Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Julia A. Barsi is active.

Publication


Featured researches published by Julia A. Barsi.


IEEE Geoscience and Remote Sensing Letters | 2007

Revised Landsat-5 Thematic Mapper Radiometric Calibration

Gyanesh Chander; Brian L. Markham; Julia A. Barsi

Effective April 2, 2007, the radiometric calibration of Landsat-5 (L5) Thematic Mapper (TM) data that are processed and distributed by the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) will be updated. The lifetime gain model that was implemented on May 5, 2003, for the reflective bands (1-5, 7) will be replaced by a new lifetime radiometric-calibration curve that is derived from the instruments response to pseudoinvariant desert sites and from cross calibration with the Landsat-7 (L7) Enhanced TM Plus (ETM+). Although this calibration update applies to all archived and future L5 TM data, the principal improvements in the calibration are for the data acquired during the first eight years of the mission (1984-1991), where the changes in the instrument-gain values are as much as 15%. The radiometric scaling coefficients for bands 1 and 2 for approximately the first eight years of the mission have also been changed. Users will need to apply these new coefficients to convert the calibrated data product digital numbers to radiance. The scaling coefficients for the other bands have not changed.


Proceedings of SPIE | 2005

Validation of a web-based atmospheric correction tool for single thermal band instruments

Julia A. Barsi; John R. Schott; Frank D. Palluconi; Simon J. Hook

An atmospheric correction tool has been developed on a public access web site for the thermal band of the Landsat-5 and Landsat-7 sensors. The Atmospheric Correction Parameter Calculator uses the National Centers for Environmental Prediction (NCEP) modeled atmospheric global profiles interpolated to a particular date, time and location as input. Using MODTRAN radiative transfer code and a suite of integration algorithms, the site-specific atmospheric transmission, and upwelling and downwelling radiances are derived. These calculated parameters can be applied to single band thermal imagery from Landsat-5 Thematic Mapper (TM) or Landsat-7 Enhanced Thematic Mapper Plus (ETM+) to infer an at-surface kinetic temperature for every pixel in the scene. The derivation of the correction parameters is similar to the methods used by the independent Landsat calibration validation teams at NASA/Jet Propulsion Laboratory and at Rochester Institute of Technology. This paper presents a validation of the Atmospheric Correction Parameter Calculator by comparing the top-of-atmosphere temperatures predicted by the two teams to those predicted by the Calculator. Initial comparisons between the predicted temperatures showed a systematic error of greater then 1.5K in the Calculator results. Modifications to the software have reduced the bias to less then 0.5 ± 0.8K. Though not expected to perform quite as well globally, the tool provides a single integrated method of calculating atmospheric transmission and upwelling and downwelling radiances that have historically been difficult to derive. Even with the uncertainties in the NCEP model, it is expected that the Calculator should predict atmospheric parameters that allow apparent surface temperatures to be derived within ±2K globally, where the surface emissivity is known and the atmosphere is relatively clear. The Calculator is available at http://atmcorr.gsfc.nasa.gov.


Canadian Journal of Remote Sensing | 2003

Landsat TM and ETM+ thermal band calibration

Julia A. Barsi; John R. Schott; F D Palluconi; Dennis L. Helder; Simon J. Hook; Brian L. Markham; Gyanesh Chander; E M O'Donnell

Landsat-5 has been imaging the Earth since March 1984, and Landsat-7 was added to the series of Landsat instruments in April 1999. The Landsat Project Science Office and the Landsat-7 Image Assessment System have been monitoring the on-board calibration of Landsat-7 since launch. Additionally, two separate university teams have been evaluating the on-board thermal calibration of Landsat-7 through ground-based measurements since launch. Although not monitored as closely over its lifetime, a new effort is currently being made to validate the calibration of Landsat-5. Two university teams are beginning to collect ground truth under Landsat-5, along with using other vicarious calibration methods to go back into the archive to validate the history of the calibration of Landsat-5. This paper considers the calibration efforts for the thermal band, band 6, of both the Landsat-5 and Landsat-7 instruments. Though stable since launch, Landsat-7 had an initial calibration error of about 3 K, and changes were made to correct for this beginning 1 October 2000 for data processed with the National Landsat Archive Production System (NLAPS) and beginning 20 December 2000 for data processed with the Landsat Product Generation System (LPGS). Recent results from Landsat-5 vicarious calibration efforts show an offset of ‐0.7 K over the lifetime of the instrument. This suggests that historical calibration efforts may have been detecting errors in processing systems rather than changes in the instrument. A correction to the Landsat-5 processing has not yet been implemented but will be in the near future.


Remote Sensing | 2014

Landsat-8 Operational Land Imager Radiometric Calibration and Stability

Brian L. Markham; Julia A. Barsi; Geir Kvaran; Lawrence Ong; Edward Kaita; Stuart F. Biggar; Jeffrey S. Czapla-Myers; Nischal Mishra; Dennis L. Helder

The Landsat-8 Operational Land Imager (OLI) was radiometrically calibrated prior to launch in terms of spectral radiance, using an integrating sphere source traceable to National Institute of Standards and Technology (NIST) standards of spectral irradiance. It was calibrated on-orbit in terms of reflectance using diffusers characterized prior to launch using NIST traceable standards. The radiance calibration was performed with an uncertainty of ~3%; the reflectance calibration to an uncertainty of ~2%. On-orbit, multiple calibration techniques indicate that the sensor has been stable to better than 0.3% to date, with the exception of the shortest wavelength band, which has degraded about 1.0%. A transfer to orbit experiment conducted using the OLI’s heliostat-illuminated diffuser suggests that some bands increased in sensitivity on transition to orbit by as much as 5%, with an uncertainty of ~2.5%. On-orbit comparisons to other instruments and vicarious calibration techniques show the radiance (without a transfer to orbit adjustment), and reflectance calibrations generally agree with other instruments and ground measurements to within the uncertainties. Calibration coefficients are provided with the data products to convert to either radiance or reflectance units.


Remote Sensing | 2014

The Spectral Response of the Landsat-8 Operational Land Imager

Julia A. Barsi; Kenton Lee; Geir Kvaran; Brian L. Markham; Jeffrey A. Pedelty

Abstract: This paper discusses the pre-launch spectral characterization of the Operational Land Imager (OLI) at the component, assembly and instrument levels and relates results of those measurements to artifacts observed in the on-orbit imagery. It concludes that the types of artifacts observed and their magnitudes are consistent with the results of the pre-launch characterizations. The OLI in-band response was characterized both at the integrated instrument level for a sampling of detectors and by an analytical stack-up of component measurements. The out-of-band response was characterized using a combination of Focal Plane Module (FPM) level measurements and optical component level measurements due to better sensitivity. One of the challenges of a pushbroom design is to match the spectral responses for all detectors so that images can be flat-fielded regardless of the spectral nature of the targets in the imagery. Spectral variability can induce striping (detector-to-detector variation), banding (FPM-to-FPM variation) and other artifacts in the final data products. Analyses of the measured spectral response showed that the maximum discontinuity between FPMs due to spectral filter differences is 0.35% for selected targets for all bands except for Cirrus, where there is almost no signal. The average discontinuity between FPMs is 0.12% for the same targets. These results were expected and are in accordance with the OLI requirements. Pre-launch testing identified low levels (within requirements) of spectral crosstalk amongst the three HgCdTe (Cirrus, SWIR1 and SWIR2) bands of the OLI and on-orbit data confirms this crosstalk in the imagery. Further post-launch analyses and simulations revealed that the strongest crosstalk effect is from the SWIR1 band to the Cirrus band; about 0.2% of SWIR1 signal leaks into the Cirrus. Though the total crosstalk signal is only a few counts, it is evident in some scenes when the in-band cirrus signal is very weak. In moist cirrus-free atmospheres and over typical land surfaces, at least 30% of the cirrus signal was due to the SWIR1 band. In the SWIR1 and SWIR2 bands, crosstalk accounts for no more than 0.15% of the total signal.


Remote Sensing | 2014

Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration

Julia A. Barsi; John R. Schott; Simon J. Hook; Nina G. Raqueno; Brian L. Markham; Robert G. Radocinski

Launched in February 2013, the Landsat-8 carries on-board the Thermal Infrared Sensor (TIRS), a two-band thermal pushbroom imager, to maintain the thermal imaging capability of the Landsat program. The TIRS bands are centered at roughly 10.9 and 12 μm (Bands 10 and 11 respectively). They have 100 m spatial resolution and image coincidently with the Operational Land Imager (OLI), also on-board Landsat-8. The TIRS instrument has an internal calibration system consisting of a variable temperature blackbody and a special viewport with which it can see deep space; a two point calibration can be performed twice an orbit. Immediately after launch, a rigorous vicarious calibration program was started to validate the absolute calibration of the system. The two vicarious calibration teams, NASA/Jet Propulsion Laboratory (JPL) and the Rochester Institute of Technology (RIT), both make use of buoys deployed on large water bodies as the primary monitoring technique. RIT took advantage of cross-calibration opportunity soon after launch when Landsat-8 and Landsat-7 were imaging the same targets within a few minutes of each other to perform a validation of the absolute calibration. Terra MODIS is also being used for regular monitoring of the TIRS absolute calibration. The buoy initial results showed a large error in both bands, 0.29 and 0.51 W/m2·sr·μm or −2.1 K and −4.4 K at 300 K in Band 10 and 11 respectively, where TIRS data was too hot. A calibration update was recommended for both bands to correct for a bias error and was implemented on 3 February 2014 in the USGS/EROS processing system, but the residual variability is still larger than desired for both bands (0.12 and 0.2 W/m2·sr·μm or 0.87 and 1.67 K at 300 K). Additional work has uncovered the source of the calibration error: out-of-field stray light. While analysis continues to characterize the stray light contribution, the vicarious calibration work proceeds. The additional data have not changed the statistical assessment but indicate that the correction (particularly in band 11) is probably only valid for a subset of data. While the stray light effect is small enough in Band 10 to make the data useful across a wide array of applications, the effect in Band 11 is larger and the vicarious results suggest that Band 11 data should not be used where absolute calibration is required.


Remote Sensing | 2015

Landsat-8 Operational Land Imager (OLI) Radiometric Performance On-Orbit

Ron Morfitt; Julia A. Barsi; Raviv Levy; Brian L. Markham; Esad Micijevic; Lawrence Ong; Pat L. Scaramuzza; Kelly Vanderwerff

Expectations of the Operational Land Imager (OLI) radiometric performance onboard Landsat-8 have been met or exceeded. The calibration activities that occurred prior to launch provided calibration parameters that enabled ground processing to produce imagery that met most requirements when data were transmitted to the ground. Since launch, calibration updates have improved the image quality even more, so that all requirements are met. These updates range from detector gain coefficients to reduce striping and banding to alignment parameters to improve the geometric accuracy. This paper concentrates on the on-orbit radiometric performance of the OLI, excepting the radiometric calibration performance. Topics discussed in this paper include: signal-to-noise ratios that are an order of magnitude higher than previous Landsat missions; radiometric uniformity that shows little residual banding and striping, and continues to improve; a dynamic range that limits saturation to extremely high radiance levels; extremely stable detectors; slight nonlinearity that is corrected in ground processing; detectors that are stable and 100% operable; and few image artifacts.


IEEE Transactions on Geoscience and Remote Sensing | 2004

In-flight validation and recovery of water surface temperature with Landsat-5 thermal infrared data using an automated high-altitude lake validation site at Lake Tahoe

Simon J. Hook; Gyanesh Chander; Julia A. Barsi; Ronald E. Alley; Ali A. Abtahi; Frank D. Palluconi; Brian L. Markham; R.C. Richards; S.G. Schladow; Dennis L. Helder

The absolute radiometric accuracy of the thermal infrared band (B6) of the Thematic Mapper (TM) instrument on the Landsat-5 (L5) satellite was assessed over a period of approximately four years using data from the Lake Tahoe automated validation site (California-Nevada). The Lake Tahoe site was established in July 1999, and measurements of the skin and bulk temperature have been made approximately every 2 min from four permanently moored buoys since mid-1999. Assessment involved using a radiative transfer model to propagate surface skin temperature measurements made at the time of the L5 overpass to predict the at-sensor radiance. The predicted radiance was then convolved with the L5B6 system response function to obtain the predicted L5B6 radiance, which was then compared with the radiance measured by L5B6. Twenty-four cloud-free scenes acquired between 1999 and 2003 were used in the analysis with scene temperatures ranging between 4/spl deg/C and 22/spl deg/C. The results indicate L5B6 had a radiance bias of 2.5% (1.6/spl deg/C) in late 1999, which gradually decreased to 0.8% (0.5/spl deg/C) in mid-2002. Since that time, the bias has remained positive (predicted minus measured) and between 0.3% (0.2/spl deg/C) and 1.4% (0.9/spl deg/C). The cause for the cold bias (L5 radiances are lower than expected) is unresolved, but likely related to changes in instrument temperature associated with changes in instrument usage. The in situ data were then used to develop algorithms to recover the skin and bulk temperature of the water by regressing the L5B6 radiance and the National Center for Environmental Prediction (NCEP) total column water data to either the skin or bulk temperature. Use of the NCEP data provides an alternative approach to the split-window approach used with instruments that have two thermal infrared bands. The results indicate the surface skin and bulk temperature can be recovered with a standard error of 0.6/spl deg/C. This error is larger than errors obtained with other instruments due, in part, to the calibration bias. L5 provides the only long-duration high spatial resolution thermal infrared measurements of the land surface. If these data are to be used effectively in studies designed to monitor change, it is essential to continue to monitor instrument performance in-flight and develop quantitative algorithms for recovering surface temperature.


IEEE Transactions on Geoscience and Remote Sensing | 2008

Updated Radiometric Calibration for the Landsat-5 Thematic Mapper Reflective Bands

Dennis L. Helder; Brian L. Markham; Kurtis J. Thome; Julia A. Barsi; Gyanesh Chander; Rimy Malla

The Landsat-5 Thematic Mapper (TM) has been the workhorse of the Landsat system. Launched in 1984, it continues collecting data through the time frame of this paper. Thus, it provides an invaluable link to the past history of the land features of the Earths surface, and it becomes imperative to provide an accurate radiometric calibration of the reflective bands to the user community. Previous calibration has been based on information obtained from prelaunch, the onboard calibrator, vicarious calibration attempts, and cross-calibration with Landsat-7. Currently, additional data sources are available to improve this calibration. Specifically, improvements in vicarious calibration methods and development of the use of pseudoinvariant sites for trending provide two additional independent calibration sources. The use of these additional estimates has resulted in a consistent calibration approach that ties together all of the available calibration data sources. Results from this analysis indicate a simple exponential, or a constant model may be used for all bands throughout the lifetime of Landsat-5 TM. Where previously time constants for the exponential models were approximately one year, the updated model has significantly longer time constants in bands 1-3. In contrast, bands 4, 5, and 7 are shown to be best modeled by a constant. The models proposed in this paper indicate calibration knowledge of 5% or better early in life, decreasing to nearly 2% later in life. These models have been implemented at the U.S. Geological survey earth resources observation and science (EROS) and are the default calibration used for all Landsat TM data now distributed through EROS.


IEEE Geoscience and Remote Sensing Letters | 2007

Landsat-5 Thematic Mapper Thermal Band Calibration Update

Julia A. Barsi; Simon J. Hook; John R. Schott; Nina G. Raqueno; Brian L. Markham

The Landsat-5 thematic mapper (TM) has been operational since 1984. For much of its life, the calibration of TM has been neglected, but recent efforts are attempting to monitor stability and absolute calibration. This letter focuses on the calibration of the TM thermal band from 1999 to the present. Initial studies in the first two years of the TM mission showed that the thermal band was calibrated within the error in the calibration process (plusmn 0.9 K at 300 K). The calibration was not rigorously monitored again until 1999. While the internal calibrator has behaved as expected, recent vicarious calibration results show a significant offset error of 0.092 W/m2 ldr sr ldr mum or about 0.68 K at 300 K. This offset error was corrected on April 2, 2007 within the U.S. processing system through the modification of a calibration coefficient for all data acquired on or after April 1, 1999. Users can correct their own Level-1 data processed prior to April 2, 2007, by adding 0.092 W/m2 ldr sr ldr mum to their radiance level products. The state of the calibration between 1985 and 1999 is unknown; no changes for data acquired in those years are being recommended here.

Collaboration


Dive into the Julia A. Barsi's collaboration.

Top Co-Authors

Avatar

Brian L. Markham

Goddard Space Flight Center

View shared research outputs
Top Co-Authors

Avatar

Dennis L. Helder

South Dakota State University

View shared research outputs
Top Co-Authors

Avatar

John R. Schott

Rochester Institute of Technology

View shared research outputs
Top Co-Authors

Avatar

Gyanesh Chander

United States Geological Survey

View shared research outputs
Top Co-Authors

Avatar

Simon J. Hook

California Institute of Technology

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Esad Micijevic

United States Geological Survey

View shared research outputs
Top Co-Authors

Avatar

Md. Obaidul Haque

United States Geological Survey

View shared research outputs
Top Co-Authors

Avatar

Pat L. Scaramuzza

United States Geological Survey

View shared research outputs
Top Co-Authors

Avatar

Ron Morfitt

United States Geological Survey

View shared research outputs
Researchain Logo
Decentralizing Knowledge