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 micrometers (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/sq msrmicrometers 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/sq msrmicrometers 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

Land Surface Temperature Product Validation Best Practice Protocol Version 1.0 - October, 2017

The Global Climate Observing System (GCOS) has specified the need to systematically generate andvalidate Land Surface Temperature (LST) products. This document provides recommendations on goodpractices for the validation of LST products. Internationally accepted definitions of LST, emissivity andassociated quantities are provided to ensure the compatibility across products and reference data sets. Asurvey of current validation capabilities indicates that progress is being made in terms of up-scaling and insitu measurement methods, but there is insufficient standardization with respect to performing andreporting statistically robust comparisons.Four LST validation approaches are identified: (1) Ground-based validation, which involvescomparisons with LST obtained from ground-based radiance measurements; (2) Scene-based intercomparisonof current satellite LST products with a heritage LST products; (3) Radiance-based validation,which is based on radiative transfer calculations for known atmospheric profiles and land surface emissivity;(4) Time series comparisons, which are particularly useful for detecting problems that can occur during aninstrument's life, e.g. calibration drift or unrealistic outliers due to undetected clouds. Finally, the need foran open access facility for performing LST product validation as well as accessing reference LST datasets isidentified

AN APPROACH TO ESTIMATE GLOBAL BIOMASS BURNING EMISSIONS OF ORGANIC AND BLACK CARBON FROM MODIS FIRE RADIATIVE POWER

Biomass burning is an important global phenomenon affecting atmospheric composition with significant implications for climatic forcing. Wildland fire is the main global source of fine primary carbonaceous aerosols in the form of organic carbon (OC) and black carbon (BC), but uncertainty in aerosol emission estimates from biomass burning is still rather large. Application of satellite based measures of fire radiative power (FRP) has been demonstrated to offer an alternative approach to estimate biomass consumed with the potential to estimate the associated emissions from fires. To date, though, no study has derived integrated FRP (referred to as fire radiative energy or FRE) at a global scale, in part due to limitations in temporal or spatial resolution of satellite sensors. The main objective of this research was to quantify global biomass burning emissions of organic and black carbon aerosols and the corresponding effect on planetary radiative forcing. The approach is based on the geophysical relationship between the flux of FRE emitted, biomass consumed, and aerosol emissions. Aqua and Terra MODIS observations were used to estimate FRE using a simple model to parameterize the fire diurnal cycle based on the long term ratio between Terra and Aqua MODIS FRP and cases of diurnal satellite measurements of FRP made by the geostationary sensor SEVIRI, precessing sensor VIRS, and high latitude (and thus high overpass frequency) observations by MODIS. Investigation of the atmospheric attenuation of MODIS channels using a parametric model based on the MODTRAN radiative transfer model indicates a small bias in FRE estimates which was accounted for. Accuracy assessment shows that the FRE estimates are precise (R2 = 0.85), but may be underestimated. Global estimates of FRE show that Africa and South America dominate biomass burning, accounting for nearly 70% of the annual FRE generated. The relationship between FRE and OCBC estimates made with a new MODIS-derived inversion product of daily integrated biomass burning aerosol emissions was explored. The slope of the relationship within each of several biomes yielded a FRE-based emission factor. The biome specific emission factors and FRE monthly data were used to estimate OCBC emissions from fires on a global basis for 2001 to 2007. The annual average was 17.23 Tg which was comparable to previously published values, but slightly lower. The result in terms of global radiative forcing suggests a cooling effect at both the top-of-atmosphere (TOA) and surface approaching almost -0.5 K which implies that biomass burning aerosols could dampen the warming effect of green house gas emissions. An error budget was developed to explore the sources and total uncertainty in the OCBC estimation. The results yielded an uncertainty value of 58% with specific components of the process warranting future consideration and improvement. The uncertainty estimate does not demonstrate a significant improvement over current methods to estimate biomass burning aerosols, but given the simplicity of the approach should allow for refinements to be made with relative ease

An Integrated physics-based approach to demonstrate the potential of the Landsat Data Continuity Mission (LDCM) for monitoring coastal/inland waters

Monitoring coastal or inland waters, recognized as case II waters, using the existing Landsat technology is somewhat restricted because of its low Signal-to-Noise ratio (SNR) as well as its relatively poor radiometric resolution. As a primary task, we introduce a novel technique, which integrates the Landsat-7 data as a surrogate for LDCM with a 3D hydrodynamic model to monitor the dynamics of coastal waters near river discharges as well as in a small lake environment. The proposed approach leverages both the thermal and the reflective Landsat-7 imagery to calibrate the model and to retrieve the concentrations of optically active components of the water. To do so, the model is first calibrated by optimizing its thermal outputs with the surface temperature maps derived from the Landsat-7 data. The constituent retrieval is conducted in the second phase where multiple simulated concentration maps are provided to an in-water radiative transfer code (Hydrolight) to generate modeled surface reflectance maps. Prior to any remote sensing task, one has to ensure that a dataset comes from a well-calibrated imaging system. Although the calibration status of Landsat-7 has been regularly monitored over multiple desert sites, it was desired to evaluate its performance over dark waters relative to a well-calibrated instrument designed specifically for water studies. In the light of this, several Landsat- 7 images were cross-calibrated against the Terra-MODIS data over deep, dark waters whose optical properties remain relatively stable. This study is intended to lay the groundwork and provide a reference point for similar studies planned for the new Landsat. In an independent case study, the potential of the new Landsat sensor was examined using an EO-1 dataset and applying a spectral optimization approach over case II waters. The water constituent maps generated from the EO-1 imagery were compared against those derived from Landsat-7 to fully analyze the improvement levels pertaining to the new Landsat\u27s enhanced features in a water constituent retrieval framework