BYU High Resolution Images of NSCAT Sigma0 Measurements (D. Long)


The NASA scatterometer (NSCAT) provided normalized radar cross section (sigma0) measurements of the Earth's surface. While originally designed for wind observation, scatterometer sigma0 measurements have proven useful in a variety of land and ice studies. To aid in the application of these measurements, Brigham Young University has prepared this dataset consisting of enhanced resolution images generated from NSCAT sigma0 measurements.

Table of Contents:

1. Data Set Overview:

Data Set Identification:

PO.DAAC Dataset Long Name: NSCAT Gridded Level 3 Enhanced Resolution Sigma-0 from BYU
PO.DAAC Legacy Product ID: 177

Data Set Introduction:

This data set contains images from 16 regions around the globe. Images are made from NSCAT Level 1.5 data (geo-located sigma0 cells) and processed using the BYU SIRF algorithm. To produce the highest possible spatial resolution as well as to ensure full coverage over the images, multiple orbit passes are combined.

Ice Extent

This data set also contains ASCII ice extent files from the Arctic and the Antarctic.


With their rapid global coverage, day or night and all-weather operation, scatterometers offer a unique tool for long-term climate studies. The first wind scatterometer, the Ku-band Seasat Scatterometer (SASS), provided a baseline for later scatterometers such as NSCAT to measure global change.

Summary of Parameters:

Each data file contains one image and represents a unique combination of:
  • polarization
  • geographical region
  • time span
  • image type
  • reconstruction technique
Land- and ice-masked versions of some files are often available as well.


Launched in 1996 aboard the ADEOS-I satellite, the Ku-band NASA Scatterometer (NSCAT) operated for 9 months until the spacecraft power system failed. NSCAT had 6 dual-pol antennas covering two 600 km wide swaths, one on each side of the spacecraft. NSCAT used on-board digital processing to achieve nominally 25 km resolution sigma0 measurements over a 25 km grid.

Related Data Sets:

NSCAT Data Products
  • NSCAT scatterometer ocean wind products CD-ROM (JPL)
    JPL PO.DAAC Product #85
  • NSCAT scatterometer global 25km sigma-0 and ocean winds (Dunbar)
    JPL PO.DAAC Product #84
  • NSCAT Scatterometer Science Product, Levels 1.7, 2, 3
    JPL PO.DAAC Product #66
  • NSCAT scatterometer SDR, geo-located sigma0 cells Level 1.5 (JPL)
    JPL PO.DAAC Product #62
The Scatterometry Climate Record Pathfinder (SCP),, at Brigham Young University is the source of this and other data sets available from PO.DAAC:
  • SeaWinds on QuikSCAT Gridded Level 3 Daily Browse Sigma-0 Measurements from BYU (D. Long)
  • SeaWinds on QuikSCAT Gridded Level 3 Enhanced Resolution Sigma-0 Measurements from BYU (D. Long)
    PO.DAAC Dataset ID: PODAAC-QSBYU-ENR00; formerly, PO.DAAC Product 122
  • SeaWinds on ADEOS-II Gridded Level 3 Daily Browse Sigma-0 Measurements from BYU (D. Long)
  • SeaWinds on ADEOS-II Gridded Level 3 Enhanced Resolution Sigma-0 Measurements from BYU (D. Long)
    PO.DAAC Dataset ID: PODAAC-SEABY-ENR00; formerly, PO.DAAC Product 124
  • SEASAT-A Scatterometer Gridded Level 3 Enhanced Resolution Sigma-0 Measurements from BYU (D. Long)
    PO.DAAC Dataset ID: PODAAC-SASSX-BYSN0; formerly, PO.DAAC Product 175
  • ERS-1 Gridded Level 3 Enhanced Resolution Sigma-0 Measurements from BYU (D. Long)
    PO.DAAC Dataset ID: PODAAC-ERS1B-SNEN0; formerly, PO.DAAC Product 176
  • ERS-2 Gridded Level 3 Enhanced Resolution Sigma-0 Measurements from BYU (D. Long)
    PO.DAAC Dataset ID: PODAAC-ERS2B-SNEN0; formerly, PO.DAAC Product 177

2. Investigator(s):

Investigator:Dr. David G. Long
Title:Director, BYU Center for Remote Sensing
Professor, Department of Electrical & Computer Engineering
Address: 459 Clyde Building
Brigham Young University
Provo, UT 84602

3. Theory of Measurements:

Scatterometers are designed to measure the normalized radar cross-section backscatter (also termed sigma0) of the surface. Over the ocean, the backscatter is due to Bragg scattering of microwaves from centimeter length capillary ocean waves which is related to the wind. Sigma0 measurements from multiple azimuth angles can be used to estimate the near-surface vector wind. Over land, the backscatter is related to the surface roughness and dielectric properties as well as volume scattering from vegetation and snow cover. Over ice, the backscatter is very sensitive to melting and brine inclusions. It is also sensitive to the internal structure of the ice via volume scattering.

4. Equipment:

Advanced Earth Observing Satellite (ADEOS)

Sensor/Instrument Description:

Collection Environment:

NSCAT was a specialized, wind-measuring microwave radar instrument aboard the Advanced Earth Observing Satellite (ADEOS). The instrument was located on the forward (top) end of the spacecraft.


The National Space Development Agency of Japan (NASDA) launched the Advanced Earth Observing Satellite (ADEOS) at 10:53am on August 17, 1996 (JST) from Tanegashima Space Center. The largest satellite ever developed by Japan, ADEOS had a mass of 3500 kilograms and a power-generation capability of 4500 watts. The bus dimensions at launch were 4x4x5 meters; with the NSCAT antennas deployed, the total height of the spacecraft was 11 meters.

Source/Platform Mission Objectives:

NSCAT measured wind speeds and directions over > 90% of the ice-free oceans every 2 days -- under all weather and cloud conditions.

Key Variables:

The normalized radar cross-section backscatter, i.e. sigma0

Principles of Operation:

"NSCAT has six stick-type antennas generating fan beam footprints on the ground, oriented to make observations at three independent azimuths on each side of the satellite subtrack. With the dual-polarized mid-beams, there are a total of eight independent antenna/polarization combinations. In order to achieve 25 km resolution in the along-track direction, the instrument must cycle through all eight beams in 3.74 seconds (the antenna cycle period), giving 468 msec per beam in which to obtain sigma0 measurements. The radar return signal is received in four bandpass filter 'channels', and divided by the on-board digital Doppler processor into 25 sigma0 'cells' (24 science + 1 monitor) with cross-track resolution of 25 km. Each beam measurement period consists of a sequence of 29 pulse cycles 16 msec long, of which the first 25 cycles are transmit/receive cycles (5 msec transmit pulse length, 11 msec receive interval) and the last 4 are receive-only cycles, providing signal+noise and noise-only received power measurements respectively. Superimposed on these cycles is the measurement cycle sequence, consisting of 128 antenna cycles (about 8 minutes long), of which the first cycle is a calibration cycle." [NSCAT Science Data Product User's Manual, 1998]

Sensor/Instrument Measurement Geometry:

NSCAT scanned two 600 km bands of ocean: one on each side of the instrument's orbital path separated by a gap of approximately 380 km.

Manufacturer of Sensor/Instrument:







Frequency of Calibration:

"Every 128 antenna cycles, NSCAT performed a self-calibration step to provide receiver gain data necessary in computing the radar backscatter." [NSCAT Science Data Product User's Manual, 1998]

Other Calibration Information:


5. Data Acquisition Methods:

"The NSCAT Ground System included components provided by Japan (NASDA) and by the US (NASA). For the NSCAT data used for processing the science products the ADEOS-I Low Mission Data-Rate Recorders (LMDR) were played back to the Earth Observation Center (EOC) at Hatoyama. Data were collected for one week and organized into a time-ordered Level 0 file. A weekly data tape was shipped by EOC to JPL for processing by the NSCAT Science Processing Operations Team (SPOT) using the NSCAT Science Data Processing System (SDPS) . The Science Algorithm Performance and Instrument Engineering Team (SAPIENT) performed quality assurance tests to the standard science products, in addition to calibration and validation analyses. After the data quality had been verified, the SPOT sent the data to PO.DAAC, also located at JPL. PO.DAAC converted the SDPS format data to Hierarchical Data Format (HDF) for distribution for certain level products. [NSCAT Science Data Product User's Manual, 1998]

Brigham Young University (BYU) obtained NSCAT Level 1.5 data from PO.DAAC and used them in creating this product.

6. Observations:

Data Notes:


Field Notes:


7. Data Description:

Spatial Characteristics:

Spatial Coverage:

Alaska Greenland North America North America Central America Antarctica South America South America Europe Northern Africa Northern Africa Southern Africa Siberia Bering Sea Bering Sea China and Japan Southern Asia Southern Asia Arctic Indonesia Indonesia Australia and New Zealand
The 16 regions of this data set are:
Alaska, Antarctic, Arctic, Australia, Bering Sea, Central America, China and Japan, Europe, Greenland, Indonesia, North America, North Africa, Siberia, South Africa, South America, South Asia

Spatial Coverage Map:

The absolute value of a pixel in a count image indicates the number of sigma0 measurements that hit the pixel during the imaging interval. Zero indicates no data.

Spatial Resolution:

Each file's reconstruction technique determines its resolution.
SIR, average files: 4.45 km pixel grid
Gridded files: 22.25 km pixel grid
A field in the header identifies the resolution.


Each file's geographical region determines its projection.
Antarctic, Arctic files: polar stereographic projection
All others: Lambert Equal Area projection
A field in the header identifies the projection.

Grid Description:

Two auxiliary files for each region at each spatial resolution (i.e. 4.45 km/pix for SIR and average files, 22.25 for gridded) contain the longitude and latitude for the center of each pixel. The files are in the same format as the product but have a latitude or a longitude value instead of a sigma0 value stored in the image. The naming scheme for these auxiliary files is:
Timage type x = longitude, y = latitude
regregion Ala = Alaska, Ant = Antarctica, ...
rcn reconstruction technique sir = SIR, grd = gridded

Two other types of auxiliary files for each region at each spatial resolution contain topography and land mask information. The naming scheme for these files is:
regregion Ala = Alaska, Ant = Antarctica, ...
rcn reconstruction technique sir = SIR, grd = gridded
infotype topo = topography, lmask = land mask

Temporal Characteristics:

Temporal Coverage:

15 September 1996 - 26 June 1997

Temporal Coverage Map:

Not available.

Temporal Resolution:

The imaging time ranges from 6 to 12 days.

Data Characteristics:


Each data file contains one image and represents a unique combination of parameters, which is reflected in the naming scheme.
Timage type
sigma0 average, the normalized sigma0 at a 40° incidence angle
sigma0 standard deviation
sigma0 error
sigma0 slope, sigma0 vs. incidence angle
average incidence angle
incidence angle standard deviation
count, the number of measurements
pixel time
reg geographical
region -
see Spatial

Ala Alaska
Ant Antarctic
Arc Arctic
Aus Australia
Ber Bering Sea
CAm Central America
ChJ China and Japan     Eur Europe
Grn Greenland
Ind Indonesia
NAm North America
NAf North Africa
SAf South Africa
SAm South America
SAs South Asia
Sib Siberia
yy two-digit year, either 96 or 97
dd1 three-digit day of year, start of imaging
dd2 three-digit day of year, end of imaging
rcn reconstruction
SIR or SIRF. The Data Manipulations section describes SIR processing generally then specifically for NSCAT.
average, the first iteration of the SIR algorithm, less enhanced but less noisy (see Processing Steps)
gridded, non-enhanced on a coarser grid
msk mask (optional)
ice mask. If present, image is ice masked.
land mask. If present, image is land masked.

The Grid Description section describes the naming scheme and the meanings of the auxiliary files.

Ice Extent

The ASCII ice extent files contain the "average" sea ice edge over a 6-day period, with time periods overlapping on 3-day centers. The naming scheme:
The fields have the same meanings as above. The only two regions these files are produced for are the Arctic and the Antarctic.

Variable Description/Definition:

See the previous section

Unit of Measurement:

This depends upon the image type.
sigma0 average: dB
sigma0 standard deviation: dB
sigma0 error: dB
sigma0 slope: dB/deg
average incidence angle: deg
incidence angle standard deviation: deg
count: unitless
pixel time

Data Source:

Images are made from NSCAT Level 1.5 data, geo-located sigma0 cells.

Data Range:


Sample Data Record:

Each file contains 1 image, which can be visualized using the software described below, such as the modified version of xv.

Each file also has header information. The program xv printed the following sample output as it displayed the file nscv-a-Ala96-259-270.sir:

    SIR file header: 'nscv-a-Ala96-259-270.sir'
      Title:   'SIRF image of alaska'
      Sensor:  'NSCAT L1.5'
      Type:    'A image  (nscv-a-Ala96-259-270.sir)'
      Tag:     '(c) 2001 BYU MERS Laboratory'
      Creator: 'BYU MERS:nscat_meta_sirf v3.0 Ai= -8.40 Bi=-0.140 Bw=30 It=50'
      Created: '15:54:57 06/22/01'
      Size: 810 x 630    Total:510300  Offset: -33  Scale: 1000
      Year: 1996  JD range: 259-270  Region Number: 203  Type: 1  Form: 2
      Polarization: 2  Frequency: 14.000000 MHz
      Datatype: 2  Headers: 1  Ver:30
      Nodata: -33.000000   Vmin: -32.000000  Vmax: 0.000000
      Lambert form: (local radius)
       Center point:      -155.000000 , 61.500000
       Lon, Lat scale:    4.450000 , 4.450000 (km/pix)
       Lower-Left Corner: -1800.000000 , -1300.000000
      Image Min, Max: -32.000000 , 0.000000

    Greyscale conversion range:  Min: -32.000000, Max:0.000000

8. Data Organization:

Data Granularity:

The basic granule is one data file. Each file has a unique combination of polarization, region, image type, time span, reconstruction technique, and land mask.

The EOSDIS Glossary describes data granularity generally as it applies to the IMS.

Data Format:

The BYU-MERS SIR image format was developed by the Brigham Young University (BYU) Microwave Earth Remote Sensing (MERS) laboratory to store a variety of image types along with the information required to Earth-locate the image pixels.

A SIR format file consists of one or more 512-byte headers followed by the image data and additional zero padding to insure that the file is a multiple of 512 bytes long. The file header record contains all of the information required to read the remainder of the file and the map projection information required to map pixels to lat/lon on the Earth surface. The image pixel values generally represent floating point values and may be stored in one of three ways. The primary way is as 2 byte integers (with the high order byte first), though the pixels may be stored as single bytes or IEEE floating point values. Scale factors are stored in the header to convert the integer or byte pixel values to native floating point units.

The image is stored in row-scanned (left to right) order from the lower left corner (the origin of the image) up through the upper right corner. By default, the location of a pixel is identified with its lower-left corner. The origin pixel (1,1) is the lower left corner of the image. The array index n of the (i,j)th pixel where i is horizontal and j is vertical is given by

n = (j - 1) × Nx + i
where Nx is the horizontal dimension of the image. The last pixel stored in the file is at (Nx, Ny).

The SIR file header contains various numerical values and strings that describe the image contents. For example, the value for a no-data flag is set in the header as well as a nominal display range and the minimum and maximum representable value. Optional secondary header records (512 bytes) can be used to store additional, non-standard information.

The standard SIR file format supports a variety of image projections including:

  1. Rectangular array (no projection)
  2. Rectangular lat/lon array
  3. Two different types of Lambert equal-area projections which can be used in either non-polar or polar projections
  4. Polar stereographic projections
  5. EASE grid polar projection with various resolutions
  6. EASE global projection with various resolutions

Any of the programs described in Software below decodes SIR headers.

Ice Extent

The ASCII ice extent files, available only for the Arctic and the Antarctic, contain latitude/longitude pairs that represent the contour points of the estimated sea ice edge. Each line entry in the file consists of two values: a longitude, ranging from -180 to +180, and a latitude. Multiple contours are separated by a '0 0' entry.

9. Data Manipulations:


Derivation Techniques and Algorithms:

In general, SIR data files are generated using the scatterometer image reconstruction (SIR) resolution enhancement algorithm or one of its variants for radiometer processing. The multivariate SIR algorithm is a non-linear resolution enhancement algorithm based on modified algebraic reconstruction and maximum entropy techniques [Long, Hardin, and Whiting, 1993]. The singlevariate SIR algorithm was developed originally for radiometers [Long and Daum, 1997] but also used for SeaWinds [Early and Long, 2001]. The SIR w/filtering (SIRF) algorithm has been successfully applied to SASS and NSCAT measurements to study tropical vegetation and glacial ice (e.g. Long and Drinkwater, 1999). Variants of SIR have been successfully applied to the ERS-1/2 scatterometer and various radiometers (SSM/I and SMMR). (SIRF is used for SASS, NSCAT, and SeaWinds slice data processing. SIR is used for ERS-1/2 and SeaWinds egg data. The modified median filter [SIRF] is not used with ERS-1/2 data and SeaWinds egg data.)

For scatterometers, the multivariate form of the SIR algorithm models the dependence of sigma0 on incidence angle as sigma0 (in dB) = A + B * (Inc Ang - 40 deg) over the incidence angle range of 15 to 60 deg. The output of the SIR algorithm is images of the A and B coefficients. See the Data Characteristics section.

A represents the "incidence angle normalized sigma0" (effectively the sigma0 value at 40 deg incidence angle). The units of A are dB. Typically, +2 < A < -45 dB. However, in the SIR images A is typically clipped to a minimum -32 dB with values of A < -32 used to indicate 'no data'.

B describes the incidence angle dependence of sigma0 and has units of dB/deg. At Ku-band the global average of B is approximately -0.13 dB/deg. Typically, -0.2 < B < -0.1. B is clipped to a minimum value of -3 dB/deg. This value is used to denote 'no data' as well.

Single variable SIR or SIRF algorithms are used for radiometers and produce only an A (in this case, the brightness temperature) image. Typically, this can range from 165 to 320. Single variable SIR and SIRF algorithms are used for SeaWinds egg and slice images, respectively. In both cases the A images are at the nominal measurement incidence angle for the sensor and in the sensor measurement units.

Ice Extent

The polarization ratio (AV-AH in dB), vertical incidence angle dependence (BV), and the sigma0 estimate error standard deviation were used to perform the sea ice/ocean discrimination. The ice/ocean modes of the bimodal AV-AH vs. BV distribution were separated using linear and quadratic techniques. The sigma0 estimate error standard deviation threshold was used as the deciding factor when the linear and quadratic extent estimates disagreed. Residual misclassification noise was reduced using binary image processing techniques such as region growing, erosion, and dilation resulting in a low pass filtered version of the edge. The resulting edge closely matches the NSIDC SSM/I-derived 30% ice concentration edge. The lat/lon values in the ASCII edge files were obtained by computing the lat/lon location of each pixel along the edge of the binary ice mask. Note that in cases obvious algorithm ice extent errors, the edges have been manually edited.

Data Processing Sequence:

Processing Steps:

Enhanced resolution images made from NSCAT data use the Scatterometer Image Reconstruction with Filtering (SIRF) algorithm. This version of the algorithm incorporates a median filter and a simplified spatial response function in which the spatial response is assumed to be 1 over the footprint and 0 elsewhere. In the processing, a linear model relating sigma0 and incidence angle is assumed, i.e. sigma0(db) = A + B (theta - 40) where A is the "incidence angle normalized sigma0" at 40 deg incidence in dB, B is the effective incidence slope of sigma0 versus incidence angle in dB/deg, and theta is the incidence angle of the observation. The SIR algorithm makes images of A and B on an 4.5 km pixel grid. The effective resolution varies depending on region and sampling conditions but is estimated to be 8-10 km in most areas. Multiple passes of the spacecraft are combined to produce a higher spatial resolution (at a cost of reduced temporal resolution) and fill in coverage gaps between the individual measurement footprints. NSCAT measurement footprints are not contiguous and have six-sided shapes with a nominal 25 km resolution.

Processing Changes:



Special Corrections/Adjustments:


Calculated Variables:


Graphs and Plots:


10. Errors:

Sources of Error:

NSCAT was operated continuously in double-sided mode, collecting measurements over two 600 km wide swaths at both V and H pol. Since only two of the antennas were operated in dual-pol mode, there are significantly fewer H pol measurements than V pol and, in contrast to the V pol measurements, tend to be aligned with each other and thereby reducing the effective resolution enhancement. NSCAT operated at 13.995 GHz. In combining the multiple passes, sigma0 is assumed to be independent of azimuth angle. While true for most areas, some azimuth dependence in sigma0 has been observed in Antarctic firn, presumably due to sastrugi or snow dunes.

Ice Extent

Until about 1996 JD 300 the data set is not continuous due to periods of missing NSCAT data early in the mission. In some cases, the ice mapping algorithm obviously failed in small localized regions of the ice edge. In such situations, the edges were manually edited to improve the quality of the edges. When editing has been performed, it is noted in the header information of the SIR .imsk files.

Quality Assessment:

Data Validation by Source:


Confidence Level/Accuracy Judgement:


Measurement Error for Parameters:


Additional Quality Assessments:


Data Verification by Data Center:


11. Notes:

Limitations of the Data:


Known Problems with the Data:


Usage Guidance:


Any Other Relevant Information about the Study:


12. Application of the Data Set:

  • Ice extent, especially polar
  • Tropical vegetation

13. Future Modifications and Plans:

There are no future modifications or plans at this time.

14. Software:

Software Description:

Sample read and display software for SIR files are available in C, FORTRAN, IDL/PV-WAVE, and MATLAB. These programs can be easily modified to meet the requirements of individual users.
LanguageProgram NameDescription
C csir_dump.cdump SIR file to text output
csirexample.c read SIR file, print values of corner pixels
sir2bmp.cconvert SIR file to BMP
sir2byte.cconvert SIR file to raw, unsigned byte file
sir2gif.cconvert SIR file to GIF
Fortran fsir_dump.fdump SIR file to text file
fsir_locmap.fread SIR file, create latitude and longitude maps like the auxiliary files
fsirexample.f read SIR file, create an unsigned byte file
sirmask.fmask one SIR file over another to create masked SIR file load SIR file, save to file, display image, do forward/inverse transforms
PV-WAVE, load SIR file, save to file, display image, do forward/inverse transforms
MATLABloadsir.m, writesir.m, showimage.m, ... load SIR file, save to file, display image, do forward/inverse transforms
IDL is made by Research Systems, Inc.
PV-WAVE is made by Visual Numerics, Inc.
MATLAB is made by The MathWorks, Inc.
All are copyrighted software tools for numerical analysis and visualization.

Software Access:

The latest versions of the sample read and display software can be obtained via anonymous FTP from, where lang = "c", "f", "idl", or "matlab". JPL PO.DAAC also maintains a copy at

The IDL and PV-WAVE programs reside in one directory due to the similarity between the languages.,, and call the same functions, though the file must be modified for PV-WAVE.

15. Data Access:

Contact Information:

For general questions and comments regarding this dataset, please contact
Email is the preferred method of communication.

Dr. David Long of BYU is the source of this dataset. Please contact him with more detailed questions. See Investigator for contact information.

Data Center Identification:

Jet Propulsion Laboratory (JPL)
Physical Oceanography Archive Center (PO.DAAC)

Procedures for Obtaining Data:

This data set is currently available via anonymous FTP at

This data set is publicized courtesy of the PO.DAAC at JPL.

Data Center Status/Plans:


16. Output Products and Availability:

This data set is made available at PO.DAAC on behalf of the BYU SCP:

17. References:

NSCAT Science Data Product User's Manual, Version 1.2, JPL D-12985, February 1998, Jet Propulsion Laboratory, Pasadena, CA.

Early, D.S. and D.G. Long, Feb 2001. "Image Reconstruction and Enhanced Resolution Imaging From Irregular Samples", IEEE Transactions on Geoscience and Remote Sensing, Vol. 39, No.2, pp. 291-302.

Long, D.G. and D. Daum, 1997. "Spatial Resolution Enhancement of SSM/I Data", IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, pp. 407-417.

Long, D.G. and M.R. Drinkwater, 1999. "Cryosphere Applications of NSCAT Data", IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, No. 3, pp. 1671-1684.

Long, D.G., P. Hardin, and P. Whiting, 1993. "Resolution Enhancement of Spaceborne Scatterometer Data", IEEE Transactions on Geoscience and Remote Sensing, Vol. 31, pp. 700-715.

Ice Extent

Remund, Q.P. and D.G. Long, 4-8 August, 1997. "Automated Antarctic Ice Edge Detection Using NSCAT Data", Proc. IGARSS'97, pp. 1841-1843, Singapore

Remund, Q.P. and D.G. Long, 1999. "Sea Ice Extent Mapping Using Ku-Band Scatterometer Data", Journal of Geophysical Research, Vol. 104, No. C5, pp. 11515-11527

18. Glossary of Terms:

See the EOSDIS Glossary for a more general listing of terms related to the Earth Observing System project.

19. List of Acronyms:

EOS: Earth Observing System
EOSDIS: Earth Observing System Data and Information System
FTP: File Transfer Protocol
GDR: Geophysical Data Record
IDL: Interactive Data Language
JPL: Jet Propulsion Laboratory
NASA: National Aeronautics and Space Administration
NSCAT: NASA Scatterometer
PO.DAAC: Physical Oceanography Distributed Active Archive Center
QuikSCAT: the NASA Quick Scatterometer spacecraft, or
QuikSCAT: usually refers to the SeaWinds instrument on the spacecraft
SASS: Seasat Satellite Scatterometer
SDR: Sensor Data Record
SMMR: Scanning Multichannel Microwave Radiometer
SSM/I: Special Sensor Microwave/Imager
STDN: Spaceflight Tracking and Data Network
URL: Uniform Resource Locator
VIRR: Visual and Infrared Radiometer

20. Document Information:

Document Creation Date:

3 January 2003

Document Review Date:

3 January 2003

Document Revison Date:

6 December 2011

Document ID:



Document originally written by Richard Chen based heavily on information on the BYU SCP web site,

Document Curator:

PO.DAAC Data Engineering Team

Document URL: