This data set consists of enhanced resolution images generated from Seasat sigma0 measurements.
Capable of dual-polarization operation over a single 500 km wide swath, SASS normally operated in V-pol, dual-sided swath mode over the ocean. Unlike later scatterometers, its operating mode changed very frequently over land. Only a limited amount of H-pol data was collected over land and ice during the mission. The limited spatial coverage necessitates long imaging time periods, yet there are still frequent gaps in the image coverage.
Images of both V and H pol backscatter are produced. Because SASS made measurements of sigma0 over a range of incidence angles, a simple scheme was used to model the incidence angle variation: a linear model relating sigma-0 and incidence angle is assumed where
sigma-0(db) = A + B (theta - 40)where A is the "incidence angle normalized sigma-0" at 40 deg incidence in dB, B is the effective incidence slope of sigma-0 versus incidence angle in dB/deg, and theta is the incidence angle of the observation. While SASS collected backscatter measurements at near-nadir incidence angles, only measurements with incidence angle greater than 15 deg were used in making image products of A and B. Images of A and B, as well as ancillary images, are made at both the nominal sensor resolution and at enhanced resolution. The effective resolution of the enhanced resolution images vary depending on region and sampling conditions.
|Investigator:||Dr. David G. Long|
BYU Center for Remote Sensing|
Professor, Department of Electrical & Computer Engineering
|Address:||459 Clyde Building|
Brigham Young University
Provo, UT 84602
The satellite orbit is near-circular, with an inclination of 108 deg, a period of 101 min, and an altitude of a 790km. During its period of operation, Seasat circled the Earth 14 times daily, covering 95 percent of the global ocean area every 36 hours, and completing 1503 revolutions of the Earth.
"The illumination pattern for each antenna was active for 1.89-s measurement periods. The 1.89-s measurement interval was repeated continually and contiguously, but a different antenna or polarization was activated for each consecutive sampling period. Each of eight possible SASS science operational modes was associated with a different prescribed antenna/polarization sequence ordered .... All modes were characterized by an antenna switching-cycle period of 7.56 s, during which four antenna-beam/polarization combinations were cycled through. This timing was to provide sigma-0 measurements spaced approximately 50km apart (footprint area center-to-center distance) in the along-track direction"
"Fifteen Doppler filters were used to electronically subdivide each full antenna footprint into 15 measurement resolution "Doppler" cells of approximate dimension 20 km (cross-beam) by 50 km (along-beam). The intersection of the antenna-beam pattern and Doppler lines determined the resolution cell size, orientation, and location on the Earth.... The instantaneous-field-of-view (IFOV) cell boundaries were determined by the Doppler filter noise bandwidth and the antenna 3-dB beamwidth (.5 deg) in the narrow-beam dimension. [The integrated cell is the area swept out by a sequence of 61 overlapping IFOV cells generated over the course of a 1.89-s measurement period.] The surface area of this final integrated Doppler resolution cell is greater than the instantaneous illuminated region because the satellite moved (about 12.5-km ground-track distance) during the measurement period. Each of these integrated Doppler cells is a SASS footprint, and has one sigma-0 backscatter measurement value associated with it" [Boggs, 1982].
Scatterometer Ground Pattern and Swath
Extensive post-launch calibration efforts have demonstrated the calibration accuracy of the measurements [Long and Skouon].
Spacecraft data are received and recorded by tracking stations of the Spaceflight Tracking Data Network (STDN) and transmitted to the Goddard Space Flight Center (GSFC). There, data are sorted, merged, time tagged, and recorded on magnetic tape, which is then shipped to the Instrument Data Processing System (IDPS) at JPL.
The data package received from GSFC consists of the Sensor (non-SAR) and engineering data as well as attitude and orbit determination data. These data are decommutated, organized by major frame, and converted from data numbers to engineering units. Footprint locations are calculated, and data are then formatted into archival-quality SDR (Sensor Data Record) tapes suitable as input for engineering assessment and geophysical processing.
The absolute value of a pixel in a count image indicates the number of sigma-0 measurements that hit the pixel during the imaging interval. Zero indicates no data.
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
|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:
|reg||region||Ala = Alaska, Ant = Antarctica, ...|
|rcn||reconstruction technique||sir = SIR, grd = gridded|
|info||type||topo = topography, lmask = land mask|
||two-digit year, always 78
||three-digit day of year, start of imaging
||three-digit day of year, end of imaging
The Grid Description section describes the naming scheme and the meanings of the auxiliary files.
Each file also has header information. The program xv printed the following sample output as it displayed the file sasv-a-Ala78-188-233.sir.lmsk:
SIR file header: 'sasv-a-Ala78-188-233.sir.lmsk' Title: 'SIRF image of alaska' Sensor: 'SASS' Type: 'A image (sasv-a-Ala78-188-233.sir)' Tag: '(c) 1999 BYU MERS Laboratory' Creator: 'BYU MERS:sass_meta_sirf v1.0 Ai= -8.40 Bi=-0.140 Bw=30 It=50' Created: '01:39:18 03/19/01' Size: 810 x 630 Total:510300 Offset: -33 Scale: 1000 Year: 1978 JD range: 188-233 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 which 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 SASS data use the Scatterometer Image Reconstruction with Filtering (SIRF) algorithm. This version of the algorithm incoporates 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 a 4.5 km pixel grid. The effective resolution varies depending on region and sampling conditions. 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. SASS measurement footprints were not contiguous, had irregular six-sided shapes, and varied in size depending on beam and location on the earth.
SIRF is an interative algorithm, terminated after 50 iterations in this processing.
The measurement accuracy of ° was affected primarily by communication noise, attitude pointing uncertainty, instrument processing (e.g., quantization errors and gain uncertainty), and various bias errors. Bias error are in general deterministic and, depending upon the existence of adequate comparison data, are removable. The remaining errors, which are random in nature and not removable, limit the ultimate accuracy of scattering coefficient measuremnts. [Boggs, 1982]
|C||csir_dump.c||dump SIR file to text output|
|csirexample.c||read SIR file, print values of corner pixels|
|sir2bmp.c||convert SIR file to BMP|
|sir2byte.c||convert SIR file to raw, unsigned byte file|
|sir2gif.c||convert SIR file to GIF|
|Fortran||fsir_dump.f||dump SIR file to text file|
|fsir_locmap.f||read SIR file, create latitude and longitude maps like the auxiliary files|
|fsirexample.f||read SIR file, create an unsigned byte file|
|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.
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..
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.
Klose, J.C., 1979. "Seasat Node Tables and Osculating Orbital Elements", JPL Internal Document 622-215, Jet Propulsion Laboratory, Pasadena, CA.
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.
Long, D.G. and G.B. Skouson, Mar 1995. "Calibration of Spaceborne Scatterometers Using Tropical Rainforests," IEEE Transactions on Geoscience and Remote Sensing, Vol. 34, No. 2, pp. 413-424.