Improvement of Digital Elevation Model of Greenland Ice Sheet by Using ICESat Satellite Laser Altimetry Data Bea Csatho, Taehun Yoon and Yushin Ahn Byrd.

Slides:



Advertisements
Similar presentations
Ice Sheets GNSS (GPS, GLONASS, Galileo, Beidou, QZSS) Matt King.
Advertisements

IV: Ice velocity – costal regions + select areas (phase 1), all ice sheet (ph. 2) SEC: Surface elevation changes, ERS/Envisat/CryoSat, GLL: Grounding.
Present-Day Sea Level Change Present-Day Sea Level Change Assessment and Key Uncertainties Anny Cazenave Anny Cazenave LEGOS, Toulouse.
High-Resolution Maps of Outlet Glacier Surface Elevation Change from Combined Laser Altimeter and Digital Elevation Model Data (ID # ) Joanna Fredenslund.
GlobGlacier WP4 progress at SGEU Eero Rinne, University of Edinburgh School of GeoSciences Edinburgh Earth Observatory.
SEAT Traverse The Satellite Era Accumulation Traverse (SEAT) collected near-surface firn cores and Ultra High Frequency (UHF) Frequency Modulated.
Introduction to LIDAR Mapping Technology
ReCover for REDD and sustainable forest management EU ReCover project: Remote sensing services to support REDD and sustainable forest management in Fiji.
Airborne Laser Scanning: Remote Sensing with LiDAR.
NSIDC IceBridge Value Added Data Products Ted Scambos, Bruce Raup, Susan Rogers, Mary-Jo Brodzik.
Digital Elevation Models GLY 560: GIS and Remote Sensing for Earth Scientists Class Home Page:
BIIR Cost Preview Preparatory Materials. BIIR Can Help Answer These Science Questions Refined science questions derived in part from the St. Petersburg.
Summary: Scientific Achievement, Applications and Future Requirements Zueheir Altamimi Steve Klosko Richard Gross Aleksander Brzezinski.
Global Ice Sheet Mapping Orbiter Understand the polar ice sheets sufficiently to predict their response to global climate change and their contribution.
Ventures Proposal Science Objectives and Requirements.
ICESat dH/dt Thinning Thickening ICESat key findings.
An Evaluation of Interpolation Methods for MOLA Data Oleg Abramov and Alfred McEwen: Department of Planetary Sciences, University of Arizona INTRODUCTION.
Assessment of OIB 2009 Data over Pine Island and Thwaites Glaciers K. Jezek OIB Science Team Meeting.
Recent results from GRACE in Greenland and Antarctica Isabella Velicogna* and John Wahr** * ESS, University of California Irvine, Irvine CA ** Dept Of.
Finding An Ideal Ski Resort Location GIS Group Project: Meredith Faust Dana French Kalyna Malm.
DISTRIBUTION OF LIDAR DATA VIA THE INTERNET Michael Hearne and Andrew Meredith Technology Planning and Management Corporation Coastal Remote Sensing Program.
Digital Terrain Models by M. Varshosaz
Don P. Chambers Center for Space Research The University of Texas at Austin Understanding Sea-Level Rise and Variability 6-9 June, 2006 Paris, France The.
NASA/GSFC code (Dr. Edward Kim) the University of Melbourne (Dr. Jeff Walker, project PI & formerly code 614.3), and the University of Newcastle.
Remote Sensing and Active Tectonics Barry Parsons and Richard Walker Michaelmas Term 2011 Lecture 4.
earthobs.nr.no Land cover classification of cloud- and snow-contaminated multi-temporal high-resolution satellite images Arnt-Børre Salberg and.
Sea-ice freeboard heights in the Arctic Ocean from ICESat and airborne laser H. Skourup, R. Forsberg, S. M. Hvidegaard, and K. Keller, Department of Geodesy,
Raster Data Chapter 7. Introduction  Vector – discrete  Raster – continuous  Continuous –precipitation –elevation –soil erosion  Regular grid cell.
Monitoring Earths ice sheets from space Andrew Shepherd School of Geosciences, Edinburgh.
1 Assessment of Geoid Models off Western Australia Using In-Situ Measurements X. Deng School of Engineering, The University of Newcastle, Australia R.
Malcolm McMillan1, Peter Nienow1, Andrew Shepherd1 & Toby Benham2
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Center for Satellite Applications.
Raster Data Model.
1 20 th century sea-Level change. The Earth’s ice is melting, sea level has increased ~3 inches since 1960 ~1 inch since signs of accelerating melting.
Ice Sheet Mass Changes and Contribution to Sea Level Rise  Greenland and Antarctic ice sheets were close to balance 1992 to  Net only 1% of annual.
Cambiamento attuale: Ghiaccio e mare CLIMATOLOGIA Prof. Carlo Bisci.
©2010 Elsevier, Inc. 1 Chapter 14 Cuffey & Paterson.
Digital Terrain Models by M. Varshosaz 1 DTM tasks: generation  Buy global or national data set  Collect data.
Researcher requires geographical subset due to disk space restriction. Goes directly to NSIDC site hoping for “one stop shopping” at
Using instrumented aircraft to bridge the observational gap between ICESat and ICESat-2.
USGS DIGITAL TERRAIN MODELS AND MOSAICS FOR LMMP M. R. Rosiek, E. M. Lee, E. T. Howington-Kraus, R. L. Fergason, L. A. Weller, D. M. Galuszka, B. L. Redding,
Polar Ice Sheets and Ice Shelves: Mass Balance, Uncertainties, and Potential Improvements Robert H Thomas…etc.
University of Kansas S. Gogineni, P. Kanagaratnam, R. Parthasarathy, V. Ramasami & D. Braaten The University of Kansas Wideband Radars for Mapping of Near.
Quadrilateral Data Structure Geodetic latitude and longitude on GRS80/WGS 84 ellipsoid(NAD 83) Grid cell resolution constant N-S but progressively finer.
PARCA at NSIDC DAAC Where we are so far and where we might go Mark Parsons 25 April 2001.
Latitudinal Trend of Roughness and Circumpolar Mantles on Mars M. A. Kreslavsky J. W. Head III Brown University.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March Arctic Aircraft Altimeter (AAA) Experiment Envisat and ICESat underflights.
Tele-Conference with Lincoln Labs: Icing Hazard Level National Center for Atmospheric Research 29 April 2010.
GISMO Simulation Status Objective Radar and geometry parameters Airborne platform upgrade Surface and base DEMs Ice mass reflection and refraction modeling.
Data Activities at NSIDC DAAC September April 2001 Mark Parsons 25 April 2001.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Closing the Global Sea Level.
Sea ice thickness from airborne laser scanning Sine M. Hvidegaard, Rene Forsberg, Henriette Skourup, and others.
Global Ice Coverage Claire L. Parkinson NASA Goddard Space Flight Center Presentation to the Earth Ambassador program, meeting at NASA Goddard Space Flight.
SeaWiFS captures algal blooms off Strait of Juan de Fuca Blooms of phytoplankton color the water along the coast to the north and south of the Strait of.
Code Cryospheric Sciences Branch Christopher A. Shuman and Vijay P. Suchdeo (with help from many others, thank you!) Ice Sheet Elevations from ICESat.
U.S. Department of the Interior U.S. Geological Survey Afghanistan Natural Resource Assessment and Reconstruction Project Geospatial Infrastructure Development:
Date of download: 6/24/2016 Copyright © 2016 SPIE. All rights reserved. Study area of Colorado Plateau with black dots for SNOTEL locations and digital.
Integrating LiDAR Intensity and Elevation Data for Terrain Characterization in a Forested Area Cheng Wang and Nancy F. Glenn IEEE GEOSCIENCE AND REMOTE.
ICE CAP SURFACE ELEVATION CHANGE PRODUCTS FROM ENVISAT RA2 AND ICESAT GLAS ALTIMETER DATA Eero Rinne School of GeoSciences, University of Edinburgh
Lab 2-4 Surveying Bear Lake Shorelines
DIGITAL ELEVATION MODEL (DEM), ITS DERIVATIVES & APPLICATIONS
Terrain modelling: the basics
MODEL WIND FIELD COMPARE WITH HRD WIND FIELD
Table 1. Data for coastal stations in Greenland.
An T Nguyen (MIT) Thomas A Herring (MIT)
Spatial interpolation
WP 2.3 Change in mass balance of the Green-
5 Number Summaries.
R. Gutierrez, J. Gibeaut, R. Smyth, T. Hepner, J. Andrews, J. Bellian
Fig. 3 High-tide flood extent at water levels of 1. 73, 2. 03, 2
Presentation transcript:

Improvement of Digital Elevation Model of Greenland Ice Sheet by Using ICESat Satellite Laser Altimetry Data Bea Csatho, Taehun Yoon and Yushin Ahn Byrd Polar Research Center, OSU

ICESat Data to Improve Greenland DEMs2 Current Status and Objectives Available DEMs of the Greenland Ice Sheet are based on satellite radar altimetry data (e.g., Bamber and Ekholm, 2001), or on the combination of radar altimetry data with AVHRR imagery by using photoclinometry techniques to fill the regions between radar orbits (Scambos and Harran). Here out referred to as ‘available DEM’ Elevation errors of these DEMs range from a few meters at the middle of the ice sheet (>2000 m) to m in marginal regions. Our objective is to improve the accuracy of these ‘Available DEMs’ by using ICESat data. The following example is shown for the boxed region, however a whole ice sheet DEM is currently being developed.

ICESat Data to Improve Greenland DEMs3 Input Data  3/20/03- 6/23/05 ICESat satellite laser altimetry observations (L1, L2a-c, L3a-c) ( L3d and L3e should be added )  Airborne Topographic Mapper (ATM) laser altimetry data from (Krabill, NASA WFF)  ‘Available DEMs’ from Bamber et al. (2001) and Scambos and Harran  Landcover map of Greenland from KMS Categories: ice sheet, local ice caps, land and ocean

ICESat Data to Improve Greenland DEMs4 Processing Steps Step 1: Detection and removal of outliers from the ICESat and ATM data sets. Only points on ice sheet and local ice caps are used ICESat outliers: elevations are compared with median elevation of 2 X 2 km grid cells. Points with elevation difference > 40 m from the median are removed. ATM outliers are removed by using the same technique. In addition, all observations in cells with less than 2 data points are removed. Step 2: Residuals between the ICESat data and the ‘Available DEM' are computed at each ICESat point over the ice sheet and local ice caps. Residuals are set zero at grid posts over land and ocean Step 3: Residuals are interpolated into a regular grid by using minimum curvature interpolation.

ICESat Data to Improve Greenland DEMs5 Processing Steps cont. Step 4: Improved DEM = ‘Available DEM’ + interpolated residual Step 5: The accuracy of the improved DEM is assessed by using the ICESS data set (compressed ATM airborne laser scanning data derived by plane fitting to original laser point swaths)

ICESat Data to Improve Greenland DEMs6 Distribution of Data Points ICESat (red) and ATM (blue)

ICESat Data to Improve Greenland DEMs7 ‘Available DEM’ (Upper Panel) + Interpolated ICESat Residual (Lower) = Merged DEM using ICESat Data and Available DEM

ICESat Data to Improve Greenland DEMs8 Available DEM Improved DEM Close Up Comparison of DEM’s

ICESat Data to Improve Greenland DEMs9 ATM elevations - photoclinometry DEM Dh= m +/ m ATM elevations – new DEM Dh= m +/ m Error Assessment: ATM – DEM Elevations Error Assessment: ATM – DEM Elevations

ICESat Data to Improve Greenland DEMs10 Thank you NEW “AND IMPROVED” SHADED RELIEF MAP