scholarly journals New method to determine the instrument spectral response function, applied to TROPOMI-SWIR

2017 ◽  
Author(s):  
Richard M. van Hees ◽  
Paul J. J. Tol ◽  
Sidney Cadot ◽  
Matthijs Krijger ◽  
Stefan T. Persijn ◽  
...  
Keyword(s):  
Response Function ◽  
Near Infrared ◽  
Spectral Response ◽  
Short Wave ◽  
Trace Gas ◽  
Imaging Spectrometer ◽  
Swir Band ◽  
Novel Method ◽  
Single Instrument

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) is the single instrument on board of the ESA Copernicus Sentinel-5 Precursor satellite. TROPOMI is a nadir-viewing imaging spectrometer with bands in the ultraviolet and visible, the near infrared and the short-wave infrared (SWIR). An accurate instrument spectral response function (ISRF) is required in the SWIR band where absorption lines of CO, methane and water vapor overlap. Therefore a novel method for ISRF determination for an imaging spectrometer was developed and applied to the TROPOMI-SWIR band. The ISRF of all detector pixels of the SWIR spectrometer has been measured during an on-ground calibration campaign. The accuracy of the derived ISRF is well within the requirement for accurate trace-gas retrievals. Long-term in-flight monitoring of the ISRF is guaranteed by the presence of five SWIR diode lasers.

scholarly journals Determination of the TROPOMI-SWIR instrument spectral response function

2018 ◽  
Vol 11 (7) ◽  
pp. 3917-3933 ◽  
Author(s):  
Richard M. van Hees ◽  
Paul J. J. Tol ◽  
Sidney Cadot ◽  
Matthijs Krijger ◽  
Stefan T. Persijn ◽  
...  
Keyword(s):  
Response Function ◽  
Near Infrared ◽  
Spectral Response ◽  
Monochromatic Light ◽  
Imaging Spectrometer ◽  
Swir Band ◽  
Shortwave Infrared ◽  
Single Instrument

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) is the single instrument on board the ESA Copernicus Sentinel-5 Precursor satellite. TROPOMI is a nadir-viewing imaging spectrometer with bands in the ultraviolet and visible, the near infrared and the shortwave infrared (SWIR). An accurate instrument spectral response function (ISRF) is required in the SWIR band where absorption lines of CO, methane and water vapor overlap. In this paper, we report on the determination of the TROPOMI-SWIR ISRF during an extensive on-ground calibration campaign. Measurements are taken with a monochromatic light source scanning the whole detector, using the spectrometer itself to determine the light intensity and wavelength. The accuracy of the resulting ISRF calibration key data is well within the requirement for trace-gas retrievals. Long-term in-flight monitoring of SWIR ISRF is achieved using five on-board diode lasers.

scholarly journals The operational methane retrieval algorithm for TROPOMI

2016 ◽  
Author(s):  
Haili Hu ◽  
Otto Hasekamp ◽  
André Butz ◽  
André Galli ◽  
Jochen Landgraf ◽  
...  
Keyword(s):  
Response Function ◽  
Near Infrared ◽  
Spectral Response ◽  
Short Wave ◽  
Retrieval Algorithm ◽  
Model Errors ◽  
Instrument Calibration ◽  
Atmospheric Scattering ◽  
Accuracy And Precision ◽  
Land Surfaces

Abstract. This work presents the operational methane retrieval algorithm for the Sentinel-5 Precursor (S5-P) satellite and its performance tested on realistic ensembles of simulated measurements. The target product is the column-averaged dry air volume mixing ratio of methane (XCH4), which will be retrieved simultaneously with scattering properties of the atmosphere. The algorithm attempts to fit spectra observed by the shortwave and near-infrared channels of the TROPOMI spectrometer aboard S5-P. The sensitivity of the retrieval performance to atmospheric scattering properties, atmospheric input data and instrument calibration errors is evaluated. Also, we investigate the effect of inhomogeneous slit illumination on the instrument spectral response function. Finally, we discuss the cloud filters to be used operationally and as backup. We show that the required accuracy and precision of < 1 % for the XCH4 product are met for clear sky measurements over land surfaces and after appropriate filtering of difficult scenes. The algorithm is very stable having a convergence rate of 99 %. The forward model error is less than 1 % for about 95 % of the valid retrievals. Model errors in the input profile of water do not influence the retrieval outcome noticeably. The methane product is expected to meet the requirements if errors in input profiles of pressure and temperature remain below 0.3 % and 2 K, respectively. We find further that, of all instrument calibration errors investigated here, our retrievals are the most sensitive to an error in the instrument spectral response function of the short-wave infrared channel.

scholarly journals Applying spectral analysis for identification of alteration zones in north Saveh area, Iran

2020 ◽  
Author(s):  
Kazem Rangzan ◽  
Somayeh Beyranvand ◽  
Hoshang Pourkaseb ◽  
Hojjatollah Ranjbar ◽  
Alireza Zarasvandi
Keyword(s):  
Hydrothermal Alteration ◽  
Near Infrared ◽  
Thermal Emission ◽  
Spectral Response ◽  
Volcanic Rocks ◽  
Short Wave ◽  
Rapid Identification ◽  
Spectral Angle Mapper ◽  
Alteration Zones ◽  
The North

An extensive series of volcanic rocks are exposed in the north of Saveh city, Iran, which consist of phyllic, argillic and propylitic hydrothermal alteration types. For the purpose of the investigation, a FieldSpec3® spectroradiometer was used to measure the spectral response of the mineral content of these rocks. The spectral analyses of reflectance curve by The Spectral Geologist (TSG) software could discriminate kaolinite and montmorillonite (argillic), illite, muscovite, phengite and paragonite (phyllic), hornblende and chlorite, siderite (propylitic), hematite and goethite from the gossans. It also detected gypsum of hydrothermal alteration zones. The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) image, which was used for mapping the hydrothermal alteration minerals, contains the Visible and Near Infrared (VNIR) wavelengths between 0.52 µm and 0.86 µm, Short Wave Infrared (SWIR) wavelengths between 1.6 µm and 2.43 µm and Thermal Infrared (TIR) wavelengths between 8.125 µm and 11.65 µm with 15, 30 and 90 m spatial resolutions, respectively. For calibration of the ASTER images, the extracted spectra of different rocks and minerals were used for atmospheric and radiometric corrections. Mixture tuned matched filtering (MTMF) and Spectral Angle Mapper (SAM) were applied on ASTER data to map the hydrothermal alteration of minerals. The use of the spectroradiometry techniques in conjunction with other data exhibits the ability of these new methods for non-destructive and rapid identification of mineral types for more detailed investigation. The results show that the area has undergone different levels of hydrothermal alteration, so much so that phyllic, argillic and propylitic types of hydrothermal alteration are present in the study area. This may point to high potential and promising zones for the exploration of porphyry mineralisation.

SPECTRAL RESPONSE MEASUREMENTS OF SHORT WAVE INFRARED DETECTORS (SWIR)

2002 ◽  
Vol 12 (02) ◽  
pp. 541-550 ◽  
Author(s):  
TAMER F. REFAAT ◽  
M. NURUL ABEDIN ◽  
UPENDRA N. SINGH
Keyword(s):  
Bias Voltage ◽  
Infrared Detectors ◽  
Near Infrared ◽  
Spectral Response ◽  
Short Wave ◽  
Electrical Signal ◽  
External Bias ◽  
Short Wave Infrared ◽  
Critical Components ◽  
Processing And Storage

Quantum detectors are critical components in infrared lidar receivers. They convert the optical return signal into electrical signal compatible with electronic data processing and storage devices. The detectors used in this study comprise InGaAs PIN diodes and InGaAsSb avalanche photodiodes (APDs) for short wave infrared applications and Si APDs, with different structures, for near-infrared applications. The spectral response of these infrared detectors utilized for lidar receivers was studied with respect to operating temperature and external bias voltage. Variation of these spectral responses as a function of bias voltage and temperature was determined. This variation is employed to estimate errors in the detected lidar return signal. Results of this research finding are reported in this article.

scholarly journals Parameterizing the instrumental spectral response function and its changes by a Super-Gaussian and its derivatives

2016 ◽  
Author(s):  
Steffen Beirle ◽  
Johannes Lampel ◽  
Christophe Lerot ◽  
Holger Sihler ◽  
Thomas Wagner
Keyword(s):  
Response Function ◽  
Cross Sections ◽  
Spectral Response ◽  
Gaussian Function ◽  
Computation Time ◽  
Satellite Orbit ◽  
Spectral Calibration ◽  
Instrumental Resolution ◽  
Derivatives Of

Abstract. The instrumental spectral response function (ISRF) is a key quantity in DOAS analysis, as it is needed for wavelength calibration and for the convolution of trace gas cross-sections to instrumental resolution. While it can generally be measured using monochromatic stimuli, it is often parameterized in order to merge different calibration measurements and to plainly account for its wavelength dependency. For some instruments, the ISRF can be described appropriately by a Gaussian function, while for others, dedicated, complex parameterizations with several parameters have been developed. Here we propose to parameterize the ISRF as a "Super Gaussian", which can reproduce a variety of shapes, from point-hat to boxcar shape, by just adding one parameter to the "classical" Gaussian. The Super Gaussian turned out to describe the ISRF of various DOAS instruments well, including the satellite instruments GOME-2, OMI, and TROPOMI. In addition, the Super Gaussian allows for a straightforward parametrization of the effect of ISRF changes, which can occur on long-term scales as well as e.g.~during one satellite orbit, and impair the spectral analysis if ignored. In order to account for such changes, spectral structures are derived from the derivatives of the Super Gaussian, which are afterwards just scaled during spectral calibration or DOAS analysis. This approach significantly improves the fit quality compared to setups with fixed ISRF, without drawbacks on computation time due to the applied linearization. In addition, the wavelength dependency of the ISRF can be accounted for by accordingly derived spectral structures in an easy, fast, and robust way.

scholarly journals MERIS albedo climatology for FRESCO+ O<sub>2</sub> A-band cloud retrieval

2010 ◽  
Vol 3 (5) ◽  
pp. 4603-4644 ◽  
Author(s):  
C. Popp ◽  
P. Wang ◽  
D. Brunner ◽  
P. Stammes ◽  
Y. Zhou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Trace Gas ◽  
Imaging Spectrometer ◽  
Retrieval Scheme ◽  
Bright Surface ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Scanning Imaging ◽  
Small Cloud

Abstract. A new global albedo climatology for Oxygen A-band cloud retrievals is presented. The climatology is based on MEdium Resolution Imaging Spectrometer (MERIS) Albedomap data and its favourable impact on the derivation of cloud fraction is demonstrated for the FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm. To date, a relatively coarse resolution (1° × 1°) surface reflectance dataset from GOME (Global Ozone Monitoring Experiment) Lambert-equivalent reflectivity (LER) is used in FRESCO+. The GOME LER climatology does not account for the usually higher spatial resolution of UV/VIS instruments designed for trace gas remote sensing which introduces several artefacts, e.g. in regions with sharp spectral contrasts like coastlines or over bright surface targets. Therefore, MERIS black-sky albedo (BSA) data from the period October 2002 to October 2006 were aggregated to a grid of 0.25° × 0.25° for each month of the year and for different spectral channels. In contrary to other available surface reflectivity datasets, MERIS includes channels at 754 nm and 775 nm which are located close to the spectral windows required for O2 A-band cloud retrievals. The MERIS BSA in the near infrared compares well to Moderate Resolution Imaging Spectroradiometer (MODIS) derived BSA with an average difference lower than 1% and a correlation coefficient of 0.98. However, when relating MERIS BSA to GOME LER a distinctly lower correlation (0.80) and enhanced scatter is found. Effective cloud fractions from two exemplary months (January and July 2006) of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) data were subsequently derived with FRESCO+ and compared to those from the Heidelberg Iterative Cloud Retrieval Utilities (HICRU) algorithm. The MERIS climatology generally improves FRESCO+ effective cloud fractions. In particular small cloud fractions are in better agreement with HICRU. This is of importance for atmospheric trace gas retrieval which relies on accurate cloud information at small cloud fractions. In addition, overestimates along coastlines and underestimates in the Intertropical Convergence Zone introduced by the GOME LER were eliminated. While effective cloud fractions over the Saharan desert and the Arabian peninsula are successfully reduced in January, they are still too high in July relative to HICRU due to FRESCO+'s large sensitivity to albedo inaccuracies of highly reflecting targets and inappropriate aerosol information which hampers an accurate albedo retrieval. Apart from FRESCO+, the new MERIS albedo data base is applicable to any cloud retrieval algorithms using the O2 A-band or the O2-O2 absorption band around 477 nm. Moreover, the by-product of BSA at 442 nm can be used in NO2 remote sensing and the BSA at 620 nm, 665 nm, and 681 nm could be integrated in current H2O retrievals.

scholarly journals Radiometric Comparison of 1.6-μm CO2 Absorption Band of Greenhouse Gases Observing Satellite (GOSAT) TANSO-FTS with Suomi-NPP VIIRS SWIR Band

2016 ◽  
Vol 33 (7) ◽  
pp. 1443-1453
Author(s):  
Sirish Uprety ◽  
Changyong Cao
Keyword(s):  
Greenhouse Gases ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Co2 Absorption ◽  
New Methods ◽  
Swir Band ◽  
Long Term Trends ◽  
Global Concern ◽  
Shortwave Infrared

AbstractAn atmospheric CO2 increase has become a progressively important global concern in recent past decades. Since the 1950s, the Keeling curve has documented the atmospheric CO2 increase as well as seasonal variations, which also intrigued scientists to develop new methods for global CO2 measurements from satellites. One of the dedicated satellite missions is the CO2 measurement in the 1.6-μm shortwave infrared spectra by the Greenhouse Gases Observing Satellite (GOSAT) Thermal and Near Infrared Sensor for Carbon Observations–Fourier Transform Spectrometer (TANSO-FTS) instrument. While this spectral region has unique advantages in detecting lower-trophosphere CO2, there are many challenges because it relies on accurate measurements of reflected solar radiance from Earth’s surface. Therefore, the calibration of the TANSO-FTS CO2 has a direct impact on the CO2 retrievals and its long-term trends. Coincidently, the Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) 1.6-μm band spectrally overlaps with the TANSO-FTS CO2 band, and both satellites are in orbit with periodical simultaneous nadir overpass measurements. This study performs an intercomparison of VIIRS and the TANSO-FTS CO2 band in an effort to evaluate and improve the radiometric consistency. Understanding the differences provides feedback on how well the GOSAT TANSO-FTS is performing over time, which is critical to ensure a well-calibrated, stable, and bias-free CO2 product.

scholarly journals Identificación de perturbaciones en el bosque húmedo tropical colombiano usando series temporales de imágenes satelitales Landsat mediante el algoritmo Landtrendr

2019 ◽  
pp. 25
Author(s):  
L. Hurtado ◽  
I. Lizarazo
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Forest Disturbance ◽  
Spectral Response ◽  
Short Wave ◽  
Forest Vegetation ◽  
Landsat Images ◽  
Spectral Bands

<p>Time series analysis of satellite images for detection of deforestation and forest disturbances at specific dates has been a subject of research over the last few years. There are many limitations to identify the exact date of deforestation due mainly to the large volume of data and the criteria required for its correct characterization. A further limitation in the analysis of multispectral time series is the identification of true deforestation considering that forest vegetation may undergo different changes over time. This study analyzes deforestation in a zone within the Colombian Amazon using the Normalized Difference Vegetation Index (NDVI) based on semestral median mosaics generated from Landsat images collected from 2000 to 2017. Several samples representing trends of change over the time series were extracted and classified according to their degree of change and persistence in the series, using four categories: (i) deforestation, (ii) degradation, (iii) forest plantation, and (iv) regeneration. Specific deforestation samples were analyzed in the same way using the soil-adjusted vegetation index (SAVI) to reduce the effect of spectral response variations due to soil reflectance changes. It is concluded that the two indices used, together with the near infrared (NIR) and short-wave infrared (SWIR 1) spectral bands, allow to extract values and intervals where the change produced by deforestation on forest vegetation is identified with acceptable accuracy. The analysis of time series using the Landtrendr algorithm confirmed a reliable change detection in each of the forest disturbance categories.</p>

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