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Ron Morfitt

Publications and source records attributed to Ron Morfitt.

9 recordsLinked to original sources
USGS2017

Landsat-8 TIRS thermal radiometric calibration status

The Thermal Infrared Sensor (TIRS) instrument is the thermal-band imager on the Landsat-8 platform. The initial onorbit calibration estimates of the two TIRS spectral bands indicated large average radiometric calibration errors, -0.29 and -0.51 W/m 2 sr μm or -2.1K and -4.4K at 300K in Bands 10 and 11, respectively, as well as high variability in the errors, 0.87K and 1.67K (1-σ), respectively. The average error was corrected in operational processing in January 2014, though, this adjustment did not improve the variability. The source of the variability was determined to be stray light from far outside the field of view of the telescope. An algorithm for modeling the stray light effect was developed and implemented in the Landsat-8 processing system in February 2017. The new process has improved the overall calibration of the two TIRS bands, reducing the residual variability in the calibration from 0.87K to 0.51K at 300K for Band 10 and from 1.67K to 0.84K at 300K for Band 11. There are residual average lifetime bias errors in each band: 0.04 W/m 2 sr μm (0.30K) and -0.04 W/m 2 sr μm (-0.29K), for Bands 10 and 11, respectively.

Conference Paper↗
USGS2015

Landsat-8 Operational Land Imager (OLI) radiometric performance on-orbit

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.

Remote Sensing↗
USGS2014

On-orbit performance of the Landsat 8 Operational Land Imager

The Landsat 8 satellite was launched on February 11, 2013, to systematically collect multispectral images for detection and quantitative analysis of changes on the Earth’s surface. The collected data are stored at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and continue the longest archive of medium resolution Earth images. There are two imaging instruments onboard the satellite: the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS). This paper summarizes radiometric performance of the OLI including the bias stability, the system noise, saturation and other artifacts observed in its data during the first 1.5 years on orbit. Detector noise levels remain low and Signal-To-Noise Ratio high, largely exceeding the requirements. Impulse noise and saturation are present in imagery, but have negligible effect on Landsat 8 products. Oversaturation happens occasionally, but the affected detectors quickly restore their nominal responsivity. Overall, the OLI performs very well on orbit and provides high quality products to the user community. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Conference Paper↗
USGS2011

Landsat 8 on-orbit characterization and calibration system

The Landsat Data Continuity Mission (LDCM) is planning to launch the Landsat 8 satellite in December 2012, which continues an uninterrupted record of consistently calibrated globally acquired multispectral images of the Earth started in 1972. The satellite will carry two imaging sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will provide visible, near-infrared and short-wave infrared data in nine spectral bands while the TIRS will acquire thermal infrared data in two bands. Both sensors have a pushbroom design and consequently, each has a large number of detectors to be characterized. Image and calibration data downlinked from the satellite will be processed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center using the Landsat 8 Image Assessment System (IAS), a component of the Ground System. In addition to extracting statistics from all Earth images acquired, the IAS will process and trend results from analysis of special calibration acquisitions, such as solar diffuser, lunar, shutter, night, lamp and blackbody data, and preselected calibration sites. The trended data will be systematically processed and analyzed, and calibration and characterization parameters will be updated using both automatic and customized manual tools. This paper describes the analysis tools and the system developed to monitor and characterize on-orbit performance and calibrate the Landsat 8 sensors and image data products.

Conference Paper↗
USGS2011

Bias estimation for the Landsat 8 operational land imager

The Operational Land Imager (OLI) is a pushbroom sensor that will be a part of the Landsat Data Continuity Mission (LDCM). This instrument is the latest in the line of Landsat imagers, and will continue to expand the archive of calibrated earth imagery. An important step in producing a calibrated image from instrument data is accurately accounting for the bias of the imaging detectors. Bias variability is one factor that contributes to error in bias estimation for OLI. Typically, the bias is simply estimated by averaging dark data on a per-detector basis. However, data acquired during OLI pre-launch testing exhibited bias variation that correlated well with the variation in concurrently collected data from a special set of detectors on the focal plane. These detectors are sensitive to certain electronic effects but not directly to incoming electromagnetic radiation. A method of using data from these special detectors to estimate the bias of the imaging detectors was developed, but found not to be beneficial at typical radiance levels as the detectors respond slightly when the focal plane is illuminated. In addition to bias variability, a systematic bias error is introduced by the truncation performed by the spacecraft of the 14-bit instrument data to 12-bit integers. This systematic error can be estimated and removed on average, but the per pixel quantization error remains. This paper describes the variability of the bias, the effectiveness of a new approach to estimate and compensate for it, as well as the errors due to truncation and how they are reduced.

Conference Paper↗
USGS2010

Operational calibration and validation of landsat data continuity mission (LDCM) sensors using the image assessment system (IAS)

Systematic characterization and calibration of the Landsat sensors and the assessment of image data quality are performed using the Image Assessment System (IAS). The IAS was first introduced as an element of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) ground segment and recently extended to Landsat 4 (L4) and 5 (L5) Thematic Mappers (TM) and Multispectral Sensors (MSS) on-board the Landsat 1-5 satellites. In preparation for the Landsat Data Continuity Mission (LDCM), the IAS was developed for the Earth Observer 1 (EO-1) Advanced Land Imager (ALI) with a capability to assess pushbroom sensors. This paper describes the LDCM version of the IAS and how it relates to unique calibration and validation attributes of its on-board imaging sensors. The LDCM IAS system will have to handle a significantly larger number of detectors and the associated database than the previous IAS versions. An additional challenge is that the LDCM IAS must handle data from two sensors, as the LDCM products will combine the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) spectral bands.

Conference Paper↗
USGS2001

Effects of Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper plus radiometric and geometric calibrations and corrections on landscape characterization

The Thematic Mapper (TM) instruments onboard Landsats 4 and 5 provide high-quality imagery appropriate for many different applications, including land cover mapping, landscape ecology, and change detection. Precise calibration was considered to be critical to the success of the Landsat 7 mission and, thus, issues of calibration were given high priority during the development of the Enhanced Thematic Mapper Plus (ETM+). Data sets from the Landsat 5 TM are not routinely corrected for a number of radiometric and geometric artifacts, including memory effect, gain/bias, and interfocal plane misalignment. In the current investigation, the effects of correcting vs. not correcting these factors were investigated for several applications. Gain/bias calibrations were found to have a greater impact on most applications than did memory effect calibrations. Correcting interfocal plane offsets was found to have a moderate effect on applications. On June 2, 1999, Landsats 5 and 7 data were acquired nearly simultaneously over a study site in the Niobrara, NE area. Field radiometer data acquired at that site were used to facilitate crosscalibrations of Landsats 5 and 7 data. Current findings and results from previous investigations indicate that the internal calibrator of Landsat 5 TM tracked instrument gain well until 1988. After this, the internal calibrator diverged from the data derived from vicarious calibrations. Results from this study also indicate very good agreement between prelaunch measurements and vicarious calibration data for all Landsat 7 reflective bands except Band 4. Values are within about 3.5% of each other, except for Band 4, which differs by 10%. Coefficient of variation (CV) values derived from selected targets in the imagery were also analyzed. The Niobrara Landsat 7 imagery was found to have lower CV values than Landsat 5 data, implying that lower levels of noise characterize Landsat 7 data than current Landsat 5 data. It was also found that following radiometric normalization, the Normalized Difference Vegetation Index (NDVI) imagery and classification products of Landsats 5 and 7 were very similar. This implies that data from the two sensors can be used to measure and monitor the same landscape phenomena and that Landsats 5 and 7 data can be used interchangeably with proper caution. In addition, it was found that difference imagery produced using Landsat 7 ETM+ data are of excellent quality.

Remote Sensing of Environment↗
USGS2001

Landsat-7 ETM+ radiometric calibration: Two years on-orbit

Landsat-7 has been in orbit for 2 years as of April 15, 2001 and operationally providing calibrated data products for 2 years as of June 28, 2001. A radiometric calibration team consisting of scientists and analysts from the Landsat Project Science Office, the Landsat-7 Image Assessment System and four universities evaluates the calibration based on on-board and ground-look (vicarious) calibration methodologies. The results are assembled and compared semi-annually and the calibration parameter files are adjusted as necessary. To date the combined results for the reflective bands have not shown any change from pre-launch values. The pre-launch values continue to be used for data processing, with the uncertainty estimated at less than 5%. In the thermal band, the vicarious calibration results indicated a 0.31 W/m/sup 2/ sr /spl mu/m bias in the calibration. This bias results in the ETM+ derived temperatures being about 3K high. The calibration parameter file was updated October 1, 2000 to remove this bias, however the U.S. Landsat Product Generation System (LPGS) software required modification that was not incorporated until December 20, 2000. All LPGS data products generated since this date have the correct thermal band calibration, regardless of image acquisition date, with uncertainties at approximately the 1% level.

Conference Paper↗