scholarly journals Compensation of Oxygen Transmittance Effects for Proximal Sensing Retrieval of Canopy–Leaving Sun–Induced Chlorophyll Fluorescence

2018 ◽  
Vol 10 (10) ◽  
pp. 1551 ◽  
Author(s):  
Neus Sabater ◽  
Jorge Vicent ◽  
Luis Alonso ◽  
Jochem Verrelst ◽  
Elizabeth Middleton ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Spectral Resolution ◽  
Transfer Functions ◽  
Spectral Response ◽  
High Spectral Resolution ◽  
Transfer Model ◽  
Atmospheric Effects ◽  
Proximal Sensing ◽  
Field Station ◽  
Absorption Features

Estimates of Sun–Induced vegetation chlorophyll Fluorescence (SIF) using remote sensing techniques are commonly determined by exploiting solar and/or telluric absorption features. When SIF is retrieved in the strong oxygen (O 2 ) absorption features, atmospheric effects must always be compensated. Whereas correction of atmospheric effects is a standard airborne or satellite data processing step, there is no consensus regarding whether it is required for SIF proximal–sensing measurements nor what is the best strategy to be followed. Thus, by using simulated data, this work provides a comprehensive analysis about how atmospheric effects impact SIF estimations on proximal sensing, regarding: (1) the sensor height above the vegetated canopy; (2) the SIF retrieval technique used, e.g., Fraunhofer Line Discriminator (FLD) family or Spectral Fitting Methods (SFM); and (3) the instrument’s spectral resolution. We demonstrate that for proximal–sensing scenarios compensating for atmospheric effects by simply introducing the O 2 transmittance function into the FLD or SFM formulations improves SIF estimations. However, these simplistic corrections still lead to inaccurate SIF estimations due to the multiplication of spectrally convolved atmospheric transfer functions with absorption features. Consequently, a more rigorous oxygen compensation strategy is proposed and assessed by following a classic airborne atmospheric correction scheme adapted to proximal sensing. This approach allows compensating for the O 2 absorption effects and, at the same time, convolving the high spectral resolution data according to the corresponding Instrumental Spectral Response Function (ISRF) through the use of an atmospheric radiative transfer model. Finally, due to the key role of O 2 absorption on the evaluated proximal–sensing SIF retrieval strategies, its dependency on surface pressure (p) and air temperature (T) was also assessed. As an example, we combined simulated spectral data with p and T measurements obtained for a one–year period in the Hyytiälä Forestry Field Station in Finland. Of importance hereby is that seasonal dynamics in terms of T and p, if not appropriately considered as part of the retrieval strategy, can result in erroneous SIF seasonal trends that mimic those of known dynamics for temperature–dependent physiological responses of vegetation.

scholarly journals Retrieval of Ice Cloud Properties from AIRS and MODIS Observations Based on a Fast High-Spectral-Resolution Radiative Transfer Model

2013 ◽  
Vol 52 (3) ◽  
pp. 710-726 ◽  
Author(s):  
Chenxi Wang ◽  
Ping Yang ◽  
Steven Platnick ◽  
Andrew K. Heidinger ◽  
Bryan A. Baum ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spectral Resolution ◽  
Spectral Response ◽  
Thermal Infrared ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Retrieval Method ◽  
Ice Cloud ◽  
Cloud Properties

AbstractA computationally efficient high-spectral-resolution cloudy-sky radiative transfer model (HRTM) in the thermal infrared region (700–1300 cm−1, 0.1 cm−1 spectral resolution) is advanced for simulating the upwelling radiance at the top of atmosphere and for retrieving cloud properties. A precomputed transmittance database is generated for simulating the absorption contributed by up to seven major atmospheric absorptive gases (H2O, CO2, O3, O2, CH4, CO, and N2O) by using a rigorous line-by-line radiative transfer model (LBLRTM). Both the line absorption of individual gases and continuum absorption are included in the database. A high-spectral-resolution ice particle bulk scattering properties database is employed to simulate the radiation transfer within a vertically nonisothermal ice cloud layer. Inherent to HRTM are sensor spectral response functions that couple with high-spectral-resolution measurements in the thermal infrared regions from instruments such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer. When compared with the LBLRTM and the discrete ordinates radiative transfer model (DISORT), the root-mean-square error of HRTM-simulated single-layer cloud brightness temperatures in the thermal infrared window region is generally smaller than 0.2 K. An ice cloud optical property retrieval scheme is developed using collocated AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) data. A retrieval method is proposed to take advantage of the high-spectral-resolution instrument. On the basis of the forward model and retrieval method, a case study is presented for the simultaneous retrieval of ice cloud optical thickness τ and effective particle size Deff that includes a cloud-top-altitude self-adjustment approach to improve consistency with simulations.

scholarly journals Hyperspectral Data Simulation (Sentinel-2 to AVIRIS-NG) for Improved Wildfire Fuel Mapping, Boreal Alaska

2021 ◽  
Vol 13 (9) ◽  
pp. 1693
Author(s):  
Anushree Badola ◽  
Santosh K. Panda ◽  
Dar A. Roberts ◽  
Christine F. Waigl ◽  
Uma S. Bhatt ◽  
...  
Keyword(s):  
Land Cover ◽  
Spectral Resolution ◽  
Hyperspectral Image ◽  
Spectral Response ◽  
Spectral Characteristics ◽  
Hyperspectral Data ◽  
Spectral Unmixing ◽  
High Spectral Resolution ◽  
Fuel Mapping ◽  
Sentinel 2

Alaska has witnessed a significant increase in wildfire events in recent decades that have been linked to drier and warmer summers. Forest fuel maps play a vital role in wildfire management and risk assessment. Freely available multispectral datasets are widely used for land use and land cover mapping, but they have limited utility for fuel mapping due to their coarse spectral resolution. Hyperspectral datasets have a high spectral resolution, ideal for detailed fuel mapping, but they are limited and expensive to acquire. This study simulates hyperspectral data from Sentinel-2 multispectral data using the spectral response function of the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor, and normalized ground spectra of gravel, birch, and spruce. We used the Uniform Pattern Decomposition Method (UPDM) for spectral unmixing, which is a sensor-independent method, where each pixel is expressed as the linear sum of standard reference spectra. The simulated hyperspectral data have spectral characteristics of AVIRIS-NG and the reflectance properties of Sentinel-2 data. We validated the simulated spectra by visually and statistically comparing it with real AVIRIS-NG data. We observed a high correlation between the spectra of tree classes collected from AVIRIS-NG and simulated hyperspectral data. Upon performing species level classification, we achieved a classification accuracy of 89% for the simulated hyperspectral data, which is better than the accuracy of Sentinel-2 data (77.8%). We generated a fuel map from the simulated hyperspectral image using the Random Forest classifier. Our study demonstrated that low-cost and high-quality hyperspectral data can be generated from Sentinel-2 data using UPDM for improved land cover and vegetation mapping in the boreal forest.

Dependence of Simulation Biases at AHI Surface-Sensitive Channels on Land Surface Emissivity over China

2018 ◽  
Vol 35 (6) ◽  
pp. 1283-1298 ◽  
Author(s):  
X. Zhuge ◽  
X. Zou ◽  
F. Weng ◽  
M. Sun
Keyword(s):  
Brightness Temperature ◽  
Spectral Resolution ◽  
Land Surface ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Surface Emissivity ◽  
Bare Rock ◽  
Land Surface Emissivity ◽  
M Channels

AbstractThis study compares the simulation biases of Advanced Himawari Imager (AHI) brightness temperature to observations made at night over China through the use of three land surface emissivity (LSE) datasets. The University of Wisconsin–Madison High Spectral Resolution Emissivity dataset, the Combined Advanced Spaceborne Thermal Emission and Reflection Radiometer and Moderate Resolution Imaging Spectroradiometer Emissivity database over Land High Spectral Resolution Emissivity dataset, and the International Geosphere–Biosphere Programme (IGBP) infrared LSE module, as well as land skin temperature observations from the National Basic Meteorological Observing stations in China are used as inputs to the Community Radiative Transfer Model. The results suggest that the standard deviations of AHI observations minus background simulations (OMBs) are largely consistent for the three LSE datasets. Also, negative biases of the OMBs of brightness temperature uniformly occur for each of the three datasets. There are no significant differences in OMB biases estimated with the three LSE datasets over cropland and forest surface types for all five AHI surface-sensitive channels. Over the grassland surface type, significant differences (~0.8 K) are found at the 10.4-, 11.2-, and 12.4-μm channels if using the IGBP dataset. Over nonvegetated surface types (e.g., sandy land, gobi, and bare rock), the lack of a monthly variation in IGBP LSE introduces large negative biases for the 3.9- and 8.6-μm channels, which are greater than those from the two other LSE datasets. Thus, improvements in simulating AHI infrared surface-sensitive channels can be made when using spatially and temporally varying LSE estimates.

A New Highly Stable Multi-Decade Satellite Climate Data Set Derived from Polar Hyperspectral Infrared Sensors

2020 ◽  
Author(s):  
Chris Hepplewhite ◽  
Larrabee Strow ◽  
Howard Motteler ◽  
Sergio de Souza-Machad ◽  
Steven Buczkowski
Keyword(s):  
Spectral Resolution ◽  
Virtual Instrument ◽  
Spectral Response ◽  
Short Wave ◽  
High Spectral Resolution ◽  
Climate Data ◽  
Climate Trends ◽  
Polar Orbit ◽  
Data Set ◽  
Long Wave

<p>NASA's Atmospheric Infrared Sounder (AIRS) started the continuous measurement of the Earth's upwelling infrared radiation at high spectral resolution in Sept. 2002 in a 13:30 polar orbit.  The AIRS record was supplemented by the CrIS sensor flying on the NASA SNPP platform, also in the 13:30 polar orbit, in 2012.  In 2018 a second CrIS sensor on NOAA's JPSS-1 platform (NOAA-20) began operation, also in the 13:30 orbit.  Two more CrIS sensors are presently being procured for the JPSS-2 and 3 satellites, which will extend this record from 2002 through ~2040.  EUMETSAT's METOP-A/B/C provide very similar hyperspectral observations starting with the IASI sensors in the 09:30 orbit, starting in 2007, which will be continued with METOP-SG for years to come.  </p><p>Inter-calibration of all of the operating sensors shows agreement generally to 0.2K or better in brightness temperature.  More importantly, we have shown that the radiometric stability of the AIRS sensors is in the 0.002 K/year range or 0.02K/decade, based on measurements of CO2 and SST trends.   Similar stability is expected for CrIS and IASI.  Community consensus suggests that direct radiance trending, followed by conversion of these trends to geophysical quantities will yield the most accurate climate trends.  </p><p>Here we introduce a new satellite hyperspectral infrared radiance product we call the "Climate Hyperspectral InfraRed Product (CHIRP)" that combines AIRS, CrIS, and IASI into a homogeneous Level 1 radiance product with a common spectral response and channel centers for all three satellites.  This grid is equivalent to an interferometer with optical path differences of 0.8/0.6/0.4 cm for the long-wave/mid-wave/short-wave spectral bands.  This corresponds to a virtual instrument with the same spectral resolution of the JPSS-1 CrIS sensor in the long-wave, with 25/50% degradation in spectral resolution in the mid-wave/short-wave.  This choice allows accurate conversion of the long AIRS record to an equivalent interferometer record.  Conversion of IASI to CHIRP is trivial.  Conversion of all sensors to the CHIRP spectra grid permits simple adjustments of inter-satellite radiometric bias differences since all measurements are first converted to a common spectral grid.  Multiple methods (SNOs, statistical inter-comparisons) indicate these adjustments can be made to the 0.03K level or better.   </p><p>A sample application of CHIRP to climate trending will be given by showing multi-decade anomalies of temperature, humidity, and ozone profiles retrieved from CHIRP radiance anomalies, a retrieval that requires almost no a-priori information.  This data set should yield definitive measurements of water-vapor feedback and heavily contribute to our understanding of both tropospheric and stratospheric temperature trends.   Initial production of CHIRP radiances that combine AIRS and CrIS are expected to begin in late 2020.  </p>

scholarly journals Global monitoring of terrestrial chlorophyll fluorescence from moderate spectral resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2

2013 ◽  
Vol 6 (2) ◽  
pp. 3883-3930 ◽  
Author(s):  
J. Joiner ◽  
L. Guanter ◽  
R. Lindstrot ◽  
M. Voigt ◽  
A. P. Vasilkov ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Spectral Resolution ◽  
Near Infrared ◽  
High Spectral Resolution ◽  
High Signal ◽  
Good Precision ◽  
Atmospheric Absorption ◽  
Red Fluorescence ◽  
Fluorescence Measurements ◽  
Global Mapping

Abstract. Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. In addition, fluorescence can contaminate photon path estimates from the O2 A-band that has become an integral part of missions to accurately measure greenhouse gas concentrations. Global mapping of far-red (~ 755–770 nm) terrestrial vegetation solar-induced fluorescence from space has been accomplished using the high spectral resolution (ν/Δ ν > 35 000) interferometer on the Japanese Greenhouse gases Observing SATellite (GOSAT). These satellite retrievals of fluorescence rely solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data to disentangle the spectral signatures of three basic components in and surrounding the O2 A-band: atmospheric absorption, surface reflectance, and fluorescence radiance. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate spectral resolution measurements with a relatively high signal-to-noise ratio within and outside the O2 A-band can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with GOSAT. GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. It should be noted that both GOME-2 and GOSAT were designed to make atmospheric trace gas measurements and were not optimized for fluorescence measurements. Our approach can be applied to other existing and future space-based instruments that provide moderate spectral resolution observations in the near-infrared region.

scholarly journals IMK/IAA MIPAS temperature retrieval version 8: nominal measurements

2020 ◽  
Author(s):  
Michael Kiefer ◽  
Thomas von Clarmann ◽  
Bernd Funke ◽  
Maya García-Comas ◽  
Norbert Glatthor ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spectral Resolution ◽  
Spectroscopic Data ◽  
A Priori ◽  
Michelson Interferometer ◽  
High Spectral Resolution ◽  
Transfer Model ◽  
Random Component ◽  
Horizontal Structure ◽  
Total Uncertainty

Abstract. A new global set of atmospheric temperature profiles is retrieved from recalibrated radiance spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Changes with respect to previous data versions include a new radiometric calibration considering the time-dependency of the detector non-linearity, and a more robust frequency calibration scheme. Temperature is retrieved using a smoothing constraint, while tangent altitude pointing information is constrained using optimal estimation. ECMWF ERA-Interim is used as temperature a priori below 43 km. Above, a priori data is based on data from the Whole Atmosphere Community Climate Model Version 4 (WACCM4). Bias-corrected fields from specified dynamics runs, sampled at the MIPAS times and locations, are used, blended with ERA-Interim between 43 and 53 km. Horizontal variability of temperature is considered by scaling an a priori 3D temperature field in the orbit plane in a way that the horizontal structure is provided by the a priori while the vertical structure comes from the measurements. Additional microwindows with better sensitivity at higher altitudes are used. The background continuum is jointly fitted with the target parameters up to 58 km altitude. The radiance offset correction is strongly regularized towards an empirically determined vertical offset profile. In order to avoid the propagation of uncertainties of O3 and H2O a priori assumptions, the abundances of these species are retrieved jointly with temperature. The retrieval is based on HITRAN 2016 spectroscopic data, with a few amendments. Temperature-adjusted climatologies of vibrational populations of CO2 states emitting in the 15 micron region are used in the radiative transfer modelling in order to account for non-local thermodynamic equilibrium. Numerical integration in the radiative transfer model is now performed at higher accuracy. The random component of the temperature uncertainty typically varies between 0.4 and 0.8 K, with occasional excursions up to 1.3 K above 60 km altitude. The leading sources of the random component of the temperature error are measurement noise, gain calibration uncertainty, spectral shift, and uncertain CO2 mixing ratios. The systematic error is caused by uncertainties in spectroscopic data and line shape uncertainties. It ranges from 0.2 K at 24 km altitude for northern midlatitude nighttime conditions to 2.3 K at 12 km for tropical nighttime conditions. The estimated total uncertainty amounts to values between 0.5 K at 24 km and northern polar winter conditions to 2.3 K at 12 km and northern midlatitude day conditions. The vertical resolution varies around 3 km for altitudes below 50 km. The long-term drift encountered in the previous temperature product has been largely reduced. The consistency between high spectral resolution results from 2002–2004 and the reduced spectral resolution results from 2005–2012 has been largely improved. As expected, most pronounced temperature differences between version 8 and previous data versions are found in elevated stratopause situations. The fact that the phase of temperature waves seen by MIPAS is not locked to the wave phase found in ECMWF analyses demonstrates that our retrieval provides independent information and does not merely reproduce the prior information.

scholarly journals High-Resolution Fourier Transform Spectroscopy with a VLT

1984 ◽  
Vol 79 ◽  
pp. 497-497
Author(s):  
Donald N.B. Hall
Keyword(s):  
Fourier Transform ◽  
High Resolution ◽  
Spectral Resolution ◽  
Thermal Infrared ◽  
The Other ◽  
High Spectral Resolution ◽  
Resolution Element ◽  
Infrared Wavelengths ◽  
Frequency Calibration ◽  
Absorption Features

The major advantages of the FTS technique are (1) multiplexing, (2) throughput, (3) instrumental profile, (4) stability of frequency calibration, and (5) spectrophotometry accuracy. The multiplex advantage is realized only if one is detector noise limited for the signal within an individual spectral-resolution element. At optical and thermal infrared wavelengths, this is only the case at high spectral resolution (≥ 50000) for modern detectors. By the time the VLT is operating one expects this to also be the case in the 1- to 2.5-micron region. At resolutions ≥ 50000 there are severe problems matching dispersive spectrographs to the VLT aperture, whereas existing FTS instruments already have adequate through-put to match to fields of a few arcsec with a VLT. When the other advantages are considered, the FTS is the instrument of choice for high-resolution (≥ 50000) spectroscopy of absorption features with a VLT. Foreseeable astrophysical applications include observations of interstellar and circumstellar features and of fully resolved profiles of photospheric and planetary lines.

On the surface apparent reflectance exploitation: Entangled Solar Induced Fluorescence emission and aerosol scattering effects at oxygen absorption regions

2020 ◽  
Author(s):  
Neus Sabater ◽  
Pekka Kolmonen ◽  
Luis Alonso ◽  
Jorge Vicent ◽  
José Moreno ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
A Priori ◽  
European Space Agency ◽  
High Spectral Resolution ◽  
Oxygen Absorption ◽  
Aerosol Scattering ◽  
Scattering Effects ◽  
Spectrally Resolved ◽  
Absorption Features ◽  
Aerosol Characterization

<p>Monitoring vegetation photosynthetic activity and its link with the carbon cycle at a global scale is a leading breakthrough that the scientific community has been seeking in recent years. Pursuing this goal, one of the most important advances in the last decade has been the measurement of the Solar Induced Fluorescence (SIF) at a satellite scale. Current satellite-derived SIF estimations provide SIF measured at certain specific wavelengths depending on the retrieval strategy and the instrument capabilities. However, for the time being, no global observations of the total spectrally resolved and integrated SIF signal have been yet achieved. In a near-future context, spectrally resolved SIF estimations will be provided by missions such as the FLuorescence EXplorer (FLEX) from the European Space Agency.</p><p>When disentangling the total SIF contribution, emitted between 650-800 nm, from the acquired satellite signal, molecular and aerosol absorption and scattering effects must be carefully accounted for.  Particularly, within the oxygen absorption features, the characterization of the aerosol scattering effects represents the most critical step prior to the SIF estimation.</p><p>In the context of the FLEX/Sentinel-3 tandem mission concept, this work presents a novel technique that refines any a priori aerosol characterization process through the exploitation of the high spectral resolution surface apparent reflectance signal at the oxygen absorption regions. Within the absorption features, SIF contribution on satellite-derived surface apparent reflectance generates a characteristic peaky spectrum. However, the shape of these peaks can be simultaneously distorted through the atmospheric correction process due to inaccuracies in the aerosol characterization among other secondary sources. Inaccuracies in the estimation of aerosol optical thickness, Angstrom exponent, asymmetry of the scattering or single scattering albedo translate into characteristic distortions in the shape of the peaks in the apparent reflectance. This particular behaviour allows inferring the magnitude of the errors and correcting them. The presented technique improves the accuracy of any a priori aerosol retrieval.</p><p>Authors expect this study to be also of interest to other hyperspectral missions when exploiting, at high spectral resolution, information from oxygen absorption regions.</p>

scholarly journals Community Radiative Transfer Model for Stratospheric Sounding Unit

2011 ◽  
Vol 28 (6) ◽  
pp. 767-778 ◽  
Author(s):  
Yong Chen ◽  
Yong Han ◽  
Quanhua Liu ◽  
Paul Van Delst ◽  
Fuzhong Weng
Keyword(s):  
Radiative Transfer ◽  
Brightness Temperature ◽  
Spectral Resolution ◽  
Model Simulation ◽  
Spectral Response ◽  
Co2 Concentration ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Infrared Observation ◽  
The Impact

Abstract To better use the Stratospheric Sounding Unit (SSU) data for reanalysis and climate studies, issues associated with the fast radiative transfer (RT) model for SSU have recently been revisited and the results have been implemented into the Community Radiative Transfer Model version 2. This study revealed that the spectral resolution for the sensor’s spectral response functions (SRFs) calculations is very important, especially for channel 3. A low spectral resolution SRF results, on average, in 0.6-K brightness temperature (BT) errors for that channel. The variations of the SRFs due to the CO2 cell pressure variations have been taken into account. The atmospheric transmittance coefficients of the fast RT model for the Television and Infrared Observation Satellite (TIROS)-N, NOAA-6, NOAA-7, NOAA-8, NOAA-9, NOAA-11, and NOAA-14 have been generated with CO2 and O3 as variable gases. It is shown that the BT difference between the fast RT model and line-by-line model is less than 0.1 K, but the fast RT model is at least two orders of magnitude faster. The SSU measurements agree well with the simulations that are based on the atmospheric profiles from the Earth Observing System Aura Microwave Limb Sounding product and the Sounding of the Atmosphere using Broadband Emission Radiometry on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. The impact of the CO2 cell pressures shift for SSU has been evaluated by using the Committee on Space Research (COSPAR) International Reference Atmosphere (CIRA) model profiles. It is shown that the impacts can be on an order of 1 K, especially for SSU NOAA-7 channel 2. There are large brightness temperature gaps between observation and model simulation using the available cell pressures for NOAA-7 channel 2 after June 1983. Linear fittings of this channel’s cell pressures based on previous cell leaking behaviors have been studied, and results show that the new cell pressures are reasonable. The improved SSU fast model can be applied for reanalysis of the observations. It can also be used to address two important corrections in deriving trends from SSU measurements: CO2 cell leaking correction and atmospheric CO2 concentration correction.

Sign in / Sign up

Export Citation Format

Share Document