Nina G. Raqueno

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

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.

Calibration of Landsat thermal data and application to water resource studies

The newest in the Landsat series of satellites was launched April 15, 1999. The imagery collected by Landsat is used for a myriad of applications, from coral reef studies to land management. In order to take advantage of Landsat 7 data, the Enhanced Thematic Mapper+ (ETM+) instrument must be calibrated. This study focuses on the immediate postlaunch calibration verification of the Landsat 7 thermal band (Band 6), specifically so that it can be useful in water resource studies. Two years worth of thermal calibration results using a combination of underfiight data and ground truth show the ETM+ to be extremely stable, though the prelaunch calibration produces an offset of 0.261 W/m2 sr I¼m. This paper focuses on the details of the calibration process, including problems faced with ground truth instrumentation. While the technical emphasis in this paper is the calibration of Landsat thermal data, it is presented in the context of the water resource studies for which calibrated thermal data are required. At certain times in the year, water quality in large lakes, particularly the spatial structure of water quality, is driven by temperature of lake waters. During the spring warming, a phenomena called the thermal bar drives the current and sedimentation of large water bodies. A long-term goal of this study is to use thermally driven hydrodynamic models of lake processes to better understand and monitor water quality in large lakes. This paper presents the hydrodynamic model and the relationship between temperature and water quality in the Great Lakes as one example of why high-resolution, well-calibrated data are critical to earth observing. © 2001 Elsevier Science Inc. All rights reserved.

Landsat-5 Thematic Mapper Thermal Band Calibration Update

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.

Geospatial Disaster Response during the Haiti Earthquake: A Case Study Spanning Airborne Deployment, Data Collection, Transfer, Processing, and Dissemination

Immediately following the 12 January 2010 earthquake in Haiti, a disaster response team from Rochester Institute of Technology, ImageCat Inc., and Kucera International, funded by the Global Facility for Disaster Reduction and Recovery group of the World Bank, collected 0.15 m airborne imagery and two points/m2 lidar data for 650 km2 over a period of seven days. Data were transferred to Rochester, New York for processing at rates that approached 400 Mb/s using Internet2, ortho-rectified with a 24-hour turnaround, and distributed to response agencies through file or disk transfer. A unique response effort, dubbed the Global Earth Observation - Catastrophe Assessment Network (GEO-CAN) and headed by ImageCat, utilized over 600 experts from 23 different countries to generate rapid turnaround damage assessment products. This paper highlights the airborne data collection, transfer, processing, and product development effort, which arguably has raised the bar in terms of response to large-scale disasters.

The SHARE 2012 data campaign

A multi-modal (hyperspectral, multispectral, and LIDAR) imaging data collection campaign was conducted just south of Rochester New York in Avon, NY on September 20, 2012 by the Rochester Institute of Technology (RIT) in conjunction with SpecTIR, LLC, the Air Force Research Lab (AFRL), the Naval Research Lab (NRL), United Technologies Aerospace Systems (UTAS) and MITRE. The campaign was a follow on from the SpecTIR Hyperspectral Airborne Rochester Experiment (SHARE) from 2010. Data was collected in support of the eleven simultaneous experiments described here. The airborne imagery was collected over four different sites with hyperspectral, multispectral, and LIDAR sensors. The sites for data collection included Avon, NY, Conesus Lake, Hemlock Lake and forest, and a nearby quarry. Experiments included topics such as target unmixing, subpixel detection, material identification, impacts of illumination on materials, forest health, and in-water target detection. An extensive ground truthing effort was conducted in addition to collection of the airborne imagery. The ultimate goal of the data collection campaign is to provide the remote sensing community with a shareable resource to support future research. This paper details the experiments conducted and the data that was collected during this campaign.

SpecTIR hyperspectral airborne Rochester experiment data collection campaign

A multi-modal (hyperspectral, LiDAR, and multi-spectral) imaging data collection campaign was conducted at the Rochester Institute of Technology (RIT) in conjunction with SpecTIR, LLC, in the Rochester, New York, area July 26-29, 2010. The campaign was titled the SpecTIR Hyperspectral Airborne Rochester Experiment (SHARE) and collected data in support of nine simultaneous unique experiments, several of which leveraged data from multiple modalities. Airborne imagery was collected over the city of Rochester with hyperspectral, multispectral, and Light Detection and Ranging (LiDAR) sensors. Sites for data collection included the Genesee River, sections of downtown Rochester, and the RIT campus. Experiments included sub-pixel target detection, water quality monitoring, thermal vehicle tracking and wetlands health assessment. An extensive ground truthing effort was accomplished in addition to the airborne imagery collected. The ultimate goal of this comprehensive data collection campaign was to provide a community sharable resource that would support additional experiments. This paper details the experiments conducted and the corresponding data that were collected in conjunction with this campaign.

Development of an Operational Calibration Methodology for the Landsat Thermal Data Archive and Initial Testing of the Atmospheric Compensation Component of a Land Surface Temperature (LST) Product from the Archive

The Landsat program has been producing an archive of thermal imagery that spans the globe and covers 30 years of the thermal history of the planet at human scales (60–120 m). Most of that archive’s absolute radiometric calibration has been fixed through vicarious calibration techniques. These calibration ties to trusted values have often taken a year or more to gather sufficient data and, in some cases, it has been over a decade before calibration certainty has been established. With temperature being such a critical factor for all living systems and the ongoing concern over the impacts of climate change, NASA and the United States Geological Survey (USGS) are leading efforts to provide timely and accurate temperature data from the Landsat thermal data archive. This paper discusses two closely related advances that are critical steps toward providing timely and reliable temperature image maps from Landsat. The first advance involves the development and testing of an autonomous procedure for gathering and performing initial screening of large amounts of vicarious calibration data. The second advance discussed in this paper is the per-pixel atmospheric compensation of the data to permit calculation of the emitted surface radiance (using ancillary sources of emissivity data) and the corresponding land surface temperature (LST).

Megacollect 2004: hyperspectral collection experiment of terrestrial targets and backgrounds of the RIT Megascene and surrounding area (Rochester, New York)

This paper describes a collaborative collection campaign to spectrally image and measure a well characterized scene for hyperspectral algorithm development and validation/verification of scene simulation models (DIRSIG). The RIT Megascene, located in the northeast corner of Monroe County near Rochester, New York, has been modeled and characterized under the DIRSIG environment and has been simulated for various hyperspectral and multispectral systems (e.g., HYDICE, LANDSAT, etc.). Until recently, most of the electro-optical imagery of this area has been limited to very high altitude airborne or orbital platforms with low spatial resolutions. Megacollect 2004 addresses this shortcoming by bringing together, in June of 2004, a suite of airborne sensors to image this area in the VNIR, SWIR, MWIR, and LWIR regions. These include the COMPASS (hyperspectral VNIR,SWIR), SEBASS (hyperspectral LWIR), WASP (broadband VIS, SWIR, MWIR, LWIR) and MISI (hyperspectral VNIR, broadband SWIR, MWIR, LWIR). In conjunction with the airborne collections, an extensive ground truth measurement campaign was conducted to characterize atmospheric parameters, select targets, and backgrounds in the field. Laboratory measurements were also made on samples to confirm the field measurements. These spectral measurements spanned the visible and thermal region from 0.4 to 20 microns. These measurements will help identify imaging factors that affect algorithm robustness and areas of improvement in the physical modeling of scene/sensor phenomena. Reflectance panels have also been deployed as control targets to both quantify sensor characteristics and atmospheric effects. A subset of these targets have also been deployed as an independent test suite for target detection algorithms. Details of the planning, coordination, protocols, and execution of the campaign will be discussed with particular emphasis on the ground measurements. The system used to collect the metadata of ground truth measurements and disseminate this data will be described. Lastly, lessons learned in the field will be underscored to highlight additional measurements and changes in protocol to improve future collections of this area.

Landsat TM and ETM+ Thermal Band Calibration

Landsat-5 Thematic Mapper (TM) has been imaging the Earth since March 1984 and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) was added to the series of Landsat instruments in April 1999. The stability and calibration of the ETM+ has been monitored extensively since launch. Though not monitored for many years, TM now has a similar system in place to monitor stability and calibration. University teams have been evaluating the on-board calibration of the instruments through ground-based measurements since 1999. This paper considers the calibration efforts for the thermal band, Band 6, of both the Landsat-5 and Landsat-7 instruments. Initial calibration results for the Landsat-7 ETM+ thermal band found a bias error which was corrected through changes in the processing systems in late 2000. Recent results are suggesting a calibration error in gain, apparent with high temperature targets. For typical earth temperature targets, from about 5-20C, the gain error is small enough to be within the noise of the vicarious calibration process. However, for very high temperature targets (greater then 35C), Landsat-7 appears to be predicting several degrees too low. Questions remain on whether the change happened suddenly or is varying slowly, so the team will wait for another collection season before making any updates to the calibration. The calibration efforts for Landsat-5 TM considers only data collected since 1999, though there are efforts underway to extend the calibration history prior to the Landsat-7 launch. The latest data suggests that the Landsat-5 thermal band has a bias error of about 0.65K too low since 1999. Studies early in the life of Landsat-5 show that the instrument was calibrated within the error of the calibration process. It is impossible to tell, at this point, when or how the change in bias may have occurred. A correction will be calculated and implemented in the US processing system in 2006 for data acquired since April 1999.

High-resolution and LIDAR imaging support to the Haiti earthquake relief effort

The Wildfire Airborne Sensor Program (WASP) is an imaging system designed, built, and operated by the RIT Center for Imaging Science. The system consists of four cameras: a high resolution color camera and SWIR, MWIR, and LWIR cameras. When flown with our corporate partners, Kucera International, the imaging system is combined with a high-resolution LIDAR. This combination provides a full-spectrum, multimodal data collection platform unique to RIT. Under funding by the World Bank, the WASP system was used to image over 250 sq. mi. in Haiti (approximately 15,000 visible and 45,000 infrared frames) from January 21 - 27, 2010 in support of the earthquake relief efforts. Priorities of collection were the area surrounding Port au Prince, the city of Leogane, several other badly damaged towns, and, at the request of the USGS, a high resolution LIDAR collection over the fault line. The imagery was used in the field by disaster relief workers and by collaborators at the University of Buffalo and ImageCat, Inc. to perform building damage and road network trafficability assessments. Additionally, large area mosaics and semi-automatic processing algorithms were developed for value-added product development. In particular, a methodology was developed to extract the locations of blue tarps (indicative of displaced persons) from the images. All imagery was made available to the public through outlets such as Google Earth, the University of Buffalo, the US Geological Survey, the United Nations, and other sites.