Research and Discover 2003 ICESat Precise Elevation Data Over the Antarctic Megadunes Tom Daigle: NASA/University of New Hampshire Research and Discover.

Slides:



Advertisements
Similar presentations
Helen Amanda Fricker Scripps Institution of Oceanography Ted Scambos National Snow and Ice Data Center Bob Bindschadler NASA/GSFC Space Flight Center Laurie.
Advertisements

ESTO Advanced Component Technology 11/17/03 Laser Sounder for Remotely Measuring Atmospheric CO 2 Concentrations GSFC CO 2 Science and Sounder.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Lecture Slides Elementary Statistics Eleventh Edition and the Triola.
Calibration Scenarios for PICASSO-CENA J. A. REAGAN, X. WANG, H. FANG University of Arizona, ECE Dept., Bldg. 104, Tucson, AZ MARY T. OSBORN SAIC,
Earth System Science Teachers of the Deaf Workshop, August 2004 S.O.A.R. High Earth Observing Satellites.
David Prado Oct Antarctic Sea Ice: John N. Rayner and David A. Howarth 1979.
SAR Altimetry in Coastal Zone: Performances, Limits, Perspectives Salvatore Dinardo Serco/ESRIN Bruno Lucas Deimos/ESRIN Jerome Benveniste ESA/ESRIN.
Evaluation of ECHAM5 General Circulation Model using ISCCP simulator Swati Gehlot & Johannes Quaas Max-Planck-Institut für Meteorologie Hamburg, Germany.
High-Resolution Maps of Outlet Glacier Surface Elevation Change from Combined Laser Altimeter and Digital Elevation Model Data (ID # ) Joanna Fredenslund.
The ICESat-2 Mission: Laser altimetry of ice, clouds and land elevation T. Markus, T. Neumann NASA Goddard Space Flight Center W. Abdalati Earth Science.
SEAT Traverse The Satellite Era Accumulation Traverse (SEAT) collected near-surface firn cores and Ultra High Frequency (UHF) Frequency Modulated.
ICESat Overview H. Jay Zwally NASA Goddard Greenbelt, Maryland Bob E. Schutz The University of Texas at Austin Center for Space Research Laser Ranging.
ReCover for REDD and sustainable forest management EU ReCover project: Remote sensing services to support REDD and sustainable forest management in Fiji.
The Lunar Reconnaissance Orbiter (LRO) is the first mission in NASA's Vision for Space Exploration, a plan to return to the moon and then to travel to.
Menglin Jin Department of Atmospheric & Oceanic Science University of Maryland, College park Observed Land Impacts on Clouds, Water Vapor, and Rainfall.
ICESat dH/dt Thinning Thickening ICESat key findings.
Airborne LIDAR The Technology Slides adapted from a talk given by Mike Renslow - Spencer B. Gross, Inc. Frank L.Scarpace Professor Environmental Remote.
Jamika Baltrop and MyAsia Reid Mentor Malcolm A. LeCompte, Ph.D.
A Multi-Sensor, Multi-Parameter Approach to Studying Sea Ice: A Case-Study with EOS Data Walt Meier 2 March 2005IGOS Cryosphere Theme Workshop.
Remote Sensing and Active Tectonics Barry Parsons and Richard Walker Michaelmas Term 2011 Lecture 4.
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,
ICESat TM 04/21/20031 MIT Activities Two main areas of activity: –Validation of atmospheric delays being computed for ICESat –Assessment of statistics.
BPS - 3rd Ed. Chapter 211 Inference for Regression.
Spatially Complete Global Surface Albedos Derived from MODIS Data
Mapping Forest Canopy Height with MISR We previously demonstrated a capability to obtain physically meaningful canopy structural parameters using data.
Validation of the Antarctic Snow Accumulation and Ice Discharge Basal Stress Boundary of the Southeastern Region of the Ross Ice Shelf, Antarctica.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Center for Satellite Applications.
What is a map? A Map is a two or three-dimensional model or representation of the Earth’s surface. 2-Dimensional map.
Active Microwave and LIDAR. Three models for remote sensing 1. Passive-Reflective: Sensors that rely on EM energy emitted by the sun to illuminate the.
An In-depth Look at ICESat and GLAS By: Vishana Ramdeen.
Summer Institute in Earth Sciences 2009 Comparison of GEOS-5 Model to MPLNET Aerosol Data Bryon J. Baumstarck Departments of Physics, Computer Science,
June 19, 2007 GRIDDED MOS STARTS WITH POINT (STATION) MOS STARTS WITH POINT (STATION) MOS –Essentially the same MOS that is in text bulletins –Number and.
TYPES OF STATISTICAL METHODS USED IN PSYCHOLOGY Statistics.
Thoughts on OIB Science Team KCJ. Acquisition Strategies OIB developed 3, basic acquisition strategies February 2011 I. Establish once the bedrock topography.
Appraisal and Its Application to Counseling COUN 550 Saint Joseph College For Class # 3 Copyright © 2005 by R. Halstead. All rights reserved.
CS332 Visual Processing Department of Computer Science Wellesley College Binocular Stereo Vision Region-based stereo matching algorithms Properties of.
RASTERTIN. What is LiDAR? LiDAR = Light Detection And Ranging Active form of remote sensing measuring distance to target surfaces using narrow beams of.
Spaceborne 3D Imaging Lidar John J. Degnan Geoscience Technology Office, Code Code 900 Instrument and Mission Initiative Review March 13, 2002.
Using instrumented aircraft to bridge the observational gap between ICESat and ICESat-2.
InSAR and LIDAR Lecture 8 Oct 13, 2004.
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,
A bestiary of lidar errors The following images illustrate some of the defects that may be found in lidar-derived bare-earth models. The images also illustrate.
Survey – extra credits (1.5pt)! Study investigating general patterns of college students’ understanding of astronomical topics There will be 3~4 surveys.
J. Lapazaran A. Martín-Español J. Otero F. Navarro International Symposium on Radioglaciology 9-13 September 2013, Lawrence, Kansas, USA On the errors.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March Arctic Aircraft Altimeter (AAA) Experiment Envisat and ICESat underflights.
Comparison of OMI NO 2 with Ground-based Direct Sun Measurements at NASA GSFC and JPL Table Mountain during Summer 2007 George H. Mount & Elena Spinei.
Geoscience Laser Altimeter System Aerosol and Cloud Observations by the GLAS Polar Orbiting Lidar Instrument NASA - Goddard Space Flight Center Launched.
LWG, Destin (Fl) 27/1/2009 Observation representativeness error ECMWF model spectra Application to ADM sampling mode and Joint-OSSE.
Validation of the basal stress boundary utilizing Satellite Imagery along the George VI Ice Shelf, Antarctica.
An Examination of the Relation between Burn Severity and Forest Height Change in the Taylor Complex Fire using LIDAR data from ICESat/GLAS Andrew Maher.
Mapping Greenland Using NASA’s Full- Waveform, Medium/High-Altitude, LVIS Lidar System: Potential 2009 Coverage and Expected Performance Michelle Hofton.
How does InSAR work? Gareth Funning University of California, Riverside.
Don P. Chambers Center for Space Research The University of Texas at Austin Wide-Swath Ocean Sciences and Hydrology Meeting 31 October 2006 Orbit Selection.
Global Ice Coverage Claire L. Parkinson NASA Goddard Space Flight Center Presentation to the Earth Ambassador program, meeting at NASA Goddard Space Flight.
Code Cryospheric Sciences Branch Christopher A. Shuman and Vijay P. Suchdeo (with help from many others, thank you!) Ice Sheet Elevations from ICESat.
AIRS Land Surface Temperature and Emissivity Validation Bob Knuteson Hank Revercomb, Dave Tobin, Ken Vinson, Chia Lee University of Wisconsin-Madison Space.
BPS - 5th Ed. Chapter 231 Inference for Regression.
Integrating LiDAR Intensity and Elevation Data for Terrain Characterization in a Forested Area Cheng Wang and Nancy F. Glenn IEEE GEOSCIENCE AND REMOTE.
Surface Characterization 4th Annual Workshop on Hyperspectral Meteorological Science of UW MURI And Beyond Donovan Steutel Paul G. Lucey University of.
PADMA ALEKHYA V V L, SURAJ REDDY R, RAJASHEKAR G & JHA C S
MATH-138 Elementary Statistics
Clouds, shear and the simulation of hybrid wind lidar
N. Bousserez, R. V. Martin, L. N. Lamsal, J. Mao, R. Cohen, and B. R
Topographical Maps.
M7Plus Unit-10: Statistics CMAPP Days (Compacted Days 1 – 5 )
ICESat: Ice, Cloud and Land Elevation Satellite
LiDAR Range (R) recorded as R = c * t/2 Unaffected by clouds above
NanoBPM Status and Multibunch Mark Slater, Cambridge University
An T Nguyen (MIT) Thomas A Herring (MIT)
Presentation transcript:

Research and Discover 2003 ICESat Precise Elevation Data Over the Antarctic Megadunes Tom Daigle: NASA/University of New Hampshire Research and Discover Internship Christopher Shuman: NASA GSFC Mark Fahnestock: University of New Hampshire

Research and Discover 2003 Background Graduated Union College June 2003 BS in biology and geology Summer 2002 at UNH working with ice cores from NW Canada (R+D)

Research and Discover 2003 Summer 2003 Research and Discover Work at NASA Goddard Space Flight Center Evaluate and understand ICESat precise elevation data. Established topographic details of Antarctic Megadune study area. Ice, Cloud, and land Elevation Satellite (ICESat) carrying the Geoscience Laser Altimeter System (GLAS) Launched January 12, 2003

Research and Discover 2003 The Next Few Minutes… 1. Get familiar with the dunefield 2. Talk about the exact satellite tracks that cover the dunes 3. How to interpret and assess the quality of the data. 4. Name of the game is Quality Control…where is our good data and how good is it? Image courtesy of Radarsat/NSIDC

Research and Discover 2003 What Are These Megadunes Anyway? Broad, subdued features 2-5 km wavelength 2-5 m amplitude Rough, coarse-grained upwind surface, smooth downwind surface ~ 4 km Image courtesy of Mary Albert/CRREL

Research and Discover 2003 Satellite Tracks and Cycles ICESat operating on Laser 1 in CAL/VAL mode Each track is repeated in a cycle every 8 days. Each laser (3 total) has a 40 Hz pulse rate and produces an ~70 m footprint with ~170 m separation along track. Vertical resolution: 15 cm surface, 75 m atmosphere. 8-Day repeat ground tracks over Antarctica Graphic courtesy of Matt Beckley

Research and Discover 2003 Eight Tracks Over the Dunes Eight tracks cover the dunefield study area. We have 4 to 5 cycles for each track from Feb. 20 to March 29. Must assess the quality of each track/cycle. Terra/MODIS composite image showing the exact paths of the eight tracks of interest. MODIS basemap courtesy of Mark Fahnestock Dunefield basecamp December 2002

Research and Discover 2003 Summer Objectives…Quality Control To assess the quality of elevation data from all cycles of each track we will Check visually the elevation profiles and categorize them as good, okay, or poor. 2. Identify crossover points and their elevation differences. 3. Examined waveforms and gain settings at crossover points using ICESat Science Investigator-led Processing System (I-SIPS) and Visualizer software to better understand how the elevation measurement was made. okay 4. Categorize crossover points as good, okay, poor or bad based on waveforms and compare their elevation offsets.

Research and Discover 2003 Track 61 Profile Cycle 2 of Track 61 is good.

Research and Discover 2003 Cycle 3 of Track 61 is good in places Track 61 Profile

Research and Discover 2003 Cycle 4 of Track 61 is good. Track 61 Profile

Research and Discover 2003 Cycle 5 of Track 61 is poor. Track 61 Profile

Research and Discover 2003 Crossover Points Tracks 11 and 61 over the entire study area. Zoom in on the exact crossover to resolve each cycle. 6111

Research and Discover 2003 Crossover Points 20 unique crossover points for track 11 vs track 61. Assume the two crossover points describe a single, unique elevation despite 10 to 200 meter true horizontal offsets. Safe assumption since the Megadunes are extremely low-slope features (observe ~25 cm elevation offset over 500 m distance). ~2 km 170 m offset at 6_11 vs 5_61

Research and Discover 2003 Crossover Tables Crossover points for all tracks are summarized in a table with their corresponding elevation offset. Yellow cells are missing an elevation measure at the exact crossover (nearest point is used). Orange cells have no elevation measure at or near the crossover probably due to atmospheric phenomena. These cells are not included in the waveform analysis since they would introduce a bias.

Research and Discover 2003 Waveforms and Quality The laser return-pulse to the satellite is recorded and fit with a gaussian curve to describe elevation. The gain setting is a proxy for the strength of the return pulse, and how gain settings are selected is an issue being investigated by the ICESat science team. The goal is to resolve elevation data from pulses where the gain setting is too high or too low making waveforms saturated or undersaturated (13-25 is best). okayLooked at crossover point waveforms and gains and classified them as good, okay, poor, or bad based on shape and return gain From I-SIPS and Visualizer.

Research and Discover 2003 Refined Crossover Quality Index Table of all 306 crossover points and their quality based on waveform properties (color code), and early visual analysis (text). The technical waveform analysis of the preliminary visual categories reveals some tracks that look good are in fact impacted by saturation and consequent elevation uncertainty.

Research and Discover 2003 Crossover Quality Histograms Good crossover pairs have the most narrow range in offset, and the smallest average offsets. OkayOkay, poor, and bad crossover pairs have a wider range of offsets and higher average differences.

Research and Discover 2003 Average Offset Take absolute value of the offset and get the average deviation from zero. This gives the absolute magnitude of offset and negative offsets cannot be counteracted by positive offsets.

Research and Discover 2003 Conclusions Pointing of GLAS laser 1was only accurate to about plus/minus 800 m from theoretical track. Tracks subject to atmospheric phenomenon have a few meters of scatter around the probable surface. Clouds and/or blowing snow are contributing to bad gains and scatter around the surface. For saturated pulses, better processing of original data may provide more accurate and consistent results. Despite some of these errors we still have a better measure of the Antarctic Ice Sheet elevation than ever before.

Research and Discover 2003 Future Work on This Project Map actual laser shot-points on MODIS basemap to notice changes in upwind and downwind faces of the dunes. Document any correlations between slope and dune wavelength. Establish a grid of high quality elevation data at crossover and along track locations for a high resolution DEM.

Research and Discover 2003 Thank You Chris Shuman Vijay Suchedo Mark Fahnestock UNH/NASA Research and Discover