto International, 32(11), 1229–1242. https://doi.org/10.1080/10106049.2016.1195890

Ramzan, U., Fan, H., Aeman, H., Ali, M., & Al-qaness, M. A. A. (2022). Combined analysis of PS-InSAR and hypsometry integral (HI) for comparing seismic vulnerability and assessment of various regions of Pakistan. Scientific Reports, 12, 22423. https://doi.org/10.1038/s41598-022-26159-1

Ran, P., Li, S., Zhuo, G., Wang, X., Meng, M., Liu, L., Chen, Y., Huang, H., Ye, Y., & Lei, X. (2023). Early Identification and Influencing Factors Analysis of Active Landslides in Mountainous Areas of Southwest China Using SBAS−InSAR. Sustainability (Switzerland), 15(5), 4366. https://doi.org/10.3390/su15054366

Romero, R. V. (2024). Application of Geographic Information System (GIS) for Hypsometric Analysis of a Bicol River Basin Area. Engineering and Technology Journal, 09(08), 4787–4794. https://doi.org/10.47191/etj/v9i08.25

Saepuloh, A. (2021). Prinsip dan aplikasi penginderaan jauh geologi gunungapi. ITB Press.

Schumm, S. A. (1956). Geological Society of America Bulletin Evolution Of Drainage Systems And Slopes In Badlands At Perth Amboy , New Jersey. Bulletin of the Geological Society of America, 67(5), 597–646. https://doi.org/10.1130/0016-7606(1956)67

Shan, Y., Xu, Z., Zhou, S., Lu, H., Yu, W., Li, Z., Cao, X., Li, P., & Li, W. (2024). Landslide Hazard Assessment Combined with InSAR Deformation: A Case Study in the Zagunao River Basin, Sichuan Province, Southwestern China. Remote Sensing, 16(1), 99. https://doi.org/10.3390/rs16010099

Sorkhabi, O. M., Khajehzadeh, M., & Keawsawasvong, S. (2023). Landslides monitoring with SBAS-InSAR and GNSS. Physics and Chemistry of the Earth, 132(December), 103486. https://doi.org/10.1016/j.pce.2023.103486

Staniewicz, S., & Chen, J. (2024). Automatic Detection of InSAR Surface Deformation Signals in the Presence of Severe Tropospheric Noise, TechRxiv, 1–12. https://doi.org/10.36227/techrxiv.20128406.v2

Strząbała, K., Ćwiąkała, P., & Puniach, E. (2024). Identification of Landslide Precursors for Early Warning of Hazards with Remote Sensing. Remote Sensing, 16(15), 2781. https://doi.org/10.3390/rs16152781

Suwarna, N., & Noya, Y. (1995). Peta geologi lembar Jayapura (Pegunungan Cycloops), Irian Jaya. Pusat Penelitian dan Pengembangan Geologi (P3G). Bandung.

Vijith, H., Prasannakumar, V., & Pratheesh, P. (2017). Landform evaluation through hypsometric characterisation: An example from a selected river basin in Southern Western Ghats, India. Environmental Research, Engineering and Management, 73(4), 41–57. https://doi.org/10.5755/j01.erem.73.4.19553

Welikanna, D., & Jin, S. (2023). Investigating ground deformation due to a series of collapse earthquakes by means of the ps-insar technique and sentinel 1 data in kandy, sri lanka. Journal of Applied Remote Sensing, 17(1), 014507. https://doi.org/10.1117/1.jrs.17.014507

Wu, X., Qi, X., Peng, B., & Wang, J. (2024). Optimized Landslide Susceptibility Mapping and Modelling Using the SBAS-InSAR Coupling Model. Remote Sensing, 16(16). https://doi.org/10.3390/rs16162873

Yao, Z., Chen, M., Zhan, J., Zhuang, J., Sun, Y., Yu, Q., & Yu, Z. (2023). Refined Landslide Susceptibility Mapping by Integrating the SHAP-CatBoost Model and InSAR Observations: A Case Study of Lishui, Southern China. Applied Sciences, 13(23), 12817. https://doi.org/10.3390/app132312817

Yu, W., Li, W., Wu, Z., Lu, H., Xu, Z., Wang, D., Dong, X., & Li, P. (2024). Integrated Remote Sensing Investigation of Suspected Landslides: A Case Study of the Genie Slope on the Tibetan Plateau, China. Remote Sensing, 16(13), 2412. https://doi.org/10.3390/rs16132412

Zhang, X., Gan, S., Yuan, X., Zong, H., Wu, X., & Shao, Y. (2024). Early Identification and Characteristics of Potential Landslides in Xiaojiang Basin, Yunnan Province, China Using Interferometric Synthetic Aperture Radar Technology. Sustainability (Switzerland), 16(11), 4649. https://doi.org/10.3390/su16114649

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2025-10-30

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Anas, N. A., Hasudungan, H. I., Indrajati, R., Yonas, M. N., & Hutami, H. Y. (2025). Assessment of Ground Deformation and Landslide Susceptibility Using InSAR and Hypsometric Data in Jayapura City, Papua. JURNAL GEOCELEBES, 9(2), 171–188. https://doi.org/10.70561/geocelebes.v9i2.45404

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