The latest DTM using InSAR for dynamics detection of Semangko fault-Indonesia

    Atriyon Julzarika   Affiliation
    ; Trias Aditya   Affiliation
    ; Subaryono Subaryono Affiliation
    ; Harintaka Harintaka   Affiliation


The latest Digital Terrain Model (DTM) is seen as an upgradable DTM that is fitted to the latest combination of DTM master and its displacement. The latest DTM can be used to overcome the problem of static DTM weaknesses in displaying the latest topographic changes. DTM masters are obtained from InSAR and Digital Surface Model (DSM) ALOS PALSAR conversions. Meanwhile, the displacement is obtained from Sentinel-1 images, which can be updated every 6–12 days or at least every month. ALOS PALSAR data were the images acquired in 2008 and 2017, while Sentinel-1 data used were images acquired in 2018 and 2020. This study aims to reveal the importance of an upgradable DTM so called latest DTM which is combination of DTM master and its displacement in order to show the latest condition of study area. The case study is the dynamics analyze of the Semangko fault specifically in the Sianok and Sumani segments situated in Indonesia. The vertical accuracy assessment was done to evaluate the DSM to DTM conversion with a tolerance of 1.96σ. The result obtained is the latest DTM. It is derived from the integration of the DTM master with displacement. The latest DTM can be used to detect the dynamics of Semangko fault. The study area has vertical deformation at a value of –50 cm to 30 cm. The Semangko fault area is dominated by –25 to 5 cm deformation. In general, this region has decreased. The decline in this region ranges from 7.5 cm to 10 cm per year. The latest DTM vertical accuracy is 2.158 m (95% confidence level) with a scale of 1: 10,000 to 1: 20,000.

Keyword : the latest DTM, InSAR, ALOS PALSAR, Sentinel-1, Semangko fault

How to Cite
Julzarika, A., Aditya, T., Subaryono, S., & Harintaka, H. (2021). The latest DTM using InSAR for dynamics detection of Semangko fault-Indonesia. Geodesy and Cartography, 47(3), 118-130.
Published in Issue
Nov 9, 2021
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Alganci, U., Besol, B., & Sertel, E. (2018). Accuracy assessment of different digital surface models. ISPRS International Journal of Geo-Information, 7(3), 114.

Arai, Y. (2019). Pre-treatment for preventing degradation of measurement accuracy from speckle noise in speckle interferometry. Measurement, 136, 36–41.

Arefi, H., d’Angelo, P., Mayer, H., & Reinartz, P. (2009). Automatic generation of digital terrain models from Cartosat-1 stereo images. In ISPRS workshop Hannover 2009, 83(1–4–7), 1–6.

ASPRS. (2014). ASPRS Accuracy standards for Digital Geospatial Data. The American Society for Photogrammetry and Remote Sensing.

Bakon, M., Perissin, D., Lazecky, M., & Papco, J. (2014). Infrastructure nonlinear deformation monitoring via satellite radar interferometry. Procedia Technology, 16, 294–300.

Bayoud, F. A., & Sideris, M. G. (2003). Two different methodologies for geoid determination from ground and airborne gravity data. Geophysical Journal International, 155(3), 914–922.

Badan Informasi Geospasial. (2019). DEMNAS.

Bigdeli, B., Amini Amirkolaee, H., & Pahlavani, P. (2018). DTM extraction under forest canopy using LiDAR data and a modified invasive weed optimization algorithm. Remote Sensing of Environment, 216, 289–300.

Bonvalot, S., Balmino, G., Briais, A., Kuhn, M., Peyrefitte, A., Vales, N., & Biancale, R. (2012). World Gravity Map: a set of global complete spherical Bouguer and isostatic anomaly maps and grids. Geophysical Research Abstracts, 14, 11091.

Caro Cuenca, M., Hooper, A. J., & Hanssen, R. F. (2013). Surface deformation induced by water influx in the abandoned coal mines in Limburg, The Netherlands observed by satellite radar interferometry. Journal of Applied Geophysics, 88, 1–11.

Champion, N., & Boldo, D. (2006). A robust algorithm for estimating digital terrain models from digital surface models in dense urban areas. In Proceedings ISPRS Commission 3 Symposium, Photogrammetric Computer Vision.

Chang, L., Ku, O., & Hanssen, R. F. (2019). Identification of deformation pattern changes caused by enhanced oil recovery (EOR) using InSAR. International Journal of Remote Sensing, 40(4), 1495–1505.

Costantini, M. (1998). A novel phase unwrapping method based on network programming. IEEE Transactions on Geoscience and Remote Sensing, 36(3), 813–821.

Cuevas-González, M., Crosetto, M., Monserrat, O., & Crippa, B. (2018). Sentinel-1A/B imagery for terrain deformation monitoring: a strategy for Atmospheric Phase Screening (APS) estimation. Procedia Computer Science, 138, 388–392.

Dai, K., Li, Z., Tomás, R., Liu, G., Yu, B., Wang, X., Cheng, H., Chen, J., & Stockamp, J. (2016). Monitoring activity at the Daguangbao mega-landslide (China) using Sentinel-1 TOPS time series interferometry. Remote Sensing of Environment, 186, 501–513.

Dammann, D. O., Eicken, H., Meyer, F. J., & Mahoney, A. R. (2016). Assessing small-scale deformation and stability of landfast sea ice on seasonal timescales through L-band SAR interferometry and inverse modeling. Remote Sensing of Environment, 187, 492–504.

Dias, P., Catalao, J., & Marques, F. O. (2018). Sentinel-1 InSAR data applied to surface deformation in Macaronesia (Canaries and Cape Verde). Procedia Computer Science, 138, 382–387.

Du, Z., Ge, L., Ng, A. H.-M., Zhu, Q., Yang, X., & Li, L. (2018). Correlating the subsidence pattern and land use in Bandung, Indonesia with both Sentinel-1/2 and ALOS-2 satellite images. International Journal of Applied Earth Observation and Geoinformation, 67, 54–68.

EORC-JAXA. (2021). ALOS research and application project.

European Space Agency. (2019). Sentinel satellites.

Ferretti, A., Fumagalli, A., Novali, F., Prati, C., Rocca, F., & Rucci, A. (2011). A new algorithm for processing interferometric data-stacks: SqueeSAR. IEEE Transactions on Geoscience and Remote Sensing, 49(9), 3460–3470.

Ferretti, A., Monti-Guarnieri, A., Prati, C., & Fabio, R. (2007). InSAR principles: Guidelines for SAR interferometry processing and interpretation (TM-19). European Space Agency.

Gallant, J. C., Read, A. M., & Dowling, T. I. (2012). Removal of tree offsets from SRTM and other digital surface models. ISPRS – International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIX-B4(September), 275–280.

Geological. (2017). Sesar Semangko.

Hirt, C. (2014). Encyclopedia of geodesy. Springer.

Hofmann-Wellenhof, B., & Moritz, H. (2006). Physical geodesy (2nd ed.). Springer.

Hooper, A., Bekaert, D., Spaans, K., & Arikan, M. (2012). Recent advances in SAR interferometry time series analysis for measuring crustal deformation. Tectonophysics, 514–517, 1–13.

Hurukawa, N., Wulandari, B. R., & Kasahara, M. (2014). Earthquake history of the Sumatran fault, Indonesia, since 1892, derived from relocation of large earthquakes. Bulletin of the Seismological Society of America, 104(4), 1750–1762.

JAXA. (2008). ALOS data users handbook. Revision C.

Julzarika, A. (2015). Height model integration using ALOS PALSAR, X SAR, SRTM C, and IceSAT/GLAS. International Journal of Remote Sensing and Earth Sciences, 12(2), 107–116.

Julzarika, A., & Djurdjani, D. (2018). DEM classifications: opportunities and potential of its applications. Journal of Degraded and Mining Lands Management, 5(53).

Julzarika, A., & Harintaka. (2019). Utilization of sentinel satellite for vertical deformation monitoring in Semangko FAULT-Indonesia. In The 40th Asian Conference on Remote Sensing (ACRS 2019) (pp. 1–7).

Julzarika, A., & Harintaka. (2020). Indonesian DEMNAS: DSM or DTM? In 2019 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) (pp. 31–36). IEEE.

Julzarika, A., & Rokhmana, C. A. (2019). Detection of vertical deformation in Jakarta-Bandung high speed train route using X sar and sentinel. Geodesy and Cartography, 45(4), 169–176.

Katili, J. A. (1967). On the occurrence of Large Transcurrent Faults in Sumatra, Indonesia. Journal of Geosciences Osaka City University, 10, 5–17.

Koudogbo, F., Urdiroz, A., Robles, J. G., & Chapron, G. (2019). Radar interferometry as an innovative solution for monitoring the construc-tion of the Grand Paris Express metro network – First results. In INSAR Paper-Tre Altamira.

Koukouvelas, I. K., Zygouri, V., Nikolakopoulos, K., & Verroios, S. (2018). Treatise on the tectonic geomorphology of active faults: The significance of using a universal digital elevation model. Journal of Structural Geology, 116, 241–252.

Krauß, T. (2018). A new simplified DSM-to-DTM algorithm – dsm-to-dtm-step. Preprints.

Krauß, T., Arefi, H., & Reinartz, P. (2011). Evaluation of selected methods for extracting digital terrain models from satellite born digital sur-face models in urban areas. In SMPR 2011, (pp. 1–7).

Krauß, T., & Reinartz, P. (2007). Urban object detection using a fusion approach of dense urban digital surface models and VHR optical satellite stereo data. ISPRS Istanbul Workshop 2010 on Modeling of Optical Airborne and Spaceborne Sensors, 38, 13–18.

Lesko, M., Papco, J., Bakon, M., & Liscak, P. (2018). Monitoring of natural hazards in Slovakia by using of satellite radar interferometry. Procedia Computer Science, 138, 374–381.

Li, L., & Kuai, X. (2014). An efficient dichotomizing interpolation algorithm for the refinement of TIN-based terrain surface from contour maps. Computers and Geosciences, 72, 105–121.

Li, Z., Zhu, Q., & Gold, C. (2004). Digital terrain modeling: Principles and methodology. CRC Press.

Liosis, N., Marpu, P. R., Pavlopoulos, K., & Ouarda, T. B. M. J. (2018). Ground subsidence monitoring with SAR interferometry techniques in the rural area of Al Wagan, UAE. Remote Sensing of Environment, 216, 276–288.

Liu, C. L., Gao, X. Z., Jiang, W. D., & Li, X. (2011). Intergerometric ISAR three-dimensional imaging using one antenna. Progress in Electromagnetics Research M, 21, 33–45.

Liu, Y., Zhao, C., Zhang, Q., & Yang, C. (2018). Complex surface deformation monitoring and mechanism inversion over Qingxu-Jiaocheng, China with multisensor SAR images. Journal of Geodynamics, 114, 41–52.

Lubis, A. M., Sato, T., Tomiyama, N., Isezaki, N., & Yamanoku­chi, T. (2011). Ground subsidence in Semarang-Indonesia investigated by ALOS-PALSAR satellite SAR interferometry. Journal of Asian Earth Sciences, 40(5), 1079–1088.

Lusch, D. P. (1999). Introdcution to microwave remote sensing. The Photogrammetric Record, 24(126), 199.

Maune, D. F., & Nayegandhi, A. (2018). Digital elevation model technologies and applications: The DEM users manual. American Society for Photogrammetry and Remote Sensing.

Monserrat, O., Crosetto, M., & Luzi, G. (2014). A review of ground-based SAR interferometry for deformation measurement. ISPRS Journal of Photogrammetry and Remote Sensing, 93, 40–48.

Moudrý, V., Lecours, V., Gdulová, K., Gábor, L., Moudrá, L., Kropáček, J., & Wild, J. (2018). On the use of global DEMs in ecological modelling and the accuracy of new bare-earth DEMs. Ecological Modelling, 383, 3–9.

Mukherjee, S., Joshi, P. K., Mukherjee, S., Ghosh, A., Garg, R. D., & Mukhopadhyay, A. (2012). Evaluation of vertical accuracy of open source Digital Elevation Model (DEM). International Journal of Applied Earth Observation and Geoinformation, 21(1), 205–217.

Nahli, A., Durand, E., Rangeard, D., & Rangeard, D. (2018). Sentinel-1 for monitoring tunnel excavations in Rennes, France. Procedia Computer Science, 138, 393–400.

Naidoo, L., Mathieu, R., Main, R., Wessels, K., & Asner, G. P. (2016). L-band Synthetic Aperture Radar imagery performs better than optical datasets at retrieving woody fractional cover in deciduous, dry savannahs. International Journal of Applied Earth Observation and Geoinformation, 52, 54–64.

Natawidjaja, D. H. (2018). Updating active fault maps and sliprates along the Sumatran Fault Zone, Indonesia. IOP Conference Series: Earth and Environmental Science, 118(1), 012001.

Ng, A. H.-M., Ge, L., Du, Z., Wang, S., & Ma, C. (2017). Satellite radar interferometry for monitoring subsidence induced by longwall mining activity using Radarsat-2, Sentinel-1 and ALOS-2 data. International Journal of Applied Earth Observation and Geoinformation, 61, 92–103.

Passchier C. W., & Trouw R. A. J. (2005). Microtectonics. Springer.

Pieraccini, M., & Miccinesi, L. (2019). Ground-based radar interferometry: A bibliographic review. Remote Sensing, 11(9).

Pirotti, F. (2010). Assessing a template matching approach for tree height and position extraction from lidar-derived canopy height models of Pinus pinaster stands. Forests, 1(4), 194–208.

Quiroga, J. A., Servin, M., & Cuevas, F. (2002). Modulo 2π fringe orientation angle estimation by phase unwrapping with a regularized phase tracking algorithm. Journal of the Optical Society of America A, 19(8), 1524.

Raaflaub, L. D., & Collins, M. J. (2006). The effect of error in gridded digital elevation models on the estimation of topographic parameters. Environmental Modelling and Software, 21(5), 710–732.

Reigber, A., & Moreira, J. (1997). Phase unwrapping by fusion of local and global methods. In IGARSS’97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing – A Scientific Vision for Sustainable Development (Vol. 2, pp. 869–871). IEEE.

Rucci, A., Ferretti, A., Monti Guarnieri, A., & Rocca, F. (2012). Sentinel 1 SAR interferometry applications: The outlook for sub millimeter measurements. Remote Sensing of Environment, 120, 156–163.

Serrano-Juan, A., Pujades, E., Vázquez-Suñè, E., Crosetto, M., & Cuevas-González, M. (2017). Leveling vs. InSAR in urban underground construction monitoring: Pros and cons. Case of la sagrera railway station (Barcelona, Spain). Engineering Geology, 218, 1–11.

Socquet, A., Hollingsworth, J., Pathier, E., & Bouchon, M. (2019). Evidence of supershear during the 2018 magnitude 7.5 Palu earthquake from space geodesy. Nature Geoscience, 12, 192–199.

Strozzi, T., Klime, J., Frey, H., Cadu, R., Huggel, C., & Wegmüller, U. (2018). Remote Sensing of Environment Satellite SAR interferometry for the improved assessment of the state of activity of landslides: A case study from the Cordilleras of Peru. Remote Sensing of Environment, 217, 111–125.

Turcotte, D., & Schubert, G. (2014). Geodynamics. Cambridge University Press.

Wang, B., Shi, W., & Liu, E. (2015). Robust methods for assessing the accuracy of linear interpolated DEM. International Journal of Applied Earth Observation and Geoinformation, 34(1).

Wang, Q. J., Li, Z. W., Du, Y. N., Xie, R. A., Zhang, X. Q., Jiang, M., & Zhu, J. J. (2014). Generalized functional model of maximum and minimum detectable deformation gradient for PALSAR interferometry. Transactions of Nonferrous Metals Society of China (English Edition), 24(3), 824–832.

Weidner, U., & Förstner, W. (1995). Towards automatic building extraction from high-resolution digital elevation models. ISPRS Journal of Photogrammetry and Remote Sensing, 50(4), 38–49.

Xin, X., Liu, B., Di, K., Jia, M., & Oberst, J. (2018). High-precision coregistration of orbiter imagery and digital elevation model constrained by both geometric and photometric information. ISPRS Journal of Photogrammetry and Remote Sensing, 144, 28–37.

Zhang, Y., Zhang, Y., Zhang, Y., & Li, X. (2016). Automatic extraction of DTM from low resolution DSM by two steps semi-global filtering. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 3, 249–255.

Zuo, R., Qu, C., Shan, X., Zhang, G., & Song, X. (2016). Tectonophysics Coseismic deformation fields and a fault slip model for the Mw7.8 mainshock and Mw7.3 aftershock of the Gorkha-Nepal 2015 earthquake derived from Sentinel-1A SAR interferometry. Tectonophysics, 686, 158–169.