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Markham, Brian

Publications and source records attributed to Markham, Brian.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Landsat 9: Mission Status and Prelaunch Instrument Performance Characterization and Calibration

Landsat 9 is currently under development as a joint effort between NASA and the United States Geological Survey (USGS). Landsat 9 is essentially a rebuild of Landsat 8 and has the same two sensors, the Operational Land Imager (OLI) and the Thermal Imaging Sensor (TIRS). The OLI-2 on Landsat 9, is being built by Ball Aerospace and has completed its pre-launch characterization and calibration and is scheduled to be delivered in the summer of 2019. The TIRS-2, being built by Goddard Space Flight Center, is currently undergoing testing through Spring 2019 and also scheduled for summer 2019 delivery. Several improvements to the characterization of both instruments have been incorporated into the testing plan, including improved spectral and radiometric characterization. The instruments will then be integrated onto the spacecraft being built by Northrop Grumman Innovation Systems (NGIS). The mission is targeted to launch as early as December 2020 on an Atlas-5.

Markham, Brian↗
NASA NTRS2019

First Results from Laser-Based Spectral Characterization of Landsat 9 Operational Land Imager-2

Landsat 9 will continue the Landsat data record into its fifth decade with launch scheduled for December 2020. The two instruments on Landsat 9 are Thermal Infrared Sensor-2 (TIRS-2) and Operational Land Imager-2 (OLI-2). OLI-2 is a nine-channel pushbroom imager with a 15-degree field of view that will have a 16-day measurement cadence from its nominal 705-km orbit altitude. A key aspect of the data that will be produced by OLI-2 is its spectral fidelity which enables countless science applications. The prelaunch test campaign for spectral characterization of OLI-2 was substantially improved relative to the methodology used for OLI: the full spectral response of every detector was characterized with greater accuracy, sampling, and precision. This paper will describe how this was accomplished with a tunable laser-based light source called Goddard Laser for Absolute Measurement of Radiance (GLAMR).

tunable laser↗
NASA NTRS2019

Landsat 9: Mission Status and Prelaunch Instrument Performance Characterization and Calibration

Landsat 9 is currently under development as a joint effort between NASA and the United States Geological Survey (USGS). Landsat 9 is essentially a rebuild of Landsat 8 and has the same two sensors, the Operational Land Imager (OLI) and the Thermal Imaging Sensor (TIRS). The OLI-2 on Landsat 9, is being built by Ball Aerospace and has completed its pre-launch characterization and calibration and is scheduled to be delivered in the summer of 2019. The TIRS-2, being built by Goddard Space Flight Center, is currently undergoing testing through Spring 2019 and also scheduled for summer 2019 delivery. Several improvements to the characterization of both instruments have been incorporated into the testing plan, including improved spectral and radiometric characterization. The instruments will then be integrated onto the spacecraft being built by Northrop Grumman Innovation Systems (NGIS). The mission is targeted to launch as early as December 2020 on an Atlas-5.

Markham, Brian↗
NASA NTRS2018

Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability

Combining data from multiple sensors into a single seamless time series, also known as data interoperability, has the potential for unlocking new understanding of how the Earth functions as a system. However, our ability to produce these advanced data sets is hampered by the differences in design and function of the various optical remote-sensing satellite systems. A key factor is the impact that calibration of these instruments has on data interoperability. To address this issue, a workshop with a panel of experts was convened in conjunction with the Pecora 20 conference to focus on data interoperability between Landsat and the Sentinel 2 sensors. Four major areas of recommendation were the outcome of the workshop. The first was to improve communications between satellite agencies and the remote-sensing community. The second was to adopt a collections-based approach to processing the data. As expected, a third recommendation was to improve calibration methodologies in several specific areas. Lastly, and the most ambitious of the four, was to develop a comprehensive process for validating surface reflectance products produced from the data sets. Collectively, these recommendations have significant potential for improving satellite sensor calibration in a focused manner that can directly catalyze efforts to develop data that are closer to being seamlessly interoperable.

calibration; geometric; radiometric; Landsat; Sent↗
NASA NTRS2017

Landsat 8 Remote Sensing Reflectance (Rrs) Products: Evaluations, Intercomparisons, and Enhancements

The Operational Land Imager (OLI) onboard Landsat-8 is generating high-quality aquatic science products, the most critical of which is the remote sensing reflectance (Rrs), defined as the ratio of water-leaving radiance to the total downwelling irradiance just above water. The quality of the Rrs products has not, however, been extensively assessed. This manuscript provides a comprehensive evaluation of Level-1B, i.e., top of atmosphere reflectance, and Rrs products available from OLI imagery under near-ideal atmospheric conditions in moderately turbid waters. The procedure includes a) evaluations of the Rrs products at sites included in the Ocean Color component of the Aerosol Robotic Network (AERONET-OC), b) intercomparisons and cross-calibrations against other ocean color products, and c) optimizations of vicarious calibration gains across the entire OLI observing swath. Results indicate that the near-infrared and shortwave infrared (NIR-SWIR) band combinations yield the most robust and stable Rrs retrievals in moderately turbid waters. Intercomparisons against products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODISA) indicate slight across-track non-uniformities (<1%) associated with OLI scenes in the blue bands. In both product domains (TOA and Rrs), on average, the OLI products were found larger in radiometric responses in the blue channels. Following the implementation of updated vicarious calibration gains and accounting for across-track non-uniformities, matchup analyses using independent in-situ validation data confirmed improvements in Rrs products. These findings further support high-fidelity OLI-derived aquatic science products in terms of both demonstrating a robust atmospheric correction method and providing consistent products across OLI's imaging swath.

Pahlevan, Nima↗
NASA NTRS2015

Landsat-8 Sensor Characterization and Calibration

Landsat-8 was launched on 11 February 2013 with two new Earth Imaging sensors to provide a continued data record with the previous Landsats. For Landsat-8, pushbroom technology was adopted, and the reflective bands and thermal bands were split into two instruments. The Operational Land Imager (OLI) is the reflective band sensor and the Thermal Infrared Sensor (TIRS), the thermal. In addition to these fundamental changes, bands were added, spectral bandpasses were refined, dynamic range and data quantization were improved, and numerous other enhancements were implemented. As in previous Landsat missions, the National Aeronautics and Space Administration (NASA) and United States Geological Survey (USGS) cooperated in the development, launch and operation of the Landsat- 8 mission. One key aspect of this cooperation was in the characterization and calibration of the instruments and their data. This Special Issue documents the efforts of the joint USGS and NASA calibration team and affiliates to characterize the new sensors and their data for the benefit of the scientific and application users of the Landsat archive. A key scientific use of Landsat data is to assess changes in the land-use and land cover of the Earth's surface over the now 43-year record. In order to perform these analyses and avoid confusing sensor changes with Earth surface changes, a solid understanding of the sensors' performance, consistent geolocation and radiometry are essential. Particularly with the significant changes in the Landsat-8 sensors relative to previous Landsat missions, this characterization becomes all the more important.

Radiometry↗
NASA NTRS2011

OLI Radiometric Calibration

Goals: (1) Present an overview of the pre-launch radiance, reflectance & uniformity calibration of the Operational Land Imager (OLI) (1a) Transfer to orbit/heliostat (1b) Linearity (2) Discuss on-orbit plans for radiance, reflectance and uniformity calibration of the OLI

Markham, Brian↗
NASA NTRS2011

The OLI Radiometric Scale Realization Round Robin Measurement Campaign

A round robin radiometric scale realization was performed at the Ball Aerospace Radiometric Calibration Laboratory in January/February 2011 in support of the Operational Land Imager (OLI) Program. Participants included Ball Aerospace, NIST, NASA Goddard Space Flight Center, and the University of Arizona. The eight day campaign included multiple observations of three integrating sphere sources by nine radiometers. The objective of the campaign was to validate the radiance calibration uncertainty ascribed to the integrating sphere used to calibrate the OLI instrument. The instrument level calibration source uncertainty was validated by quatnifying: (1) the long term stability of the NIST calibrated radiance artifact, (2) the responsivity scale of the Ball Aerospace transfer radiometer and (3) the operational characteristics of the large integrating sphere.

Cutlip, Hansford↗
NASA NTRS2011

The Landsat Data Continuity Mission Operational Land Imager: Radiometric Performance

The Operational Land Imager (OLI) is one of two instruments to fly on the Landsat Data Continuity Mission (LDCM), which is scheduled to launch in December 2012 to become the 8th in the series of Landsat satellites. The OLI images in the solar reflective part of the spectrum, with bands similar to bands 1-5, 7 and the panchromatic band on the Landsat-7 ETM+ instrument. In addition, it has a 20 nm bandpass spectral band at 443 nm for coastal and aerosol studies and a 30 nm band at 1375 nm to aid in cirrus cloud detection. Like ETM+, spatial resolution is 30 m in the all but the panchromatic band, which is 15 meters. OLI is a pushbroom radiometer with approximately 6000 detectors per 30 meter band as opposed to the 16 detectors per band on the whiskbroom ETM+. Data are quantized to 12 bits on OLI as opposed to 8 bits on ETM+ to take advantage of the improved signal to noise ratio provided by the pushbroom design. The saturation radiances are higher on OLI than ETM+ to effectively eliminate saturation issues over bright Earth targets. OLI includes dual solar diffusers for on-orbit absolute and relative (detector to detector) radiometric calibration. Additionally, OLI has 3 sets of on-board lamps that illuminate the OLI focal plane through the full optical system, providing additional checks on the OLI's response[l]. OLI has been designed and built by Ball Aerospace & Technology Corp. (BATC) and is currently undergoing testing and calibration in preparation for delivery in Spring 2011. Final pre-launch performance results should be available in time for presentation at the conference. Preliminary results will be presented below. These results are based on the performance of the Engineering Development Unit (EDU) that was radiometrically tested at the integrated instrument level in 2010 and assembly level measurements made on the flight unit. Signal-to-Noise (SNR) performance: One of the advantages of a pushbroom system is the increased dwell time of the detectors allowing for significantly higher SNR than equivalent aperture whiskbroom systems. OLI performance based on the EDU at the "typical" radiance level as specified in the OLI requirements document are about 10 times better than ETM+ performance and 2-3 times better than the requirements for OLI (Table 1).

Markham, Brian↗
NASA NTRS2011

Landsat Data Continuity Mission

The Landsat Data Continuity Mission (LDCM) is currently under development and is on schedule to launch the 8th satellite in the Landsat series in December of 2012. LDCM is a joint project between the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS). NASA is responsible for developing and launching the flight hardware and on-orbit commissioning and USGS is responsible for developing the ground system and operating the system onorbit after commissioning. Key components of the flight hardware are the Operational Land Imager (OLI), nearing completion by Ball Aerospace & Technologies Corp in Boulder, CO, the Thermal Infrared Sensor (TIRS), being built by NASA's Goddard Space Flight Center and the spacecraft, undergoing integration at Orbital Sciences Corp in Gilbert, Arizona. The launch vehicle will be an Atlas-5 with launch services provided by NASA's Kennedy Space Center. Key ground systems elements are the Mission Operations Element, being developed by the Hammers Corporation, and the Collection Activity Planning Element, Ground Network Element, and Data Processing and Archive System, being developed internally by the USGS Earth Resources Observations and Science (EROS) Center. The primary measurement goal of LDCM is to continue the global coverage of moderate spatial resolution imagery providing continuity with the existing Landsat record. The science goal for this imagery is to monitor land use and land cover, particularly as it relates to global climate change. Together the OLI and TIRS instruments on LDCM replace the ETM+ instrument on Landsat-7 with significant enhancements. The OLI is a pushbroom design instrument where the scanning mechanism of the ETM+ is effectively replaced by a long line of detectors. The OLI has 9 spectral bands with similar spatial resolution to ETM+: 7 of them similar to the reflective spectral bands on ETM+ and two new bands. The two new bands cover (1) the shorter wavelength blue part of the spectrum to help with coastal studies and aerosol analyses/atmospheric correction and (2) an atmospheric water absorption band, where the Earth surface is generally not visible, but Cirrus clouds are, to aid in cloud detection and screening. The radiometry of OLI benefits from improved SNR, dynamic range and quantization. OLI is undergoing system testing with a delivery scheduled for Spring 2011. The TIRS is also a pushbroom design and used QWIPS detectors that require cooling to 43K using a cryocooler. It.has two spectral bands, effectively splitting the ETM+ band 6 in half, that can be used as a split window to aid in atmospheric correction. It has nominally 100 m spatial resolution as opposed to the 60 m of Landsat-7 ETM+: TIRS has commenced integration and test, with a delivery to the spacecraft vendor scheduled for Winter 2011-2012. The Orbital spacecraft currently being integrated for LDCM will have improved capabilities for pointing over previous missions. These capabilities will allow the OLI and TIRS instruments to point off-nadir the equivalent of one WRS-2 path to increase the chances of coverage for high priority targets, particularly in the event of natural disasters. Also, the pointing capability will allow the calibration of the OLI using the sun (roughly weekly), the moon (monthly), stars (during commissioning) and the Earth (at 90 deg from normal orientation, a.k.a., side slither) quarterly. The solar calibration will be used for OLI absolute and relative calibration, the moon for trending the stability of the OLI response, the stars will be used for Line of Sight determination and the side slither will be an alternate OLI and relative gain determination methodology. The spacecraft is scheduled to begin integration with the OLI instrument in Summer 2011. The LDCM data processing and archive system (DPAS), located at USGS EROS, generates the products for distribution to users. Like Landsat-7 this includes an image assessment system for characrizing instrument performance and updating calibration parameters. Products will be generated that include the spectral bands from both instruments, terrain corrected and registered to the geoid. Also, like Landsat-7, data products will be distributed at no charge to the user. The current status and plans of the space and ground segments of the LDCM project will be presented along with performance predictions as available. More detailed information on the two instruments is intended to be presented in separate papers.

Markham, Brian↗
NASA NTRS2011

Forty-Year Calibrated Record of Earth-Surface Reflected Radiance from Landsat: A Review

Sensors on Landsat satellites have been collecting images of the Earth's surface for nearly 40 years. These images have been invaluable for characterizing and detecting changes in the land cover and land use of the world. Although initially conceived as primarily picture generating sensors, even the early sensors were radiometrically calibrated and spectrally characterized prior to launch and incorporated some capabilities to monitor their radiometric calibration once on orbit. Recently, as the focus of studies has shifted to monitoring Earth surface parameters over significant periods of time, serious attention has been focused toward bringing the data from all these sensors onto a common radiometric scale over this 40-year period. This effort started with the most recent systems and then was extended back in time. Landsat-7 ETM+, the best-characterized sensor of the series prior to launch and once on orbit, and the most stable system to date, was chosen to serve as the reference. The Landsat-7 project was the first of the series to build an image assessment system into its ground system, allowing systematic characterization of its sensors and data. Second, the Landsat-5 TM (still operating at the time of the Landsat-7 launch and continues to operate) calibration history was reconstructed based on its internal calibrator, vicarious calibrations, pseudo-invariant sites and a tie to Landsat-7 ETM+ at the time of the commissioning of Landsat-7. This process was performed in two iterations: the earlier one relied primarily on the TM internal calibrator. When this was found to have some deficiencies, a revised calibration was based more on pseudo-invariant sites, though the internal calibrator was still used to establish the short-term variations in response due to icing build up on the cold focal plane. As time progressed, a capability to monitor the Landsat-5 TM was added to the image assessment system. The Landsat-4 TM, which operated from 1982-1992, was the third system to which the radiometric scale was extended. The limited and broken use of the Landsat-4 TM made this analysis more difficult. Eight-day separated image pairs from Landsat-5 combined with analysis of pseudo invariant sites established this history. The fourth and most challenging effort was making the Landsat-1 to -5 MSS sensors' data internally radiometrically consistent. This effort was particularly complicated by the age of the MSS data, varying formats and processing levels in the archive, limited datasets, and limited documentation available. Ultimately, pseudo-invariant sites were identified in North America and used for this effort. Note that most of the Landsat-MSS archived data had already been calibrated using the MSS internal calibrators, so this processing was imbedded in the result. The final effort was developing an absolute scale for Landsat MSS similar to what was already established for the "TM" sensors. This was accomplished by using simultaneous data from Landsat-5 MSS and Landsat-5 TM, accounting for spectral differences between the sensors using EO-1 Hyperion data. The recalibrated history of the Landsat data and implications to users are discussed. The key result from this work is a consistently calibrated Landsat data archive that spans nearly 40 years with total uncertainties on the order of 10% or less for most sensors and bands.

Markham, Brian↗