Jet Propulsion Laboratory California Institute of Technology The NASA/JPL Airborne Synthetic Aperture Radar System (AIRSAR) Yunling Lou Jet Propulsion.

Slides:



Advertisements
Similar presentations
On Estimation of Soil Moisture & Snow Properties with SAR Jiancheng Shi Institute for Computational Earth System Science University of California, Santa.
Advertisements

Optical Imaging and Field Spectroscopy: CLPX 2002 and 2003 Thomas H. Painter.
Oil spill off NW coast of Spain IKONOS image Oil reaching shore.
Space experiment on the International Space Station with P-band SAR Space experiment on the International Space Station with P-band SAR B.Kutuza, A.Kalinkevitch,
Radar Remote Sensing RADAR => RA dio D etection A nd R anging.
Estimating forest structure in wetlands using multitemporal SAR by Philip A. Townsend Neal Simpson ES 5053 Final Project.
Digital Elevation Models GLY 560: GIS and Remote Sensing for Earth Scientists Class Home Page:
Radar Imaging and Its Application to Archaeology L Kemp.
What is RADAR? What is RADAR? Active detecting and ranging sensor operating in the microwave portion of the EM spectrum Active detecting and ranging sensor.
Polarimetric Radiometer and Scatterometer Measurements Simon H. Yueh Jet Propulsion Laboratory Operational SVW Requirement Workshop, Miami 7 June 2006.
Interferometric Sounder Concept for Ice Sheet Mapping Review, Simulations, Spaceborne System, Future E. Rodriguez Jet Propulsion Laboratory California.
Merging InSAR and LIDAR to Estimate Surface and Vegetation Heights EECS 826 InSAR and Applications University of Kansas Jeff S. Hall April 2 nd, 2009.
Introduction This SAR Land Applications Tutorial has three main components: Background and theory - an overview of the principles behind SAR remote sensing,
Initial Results on the Cross- Calibration of QuikSCAT and Oceansat-2 Scatterometers David G. Long Department of Electrical and Computer Engineering Brigham.
On Estimation of Surface Soil Moisture from SAR Jiancheng Shi Institute for Computational Earth System Science University of California, Santa Barbara.
Uses of Geospatial Soils & Surface Measurement Data in DWR Delta Levee Program Joel Dudas
IGARSS’11 Compact Polarimetry Potentials My-Linh Truong-Loï, Jet Propulsion Laboratory / California Institue of Technology Eric Pottier, IETR, UMR CNRS.
WMO/ITU Seminar Use of Radio Spectrum for Meteorology Earth Exploration-Satellite Service (EESS)- Active Spaceborne Remote Sensing and Operations Bryan.
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California MITSUBISHI SPACE SOFTWARE.
DOCUMENT OVERVIEW Title: Fully Polarimetric Airborne SAR and ERS SAR Observations of Snow: Implications For Selection of ENVISAT ASAR Modes Journal: International.
Radarkartering av skogsbiomassa med P-band Pol-InSAR Lars Ulander, Maciej Soja, Gustaf Sandberg, och Daniel Murdin.
GISMO Simulation Study Objective Key instrument and geometry parameters Surface and base DEMs Ice mass reflection and refraction modeling Algorithms used.
Retrieving High Precision River Stage and Slope from Space E. Rodriguez, D. Moller Jet Propulsion Laboratory California Institute of Technology.
- Microwave Remote Sensing Group IGARSS 2011, July 23-29, Vancouver, Canada 1 M. Brogioni 1, S. Pettinato 1, E. Santi 1, S. Paloscia 1, P. Pampaloni 1,
Calibration and Validation Studies for Aquarius Salinity Retrieval PI: Shannon Brown Co-Is: Shailen Desai and Anthony Scodary Jet Propulsion Laboratory,
Michigan Tech Research Institute (MTRI)  Michigan Technological University 3600 Green Court, Suite 100  Ann Arbor, MI (734) – Phone 
APPLICATIONS OF THE INTEGRAL EQUATION MODEL IN MICROWAVE REMOTE SENSING OF LAND SURFACE PARAMETERS In Honor of Prof. Adrian K. Fung Kun-Shan Chen National.
William Crosson, Ashutosh Limaye, Charles Laymon National Space Science and Technology Center Huntsville, Alabama, USA Soil Moisture Retrievals Using C-
Active Microwave Physics and Basics 1 Simon Yueh JPL, Pasadena, CA August 14, 2014.
SWOT Near Nadir Ka-band SAR Interferometry: SWOT Airborne Experiment Xiaoqing Wu, JPL, California Institute of Technology, USA Scott Hensley, JPL, California.
1 SPACE BORNE RADAR INTERFEROMETRIC MAPPING OF PRECURSORY DEFORMATIONS OF A DYKE COLLAPSE, DEAD SEA, JORDAN Closson, Abou Karaki, al-Fugha
Soil moisture estimates over Niger from satellite sensors (T. Pellarin, M. Zribi)
A Measuring Polygon with a Complex of Polarimetric, Combined Active-Passive Sensors of S-, Ku-, and Ka-band of Frequencies for Soil and Snow Remote Sensing.
Uses of Geospatial Soils & Surface Measurement Data in DWR Delta Levee Program Joel Dudas
Synthetic Aperture Radar Specular or Bragg Scatter? OC3522Summer 2001 OC Remote Sensing of the Atmosphere and Ocean - Summer 2001.
MULTI-FREQUENCY, MULTI-POLARIZATION AND ANGULAR MEASUREMENTS OF BARE SOIL, SNOW AND WATER ICE MICROWAVE REFLECTION AND EMISSION BY C-, Ku-, AND Ka-BAND,
Scaling Up Above Ground Live Biomass From Plot Data to Amazon Landscape Sassan S. Saatchi NASA/Jet Propulsion Laboratory California Institute of Technology.
Scott Hensley, Howard Zebker, Cathleen Jones, Paul Lundgren, Eric Fielding, Thierry Michel and Bruce Chapman.
On Estimation of Soil Moisture with SAR Jiancheng Shi ICESS University of California, Santa Barbara.
CCAR / University of Colorado 1 Airborne GPS Bistatic Radar in CLPX Dallas Masters University of Colorado, Boulder Valery Zavorotny NOAA ETL Stephen Katzberg.
The Ionosphere and Interferometric/Polarimetric SAR Tony Freeman Earth Science Research and Advanced Concepts Manager.
GISMO Simulation Status Objective Radar and geometry parameters Airborne platform upgrade Surface and base DEMs Ice mass reflection and refraction modeling.
Page 1 ASAR Validation Review - ESRIN – December 2002 IM and WS Mode Level 1 Product quality update F Introduction F IM Mode Optimisation F Updated.
biomass TO OBSERVE FOREST BIOMASS
0 Riparian Zone Health Project Agriculture and Agri-Food Canada Grant S. Wiseman, BS.c, MSc. World Congress of Agroforestry Nairobi, Kenya August 23-28,
Goldstone Radar Support for LCROSS Evaluation of Impact Sites Martin Slade October 16, 2006 National Aeronautics and Space Administration Jet Propulsion.
IGARSS-2011-Vancouver Temporal decorrelation analysis at P-band over tropical forest Sandrine Daniel, Pascale Dubois-Fernandez, Aurélien Arnaubec, Sébastien.
Rick Guritz IGARSS Meeting, July Rick Guritz, Don Atwood 1 Bruce Chapman, and Scott Hensley 2 1)Alaska Satellite Facility 2)NASA Jet Propulsion.
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Evaluation of the SMAP.
CLPX Workshop May 28-29, 2003 Boulder, Colorado Ground-based Radar Measurements of LSOS Snowpack Gilles CASTRES SAINT-MARTIN Kamal SARABANDI Radiation.
RADAR.  Go through intro part of LeToan.pdfhttp://earth.esa.int/landtraining07/D1LA1- LeToan.pdf.
A Concept for Spaceborne Imaging of the Base of Terrestrial Ice Sheets and Icy Bodies in the Solar System Ken Jezek, Byrd Polar Research Center E. Rodriguez,
Over 30% of Earth’s land surface has seasonal snow. On average, 60% of Northern Hemisphere has snow cover in midwinter. About 10% of Earth’s land surface.
Using SAR Intensity and Coherence to Detect A Moorland Wildfire Scar.
Integrating LiDAR Intensity and Elevation Data for Terrain Characterization in a Forested Area Cheng Wang and Nancy F. Glenn IEEE GEOSCIENCE AND REMOTE.
Layover Layover occurs when the incidence angle (  ) is smaller than the foreslope (  + ) i.e.,  <  +. i.e.,  <  +. This distortion cannot be corrected!
Spring '17 EECS Intro to Radar Systems
HSAF Soil Moisture Training
Active Microwave Remote Sensing
(2) Norut, Tromsø, Norway Improved measurement of sea surface velocity from synthetic aperture radar Morten Wergeland Hansen.
Class 12 Assessment of Classification Accuracy
Objectives Using a time series of data from radar sensors to detect and measure forest changes Combining different types of data, including: Multi polarisations.
Estimationg rice growth parameters using X-band scatterometer data
Monitoring of Rice Growth Using Polarimetric Scatterometer System
Radar backscattering measurements of paddy rice field using L, C and X-band polarimetric scatterometer ISRS 2007.
(L, C and X) and Full-polarization
M. L. Williams1 and T. L. Ainsworth2
Soil Moisture Active Passive (SMAP) Satellite
M. L. Williams1 and T. L. Ainsworth2
Introduction to SAR Imaging
Presentation transcript:

Jet Propulsion Laboratory California Institute of Technology The NASA/JPL Airborne Synthetic Aperture Radar System (AIRSAR) Yunling Lou Jet Propulsion Laboratory 4800 Oak Grove Drive Pasadena, CA 91109

Jet Propulsion Laboratory California Institute of Technology AIRSAR System Characteristics P Simultaneous three-frequency and quad-polarization system P P-band (0.68 m), L-band (0.25 m), and C-band (0.057 m) P Along-track (ATI) and cross-track (XTI) interferometry capabilities in L & C-band P Bandwidth: 20 MHz, 40 MHz, or 80 MHz (L-band only) P Look angle: typically 25 o ~ 62 o P Range swath: ~ 10 km (40 MHz bandwidth) or 15 km (20 MHz bandwidth), 5 km (80 MHz bandwidth) P Noise equivalent sigma0: -45 dB (P/L-band), -30 dB (C-band) P Platform: DC-8 at 8 km altitude

Jet Propulsion Laboratory California Institute of Technology CLPX Data Collection Plan The objectives of the AIRSAR data collection for CLPX were: P Obtain complete coverage of the three MSAs at Rabbit Ears, North Park, and Fraser in POLSAR mode to validate SWE algorithm P Generate DEM mosaics of the Rabbit Ears, North Park, and Fraser MSAs at 5 m posting P Collect AIRSAR data in different seasons in 2002 P Collect AIRSAR data in different snow conditions in March 2003

Jet Propulsion Laboratory California Institute of Technology CLPX Data Collection Summary P AIRSAR collected data at all three CLPX sites in February, March, and September of 2002 and in March of 2003 P Total number of flight lines: 187 P Total raw data volume: about 1.8 TB (935 minutes) P Total processed data volume is estimated to be about 280 GB

Jet Propulsion Laboratory California Institute of Technology Example POLSAR Imagery over Fraser, Colorado P/L/C-band overlay of Fraser270-1, collected on 27 Feb, 2002

Jet Propulsion Laboratory California Institute of Technology Example TOPSAR DEM over Rabbit Ears, Colorado C-band DEM of Rabbit Ears collected on 13 Feb, 2002

Jet Propulsion Laboratory California Institute of Technology CLPX Data Processing Status P We have processed about 40 flight lines’ of data to date P We are requesting additional processing funding to speed up the processor throughput P We are requesting additional funding to develop software to generate geo-referenced radar data products in a standard GIS format and to generate mosaics of all three MSA sites.

Jet Propulsion Laboratory California Institute of Technology AIRSAR Data Access P Survey imagery of all the CLPX flight lines are available on AIRSAR’s website P JPEG files of all processed imagery are available on AIRSAR’s website P Request for duplicates of precision data products may be submitted to AIRSAR’s website after the one-year embargo period expires P AIRSAR’s website:

Jet Propulsion Laboratory California Institute of Technology Summary F Soil moisture measurement (POLSAR) F Surface roughness in sparsely vegetated area (POLSAR) F Biomass measurement of forested area (POLSAR) F Snow cover and snow wetness classification (frequency diversity and TOPSAR data) F Canopy (type and freezing) classification F Topography measurement (TOPSAR) F Canopy height measurement (TOPSAR) AIRSAR data can contribute to the cold land processes experiment in the following area: Note: TOPSAR data are used to remove terrain dependence in the POLSAR data

Jet Propulsion Laboratory California Institute of Technology POLSAR Mode The characteristics of POLSAR mode are: P Simultaneous P, L, C-band quad-polarizations (HH, HV, VH, VV) P Selectable chirp bandwidth (range resolution): 20 MHz, 40 MHz, 80 MHz (L-band only) P Co-registered output imagery in slant range projection (typically 3.3 m x 4.5 m pixel spacing) P Output data in compressed Stokes matrix format (10 bytes/pixel) P Cross-polarization isolation: better than -20 dB P Noise-equivalent sigma0: < -45 dB in P & L-band, < -30 dB in C- band P Absolute calibration: 3 dB for P-band and 2 dB for L & C-band P Relative calibration: 0.5 dB between polarization channels and 1.5 dB between frequencies

Jet Propulsion Laboratory California Institute of Technology POLSAR Mode (cont.) P “sigma0c” program to extract arbitrary polarization combination from compressed Stokes matrix file. P Commercial software available to read AIRSAR data format: ENVI. P Polarimetric data are used to estimate soil moisture, surface roughness, forest biomass, and land cover classification. P Radars at longer wavelengths (P-band and L-band) are able to penetrate forest canopy and wet snow.

Jet Propulsion Laboratory California Institute of Technology TOPSAR Mode The characteristics of TOPSAR mode are: P Simultaneous C-band cross-track interferometry (V-pol), L-band cross-track interferometry or polarimetry, and P-band polarimetry P Selectable chirp bandwidth (range resolution): 20 MHz, 40 MHz P Co-registered output imagery in ground range projection P Output DEM file in 5 m posting (40 MHz bandwidth) or 10 m posting (20 MHz bandwidth) P RMS height error: m for C-band and m for L-band P C and L-band DEMs provide information on differential penetration into tree canopy

Jet Propulsion Laboratory California Institute of Technology TOPSAR Mode (cont.) Standard output data products include: P DEM file in 5 m or 10 m posting P VV magnitude imagery (calibrated radar backscattering cross- section) P Local incidence angle map P Correlation map P L-band (if available) and P-band compressed Stokes matrix files P All output files are co-registered in ground range projection P DEM is used for terrain correction on POLSAR data