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 |
Email: | long@ee.byu.edu |
Fax: | (801)422-0201 |
Brigham Young University (BYU) obtained NSCAT Level 1.5 data from PO.DAAC and used them in creating this product.
SIR, average files: 4.45 km pixel gridA field in the header identifies the resolution.
Gridded files: 22.25 km pixel grid
Antarctic, Arctic files: polar stereographic projectionA field in the header identifies the projection.
All others: Lambert Equal Area projection
nsc-T-reg.rcn
T | image type | x = longitude, y = latitude |
reg | region | 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:
nsc-reg.rcn.info
reg | region | Ala = Alaska, Ant = Antarctica, ... |
rcn | reconstruction technique | sir = SIR, grd = gridded |
info | type | topo = topography, lmask = land mask |
nscp-T-regyy-dd1-dd2.rcn[.msk]
p | polarization |
T | image type
| reg
| geographical | region - see Spatial Coverage above
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 |
technique |
The Grid Description section describes the naming scheme and the meanings of the auxiliary files.
regyy-dd1-dd2.ieThe fields have the same meanings as above. The only two regions these files are produced for are the Arctic and the Antarctic.
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
The EOSDIS Glossary describes data granularity generally as it applies to the IMS.
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 + iwhere 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:
Any of the programs described in Software below decodes SIR headers.
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.
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.
Language | Program Name | Description |
---|---|---|
C | csir_dump.c | dump SIR file to text output |
csir_dump_small.c | ||
csirexample.c | read SIR file, print values of corner pixels | |
sir_ez_example.c | ||
sir2bmp.c | convert SIR file to BMP | |
sir2byte.c | convert SIR file to raw, unsigned byte file | |
sir2gif.c | convert SIR file to GIF | |
sir2gif_ez.c | ||
Fortran | fsir_dump.f | dump SIR file to text file |
fsir_dump_small.f | ||
fsir_locmap.f | read SIR file, create latitude and longitude maps like the auxiliary files | |
fsir_locmap_EZ.f | ||
fsirexample.f | read SIR file, create an unsigned byte file | |
fsirexample_EZ.f | ||
sir2byte.f | ||
sirmask.f | mask one SIR file over another to create masked SIR file | |
IDL | xsir_idl.pro | load SIR file, save to file, display image, do forward/inverse transforms |
PV-WAVE | xsir.pro, xsir_pvwave.pro | load SIR file, save to file, display image, do forward/inverse transforms |
MATLAB | loadsir.m, writesir.m, showimage.m, ... | load SIR file, save to file, display image, do forward/inverse transforms |
The IDL and PV-WAVE programs reside in one directory due to the similarity between the languages. xsir_idl.pro, xsir.pro, and xsir_pvwave.pro call the same functions, though the file loadsir.pro must be modified for PV-WAVE.
email: | podaac@podaac.jpl.nasa.gov |
url: |
http://podaac.jpl.nasa.gov/dataset/NSCAT_BYU_L3_OW_SIGMA0_ENHANCED
|
Dr. David Long of BYU is the source of this dataset. Please contact him with more detailed questions. See Investigator for contact information.
This data set is publicized courtesy of the PO.DAAC at JPL.
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.
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