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      KCI등재 SCOPUS

      Land Surface Dynamics and Underwater Topography from the Latest DTM Extraction to Measure the Antarctica Ice Sheet Thickness

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      https://www.riss.kr/link?id=A109022245

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      The Antarctica ice sheet thickness is one of the important information to know the dynamics of changes in the Earth's environment. Geospatial data of the ice sheet surface, land surface and underwater topography, and vertical deformation can be used for ice sheet thickness measurement and calculation. They can be extracted from the latest DTM. The latest DTM is one of the methods and products to extract up-to-date and detailed topography based on the dynamics of the vertical deformation period. This study aims to measure the Antarctica ice sheet thickness based on land surface dynamics and underwater topography from the latest DTM extraction. The vertical accuracy of the DTM, DSM, and vertical deformation uses a 95 % (1.96σ) confidence level. The ice thickness is divided into three types of ice layers according to the reference field: ice thickness above land, ice thickness (above the sea), and ice thickness (underwater). Ice thickness above land has a volume (3,700,299.5 km3), an area (6,767,772 km2), and a total length perimeter (114,569 km). Ice thickness (above the sea) has a volume (28,103,427.8 km3), an area (13,438,789 km2), and a total perimeter length (27,199 km). Ice thickness (underwater) has a volume (1,793,778.6 km3), an area (3,223,036 km2), and a total length perimeter (46,556 km). Antarctica's ice sheet thickness results can be used for various thematic applications of the dynamics of the Earth's environment.
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      The Antarctica ice sheet thickness is one of the important information to know the dynamics of changes in the Earth's environment. Geospatial data of the ice sheet surface, land surface and underwater topography, and vertical deformation can be used f...

      The Antarctica ice sheet thickness is one of the important information to know the dynamics of changes in the Earth's environment. Geospatial data of the ice sheet surface, land surface and underwater topography, and vertical deformation can be used for ice sheet thickness measurement and calculation. They can be extracted from the latest DTM. The latest DTM is one of the methods and products to extract up-to-date and detailed topography based on the dynamics of the vertical deformation period. This study aims to measure the Antarctica ice sheet thickness based on land surface dynamics and underwater topography from the latest DTM extraction. The vertical accuracy of the DTM, DSM, and vertical deformation uses a 95 % (1.96σ) confidence level. The ice thickness is divided into three types of ice layers according to the reference field: ice thickness above land, ice thickness (above the sea), and ice thickness (underwater). Ice thickness above land has a volume (3,700,299.5 km3), an area (6,767,772 km2), and a total length perimeter (114,569 km). Ice thickness (above the sea) has a volume (28,103,427.8 km3), an area (13,438,789 km2), and a total perimeter length (27,199 km). Ice thickness (underwater) has a volume (1,793,778.6 km3), an area (3,223,036 km2), and a total length perimeter (46,556 km). Antarctica's ice sheet thickness results can be used for various thematic applications of the dynamics of the Earth's environment.

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      참고문헌 (Reference)

      1 Arana M, "What precision in the digital terrain model is required for noise mapping?" 72 (72): 522-526, 2011

      2 Bayer B, "Using advanced InSAR techniques to monitor landslide deformations induced by tunneling in the Northern Apennines, Italy" 226 : 20-32, 2017

      3 Maghsoudi Y, "Using PS-InSAR to detect surface deformation in geothermal areas of West Java in Indonesia" 64 : 386-396, 2018

      4 Znachko-Yavorskiy GA, "The topography of Antarctica" 2 (2): 1-13, 1978

      5 Ruzgiene B, "The surface modelling based on UAV Photogrammetry and qualitative estimation" 73 : 619-627, 2015

      6 Julzarika A, "The latest DTM using InSAR for dynamics detection of Semangko Fault-Indonesia" 47 (47): 118-130, 2021

      7 Dorschel B, "The international bathymetric chart of the southern ocean version 2" 9 (9): 1-13, 2022

      8 TerraColor, "TerraColor NextGen satellite" Earthstar Geographics

      9 Caro Cuenca M, "Surface deformation induced by water influx in the abandoned coal mines in Limburg, The Netherlands observed by satellite radar interferometry" 88 : 1-11, 2013

      10 ESA, "Sentinel-1: ESA’s radar observatory mission for GMES operational services (ESA SP-1322/1, March 2012)" European Space Agency

      1 Arana M, "What precision in the digital terrain model is required for noise mapping?" 72 (72): 522-526, 2011

      2 Bayer B, "Using advanced InSAR techniques to monitor landslide deformations induced by tunneling in the Northern Apennines, Italy" 226 : 20-32, 2017

      3 Maghsoudi Y, "Using PS-InSAR to detect surface deformation in geothermal areas of West Java in Indonesia" 64 : 386-396, 2018

      4 Znachko-Yavorskiy GA, "The topography of Antarctica" 2 (2): 1-13, 1978

      5 Ruzgiene B, "The surface modelling based on UAV Photogrammetry and qualitative estimation" 73 : 619-627, 2015

      6 Julzarika A, "The latest DTM using InSAR for dynamics detection of Semangko Fault-Indonesia" 47 (47): 118-130, 2021

      7 Dorschel B, "The international bathymetric chart of the southern ocean version 2" 9 (9): 1-13, 2022

      8 TerraColor, "TerraColor NextGen satellite" Earthstar Geographics

      9 Caro Cuenca M, "Surface deformation induced by water influx in the abandoned coal mines in Limburg, The Netherlands observed by satellite radar interferometry" 88 : 1-11, 2013

      10 ESA, "Sentinel-1: ESA’s radar observatory mission for GMES operational services (ESA SP-1322/1, March 2012)" European Space Agency

      11 Dias P, "Sentinel-1 InSAR data applied to surface deformation in Macaronesia(Canaries and Cape Verde)" 138 : 382-387, 2018

      12 ESA, "Sentinel-1" European Space Agency

      13 Rucci A, "Sentinel 1 SAR interferometry applications : the outlook for sub millimeter measurements" 120 : 156-163, 2012

      14 Venera J, "SAR interferometry technique for ground deformation assessment on Karazhanbas Oilfield" 100 : 1163-1167, 2016

      15 Gallant JC, "Removal of tree offsets from SRTM and other digital surface models" 275-280, 2012

      16 NASA, "Remote sensors" National Aeronautics and Space Administration

      17 Paxman GJG, "Reconstructions of Antarctic topography since the Eocene-Oligocene boundary" 535 : 109346-, 2019

      18 Hooper A, "Recent advances in SAR interferometry time series analysis for measuring crustal deformation" 514-517 : 1-13, 2012

      19 Suhadha AG, "Monitoring vertical deformations of the coastal city of Palu after earthquake 2018 Using Parallel-SBAS" 1-6, 2021

      20 Vernimmen R, "Mapping deep peat carbon stock from a LiDAR based DTM and field measurements, with application to eastern Sumatra" 15 (15): 1-18, 2020

      21 Nelson DA, "Long-term geochemical and geodynamic segmentation of the paleo-pacific margin of gondwana : insight from the Antarctic and Adjacent Sectors" 36 (36): 3229-3247, 2017

      22 Tarikhi P, "Liqui-InSAR; SAR interferometry for aquatic body" 85-90, 2012

      23 Zhang Y, "Li X(2016)Automatic Extraction of D TM from low resolution DSM by two steps semi-global filtering" 249-255, 2016

      24 Liao H, "Ionospheric correction of InSAR data for accurate ice velocity measurement at polar regions" 209 : 116-180, 2018

      25 Julzarika A, "Integration of the latest Digital Terrain Model(DTM)with Synthetic Aperture Radar(SAR)bathymetry" 8 (8): 2502-2458, 2021

      26 Julzarika A, "Indonesian DEMNAS: DSM or DTM?" 31-36, 2019

      27 NASA, "ICESat-2" National Aeronautics and Space Administration

      28 Kubla, "How accurate is the grid method for calculating earthworks cut & fill volumes?"

      29 Lancre JC, "History of Gebco. The General Bathymetric Chart of the Oceans" GITC bv 149-, 2003

      30 Xin X, "High-precision co-registration of orbiter imagery and digital elevation model constrained by both geometric and photometric information" 144 : 28-37, 2018

      31 Julzarika A, "Height model integration using ALOS PALSAR, X SAR, SRTM C, and IceSAT/GLAS" 12 (12): 107-116, 2015

      32 Liosis N, "Ground subsidence monitoring with SAR interferometry techniques in the rural area of Al Wagan, UAE" 216 : 276-288, 2018

      33 Huang MH, "Fifteen years of surface deformation in Western Taiwan : insight from SAR interferometry" 692 : 252-264, 2016

      34 Julzarika A, "Dynamics topography monitoring in peatland using the latest digital terrain model" 20 (20): 246-253, 2022

      35 Suhadha AG, "Dynamic displacement using DInSAR of Sentinel-1 in Sunda Strait" 19 (19): 4623-, 2022

      36 Li Z, "Digital terrain modeling: principles and methodology" CRC Press 323-, 2004

      37 Devanthéry N, "Deformation monitoring using persistent scatterer interferometry and Sentinel-1SAR data" 100 : 1121-1126, 2016

      38 Lemenkova P, "Dataset compilation by grass gis for thematic mapping of antarctica : topographic surface, ice thickness, subglacial bed elevation and sediment thickness" 11 (11): 67-85, 2021

      39 Caló F, "DInSAR-based detection of land subsidence and correlation with groundwater depletion in Konya plain, Turkey" 9 (9): 83-, 2017

      40 Julzarika A, "DEM classifications: opportunities and potential of its applications" 6 (6): 1897-1905, 1905

      41 Schumann GJP, "Commentary : the need for a high-accuracy, open-access global DEM" 7 : 33-, 2019

      42 Kulp SA, "CoastalDEM : a global coastal digital elevation model improved from SRTM using a neural network" 206 : 231-239, 2018

      43 Ghilani CD, "Adjustment computations: spatial data analyses" John Wiley & Sons, Inc 695-, 2018

      44 ASPRS, "Accuracy standards for digital geospatial data" The American Society for Photogrammetry and Remote Sensing

      45 Florinsky IV, "Accuracy of local topographic variables derived from digital elevation models" 12 (12): 47-61, 1998

      46 Nasir S, "Accuracy assessment of digital elevation model generated from Pleiadestri stereo-pair" 193-197, 2015

      47 Monserrat O, "A review of groundbased SAR interferometry for deformation measurement" 93 : 40-48, 2014

      48 Krauß T, "A new simplified DSM-to-DTM algorithm- dsm-to-dtm-step" 2018 : 2018070017-, 2018

      49 Baek J, "A new algorithm to find raster-based least-cost paths using cut and fill operations" 31 (31): 2234-2254, 2017

      50 Bamber JL, "A new 1 km digital elevation model of the Antarctic derived from" 3 (3): 101-111, 2009

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