Glynn C. Hulley

Generating Consistent Land Surface Temperature and Emissivity Products Between ASTER and MODIS Data for Earth Science Research

Land surface temperature and emissivity (LST&E) products are generated by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on the National Aeronautics and Space Administrations Terra satellite. These products are generated at different spatial, spectral, and temporal resolutions, resulting in discrepancies between them that are difficult to quantify, compounded by the fact that different retrieval algorithms are used to produce them. The highest spatial resolution MODIS emissivity product currently produced is from the day/night algorithm, which has a spatial resolution of 5 km. The lack of a high-spatial-resolution emissivity product from MODIS limits the usefulness of the data for a variety of applications and limits utilization with higher resolution products such as those from ASTER. This paper aims to address this problem by using the ASTER Temperature Emissivity Separation (TES) algorithm, combined with an improved atmospheric correction method, to generate the LST&E products for MODIS at 1-km spatial resolution and for ASTER in a consistent manner. The rms differences between the ASTER and MODIS emissivities generated from TES over the southwestern U.S. were 0.013 at 8.6 μm and 0.0096 at 11 μm, with good correlations of up to 0.83. The validation with laboratory-measured sand samples from the Algodones and Kelso Dunes in CA showed a good agreement in spectral shape and magnitude, with mean emissivity differences in all bands of 0.009 and 0.010 for MODIS and ASTER, respectively. These differences are equivalent to approximately 0.6 K in the LST for a material at 300 K and at 11 μm.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) after fifteen years: Review of global products

Abstract The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a 15-channel imaging instrument operating on NASA’s Terra satellite. A joint project between the U.S. National Aeronautics and Space Administration and Japan’s Ministry of Economy, Trade, and Industry, ASTER has been acquiring data for 15 years, since March 2000. The archive now contains over 2.8 million scenes; for the majority of them, a stereo pair was collected using nadir and backward telescopes imaging in the NIR wavelength. The majority of users require only a few to a few dozen scenes for their work. Studies have ranged over numerous scientific disciplines, and many practical applications have benefited from ASTER’s unique data. A few researchers have been able to mine the entire ASTER archive, that is now global in extent due to the long duration of the mission. Six examples of global products are described in this contribution: the ASTER Global Digital Elevation Model (GDEM), the most complete, highest resolution DEM available to all users; the ASTER Emissivity Database (ASTER GED), a global 5-band emissivity map of the land surface; the ASTER Global Urban Area Map (AGURAM), a 15-m resolution database of over 3500 cities; the ASTER Volcano Archive (AVA), an archive of over 1500 active volcanoes; ASTER Geoscience products of the continent of Australia; and the Global Ice Monitoring from Space (GLIMS) project.

The ASTER Global Emissivity Dataset (ASTER GED): Mapping Earth's emissivity at 100 meter spatial scale

Thermal infrared (TIR) data, acquired by instruments on several NASA satellite platforms, are primarily used to estimate the surface temperature/emissivity of the Earths land surface. One such instrument launched on NASAs Terra satellite in 1999 is the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), which has a spatial resolution of 90 m. Using ASTER data, NASA/Jet Propulsion Laboratory recently released the most detailed emissivity map of the Earth termed the ASTER Global Emissivity Dataset (ASTER GED) that was acquired by processing millions of cloud free ASTER scenes from 2000 to 2008. The ASTER GEDv3 provides an average emissivity at ~100 m and ~1 km, while GEDv4 provides a monthly emissivity from 2000 to 2015 at ~5 km spatial resolution in the wavelength range between 8 and 12 µm. Validation with lab spectra from four desert sites resulted in an average absolute band error of ~1%, compared to current heritage MODIS products that had average absolute errors of 2.4% (Collection 4) and 4.6% (Collection 5).

Directional Viewing Effects on Satellite Land Surface Temperature Products Over Sparse Vegetation Canopies—A Multisensor Analysis

Thermal infrared satellite observations of the Earths surface are key components in estimating the surface skin temperature over global land areas. However, depending on sun illumination and viewing directional configurations, satellites measure different surface radiometric temperatures, particularly over sparsely vegetated regions where the radiometric contributions from soil and vegetation vary with the sun and viewing geometry. Over an oak tree woodland located near the town of Evora, Portugal, we compare different satellite-based land surface temperature (LST) products from the Moderate Resolution Imaging Spectroradiometer on board the Terra and Aqua polar-orbiting satellites and from the Spinning Enhanced Visible and Infrared Imager on board the geostationary Meteosat satellite with ground-based LST. The observed differences between LSTs derived from polar and geostationary satellites are up to 12 K due to directional effects. In this letter, we develop a methodology based on a radiative transfer model and dedicated field radiometric measurements to interpret and validate directional remote sensing measurements. The methodology is used to estimate the quantitative uncertainty in LST products derived from polar-orbiting satellites over a sparse vegetation canopy.

Airborne methane remote measurements reveal heavy-tail flux distribution in Four Corners region

Significance Fugitive methane emissions are thought to often exhibit a heavy-tail distribution (more high-emission sources than expected in a normal distribution), and thus efficient mitigation is possible if we locate the strongest emitters. Here we demonstrate airborne remote measurements of methane plumes at 1- to 3-m ground resolution over the Four Corners region. We identified more than 250 point sources, whose emissions followed a lognormal distribution, a heavy-tail characteristic. The top 10% of emitters explain about half of the total observed point source contribution and ∼1/4 the total basin emissions. This work demonstrates the capability of real-time airborne imaging spectroscopy to perform detection and categorization of methane point sources in extended geographical areas with immediate input for emissions abatement. Methane (CH4) impacts climate as the second strongest anthropogenic greenhouse gas and air quality by influencing tropospheric ozone levels. Space-based observations have identified the Four Corners region in the Southwest United States as an area of large CH4 enhancements. We conducted an airborne campaign in Four Corners during April 2015 with the next-generation Airborne Visible/Infrared Imaging Spectrometer (near-infrared) and Hyperspectral Thermal Emission Spectrometer (thermal infrared) imaging spectrometers to better understand the source of methane by measuring methane plumes at 1- to 3-m spatial resolution. Our analysis detected more than 250 individual methane plumes from fossil fuel harvesting, processing, and distributing infrastructures, spanning an emission range from the detection limit ∼ 2 kg/h to 5 kg/h through ∼ 5,000 kg/h. Observed sources include gas processing facilities, storage tanks, pipeline leaks, and well pads, as well as a coal mine venting shaft. Overall, plume enhancements and inferred fluxes follow a lognormal distribution, with the top 10% emitters contributing 49 to 66% to the inferred total point source flux of 0.23 Tg/y to 0.39 Tg/y. With the observed confirmation of a lognormal emission distribution, this airborne observing strategy and its ability to locate previously unknown point sources in real time provides an efficient and effective method to identify and mitigate major emissions contributors over a wide geographic area. With improved instrumentation, this capability scales to spaceborne applications [Thompson DR, et al. (2016) Geophys Res Lett 43(12):6571–6578]. Further illustration of this potential is demonstrated with two detected, confirmed, and repaired pipeline leaks during the campaign.

Temperature and Emissivity Separation From MSG/SEVIRI Data

In this paper, we analyze the feasibility of applying the temperature and emissivity separation (TES) algorithm to thermal-infrared data acquired with three bands of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation platform (SEVTES). The performance of the SEVTES algorithm was tested using data simulated over different atmospheric conditions and surface emissivities, with errors around 1.5% for emissivity and 1.5 K for temperature when atmospheric correction is accurate enough. In contrast, errors on land-leaving radiances higher than 2% or uncertainties on total atmospheric water vapor amount higher than 5% lead to errors on emissivity higher than 2% and errors on land surface temperature higher than 3 K, especially when the atmospheric absorption is overestimated. SEVIRI data acquired in August 2011 were also used to validate SEVTES emissivities against in situ measurements collected in five different homogeneous areas over Africa. Values were also intercompared to Moderate Resolution Imaging Spectroradiometer (MODIS)-derived and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)-derived emissivities and to the LSA SAF emissivity product. Results show that SEVTES-derived emissivity values are consistent with MODIS-TES and ASTER-TES retrievals and that SEVTES also improves the retrievals included in LSA SAF and MOD11Cx v5 products. When compared to laboratory measurements, accuracies of around 1%-2% were obtained, although occasional inaccuracies (2%-3%) were also found in some cases at band 8.7 μm. The results presented in this paper show the potential SEVTES has for improving the LSA SAF product over arid and semiarid areas.

A Physics-Based Algorithm for the Simultaneous Retrieval of Land Surface Temperature and Emissivity From VIIRS Thermal Infrared Data

Land surface temperature (LST) is a key climate variable for studying the energy and water balance of the earth surface and monitoring the effects of climate change. This paper presents a physics-based temperature emissivity separation (TES) algorithm for the simultaneous retrieval of LST and emissivity (LST&E) from the thermal infrared bands of the Suomi National Polar-Orbiting Partnerships Visible Infrared Imaging Radiometer Suite (VIIRS) payload. The new VIIRS LST&E product (VNP21) was developed to provide continuity with the Moderate-Resolution Imaging Spectroradiometer (MODIS) equivalent LST&E product (MxD21) product, which is available in Collection 6, and to address inconsistencies between the current MODIS and VIIRS split-window LST products. The TES algorithm uses full radiative transfer simulations to isolate the surface emitted radiance, and an emissivity calibration curve based on the variability in the surface radiance data to dynamically retrieve both LST and spectral emissivity. Furthermore, an improved water vapor scaling model was implemented to improve the accuracy and stability of the atmospheric correction for conditions with high atmospheric water vapor content. An independent assessment of the VIIRS LST retrievals was performed against in situ LST measurements over two dedicated validation sites at Lake Tahoe and Salton Sea in the Southwestern USA, while the VIIRS emissivity retrievals were evaluated with the latest ASTER Global Emissivity Dataset Version 3 (GEDv3). The bias and root-mean-square error (RMSE) in retrieved VIIRS LST were 0.50 and 1.40 K, respectively for the two sites combined, while mean emissivity differences between VIIRS and ASTER GEDv3 were 0.2%, 0.1%, and 0.3% for bands M14 (

The Impacts of Precipitating Hydrometeors Radiative Effects on Land Surface Temperature in Contemporary GCMs using Satellite Observations

8.55~\mu \text{m}

Application of Landsat 8 for monitoring impacts of wastewater discharge on coastal water quality

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Remote gas plume sensing and imaging with NASA’s Hyperspectral Thermal Emission Spectrometer (HyTES).

10.76~\mu \text{m}