UJI KETELITIAN DTM ALOS PALSAR TERHADAP PENGUKURAN KOMBINASI DGNSS-ALTIMETER
Abstract
Height model is model include the information of height data and its coordinate in earth surface. Height model is one of the geological parameters that are useful for a variety of applications of survey and mapping. Height model in the form of Digital Surface Model, Digital Elevation Model, Digital Terrain Model, Digital Terrain Elevation Digital, Geoid, and others. Height model can be made with data, aerial photographs, satellite imagery, and Interferometry Synthetic Aperture Radar. This research aims to test the vertical accuracy of ALOS PALSAR against the combination measurement of Differential Global Navigation Satellite System-Altimeter. Digital Surface Model is made from images of ALOS PALSAR with interferometry Synthetic Aperture Radar methods. Digital Elevation Model retrieved after height error correction and terrain correction of Digital Surface Model. Digital Terrain Model obtained after the integration of river features and bathymetry in Digital Elevation Model ALOS PALSAR.Then do the vertical accuracy test of ALOS PALSAR againts the combination measurement of Differential Global Navigation Satellite systems-Altimeter.Differential Global Navigation Satellite systems received the data from the GPS, Beidou, GLONASS, SBAS, MSAS, Gagan, and QZSS satellite and uses period of 14 days before the measurement with the time in measurement. During the measurement for processing the position data and height value. Differential Global Navigation Satellite systems was connected with server of internet provider. Region of vertical accuracy test is in Merauke regency in 2016. The tolerance standard of this vertical accuracy test refers to National Standard for Spatial Data Accuracy in 1.96 σ (95%) tolerance. From the two vertical accuracy test, height difference test and tranverse profile test, Digital Terrain Model ALOS PALSAR have fulfilled tolerance in 4,996e- 16 (~0) and 80,791 cm so it can be used for various applications of survey and mapping for 1:10.000 scale.
ABSTRAK
Model tinggi adalah model yang meliputi informasi data tinggi dan koordinatnya di permukaan bumi. Model tinggi merupakan salah satu parameter geologi yang bermanfaat untuk berbagai aplikasi survei dan pemetaan. Model tinggi berupa model permukaan digital, model elevasi digital, model terrain digital, model terrain elevasi digital, Geoid, dan lain-lain. Model tinggi dapat dibuat dengan data lapangan, foto udara, interferometri radar sintetis, dan citra satelit. Penelitian ini bertujuan untuk melakukan uji akurasi vertikal model terrain digital ALOS PALSAR terhadap pengukuran kombinasi diferensial sistem satelit navigasi global-Altimeter. Model permukaan digital dibuat dari citra ALOS PALSAR dengan metode interferometri radar sintetis. Model elevasi digital diperoleh setelah dilakukan koreksi kesalahan tinggi dan koreksi terrain model permukaan digital. Model terrain digital diperoleh setelah dilakukan integrasi fitur sungai dan batimetri terhadap model permukaan digital. Model terrain digital ALOS PALSAR dilakukan uji akurasi vertikal dengan pengukuran kombinasi diferensial sistem satelit navigasi global-Altimeter. Diferensial sistem satelit navigasi global menerima data dari satelit GPS, Glonass, Beidou, Gagan, MSAS, SBAS, dan QZSS dan menggunakan periode waktu 14 hari sebelum pengukuran dengan waktu saat pengukuran. Selama pengukuran,untuk mengolah data posisi dan ketinggian. Diferensial sistem satelit navigasi global dikoneksikan dengan server melalui jaringan internet selular. Lokasi uji akurasi vertikal dilakukan di Kabupaten Merauke pada tahun 2016. Standar toleransi uji akurasi vertikal ini mengacu kepada toleransi standar nasional untuk akurasi data spasial sebesar 1,96σ (95 %). Dari dua jenis uji akurasi vertikal, yakni uji beda tinggi dan uji profil melintang, model terrain digital ALOS PALSAR telah memenuhi toleransi sebesar 4,996e-16 (~0)dan 80,791 cm sehinggadapat digunakan untuk berbagai aplikasi survei dan pemetaan skala 1:10.000.
Keywords
Full Text:
PDFReferences
Adam, N., Rodriguez Gonzalez, F., Parizzi, A., & Liebhart, W., (2011). Wide Area Persistent Scatterer Interferometry. IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2011) (pp. 1481–1484) (Vancouver, BC).
Berardino, P., Fornaro, G., Lanari, R., & Sansosti, E., (2002). A New Algorithm For Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40, 2375–2383.
Cigna, F, Bateson, L. B., Jordan, J.,& Dashwood, C., (2014). Simulating SAR Geometric Distortions and Predicting Persistent Scatterer Densities for ERS- 1/2 and ENVISAT C-band SAR and InSAR Applications: Nationwide Feasibility Assessment to Monitor the
Landmass of Great Britain with SAR Imagery. Remote Sensing of Environment Volume 152. Elsevier.441-466.
Crosetto, M., Monserrat, O., Iglesias, R., & Crippa, B., (2010). Persistent Scatterer Interferometry: Potential,
Limits and Initial C- and X-Band Comparison. Photogrammetric Engineering and Remote Sensing, 76, 1061–1069.
ESA, (2007). InSAR Principles: Guidelines for SAR Interferometry Processing and Interpretation. ESA. Belanda.
Freeden, W., Nashed, M.Z., & Sonar, T., (2010). Handbook of Geomathemathics. Springer. ISBN: 9783642015465
Gillani, C., & Wolf, (2006). Adjustment Computation: Spatial Data Analysis. John Wiley & Sons, Inc., Hoboken, New Jersey. Amerika Serikat.
Heiskanen, W. A., & Moritz, H.,(1967). Physical Geodesy. W. H. Freeman and Company. San Fransisco and London.
JAXA, (2006a). Annual Report 2005, EORC Bulletin, No. 9, March 2006. Tokyo. Jepang.
JAXA, (2006b). The 2nd ALOS
Research Announcement: Calibration and Validation,Utilization Research, and Scientific Research, Earth Observation Research Center Japan Aerospace Exploration Agency. Jepang.
JAXA, (2016).PALSAR Phased Array Type L-band Synthetic Aperture Radar, URL: www.eorc.jaxa.jp/ ALOS/en/about/palsar.htm.diakses 23 Oktober 2016.
Julzarika, A., & Susanto, (2009). Pemanfaatan Interferometic Synthetic Aperture Radar (InSAR) untuk Pemodelan 3D (DSM, DEM, dan DTM). Majalah Sains dan Teknologi Dirgantara, 4, 154-159.
Julzarika, A., (2009). Differential of Digital Surface Model (DSM) into Digital Elevation Model (DEM) of the ALOS PALSAR. Journal of Teknik University of Diponegoro volume 30 nomor 1. Semarang. Indonesia.
Julzarika, A., (2011a). Teknik Koreksi
Bull Eye’s. GeoSARNas. Bogor.
Julzarika, A., (2011b). Kajian Penghitungan Volume Hutan Menggunakan Model 3D dari Data Radar Berbeda Band dan Koreksi Terrain Model 3D dari Data Radar Satu Band. Seminar GeoSARNas 2011. Bogor.
Julzarika, A., (2013). Geological Structure
Detection Digitally Using Synthetic Aperture Radar (SAR) Data. Asia Conference of Remote Sensing. Bali. Indonesia.
Julzarika, A., (2015). Integrasi Model Tinggi ALOS PALSAR, X SAR, SRTM,
dan ASTER GDEM. Teknik Geodesi Geomatika. Universitas Gadjah Mada. Yogyakarta.
Li, Z., Zhu, Q., & Gold, C., (2005). Digital Terrain Modeling Principles and Methodology. CRC Press. Florida. USA.
Mora, B., Wulder, M.A., Hobart, G.W., White, J.C., Bater, C.W., Gougeon, F.A., Varhola, A., & Coops, N.C., (2013a). Forest Inventory Stand Height Estimates from Very High Spatial Resolution Satellite Imagery Calibrated with Lidar Plots. Int. J. Remote Sens. 2013, 34, 4406–4424.
Mora, B., Wulder, M.A., White, J.C., & Hobart, G., (2013b). Modeling Stand Height, Volume, and Biomass from Very High Spatial Resolution Satellite Imagery and Samples of Airborne LiDAR. Remote Sens. 2013, 5, 2308–
Notti, D., Meisina, C., Zucca, F., & Colombo, A.,(2011). Models to Predict Persistent Scatterers Data Distribution and their Capacity to Register Movement Along the Slope. Fringe 2011 Workshop, 19–23 September
Frascati, Italy:ESA/ESRIN. NSSDA, 2014. Accuracy Standard for
Digital Geospatial Data. ASPRS. Amerika Serikat.
Petrie, G.,& Kennie T., 1987. An Introduction to Terrain Modeling: Applications and Terminology. Universitas Glasgow, Skotlandia.
Riddick, S. N., Schmidt, D. A., & Deligne,
N. I., (2012). An Analysis of Terrain Properties and the Location of Surface Scatterers from Persistent Scatterer Interferometry. ISPRS Journal of Photogrammetry and Remote Sensing, 73, 50–57.
Sefercik, U., & Jacobsen, K., (2006). Analysis of SRTM Height Models. Workshop SRTM Berlin. Jerman.
Sideris, (2008). Geoid Determination by FFT Techniques. Como.
Vanicek, P.,& Krakiwsky, E., (1986).
Geodesy, the Concepts. North-
Holland, Amsterdam, NY, Oxford,Tokyo.
Vastaranta, M., Holopainen, M., Karjalainen, M., Kankare, V., Hyyppa, J., Kaasalainen, S., & Hyyppa, H., (2012). SAR Radargrammetry and Scanning LiDAR in Predicting Forest Canopy Height. In Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany, 22–27 July 2012; pp.6515–6518.
Vastaranta, M., Holopainen, M., Karjalainen, M., Kankare, V., Hyyppa,
J., & Kaasalainen, S., (2014). TerraSAR-X Stereo Radargrammetry and Airborne Scanning LiDAR Height Metrics in Imputation of Forest Above Ground Biomass and Stem Volume. IEEE Trans. Geosci. Remote Sens. 2014, 52, 1197– 1204.
Ziebart, M.K., Iliffe, J.C., Forsberg, R., & Strykowski, G., (2008). Convergence of the UK OSGM05 GRACE-Based Geoidand the UK Fundamental Benchmark Network. J. Geophys. Res., 113, B12401, doi:10.1029/2007JB00495
Refbacks
- There are currently no refbacks.
