Results for “Atmospheric correction” — Page 4

NASA NTRS1992

Overview of atmospheric correction and radiometric calibration efforts during FIFE

The primary responsibility within the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) for understanding the radiometric properties of the remote sensing instrumentation and the atmospheric optical properties affecting measurements with these instruments rested within the atmospheric corrections and radiometric calibration subgroup of FIFE, called the correction/calibration group for short. Specific activities included (1) calibration of remote sensing instrumentation used on aircraft and surface platforms, (2) formulation of recommendations for calibrating data from satellite sensors, (3) measurement and analysis of atmospheric properties, (4) development and evaluation of radiative transfer algorithms which perform the atmospheric correction of remotely sensed data, and (5) derivation and evaluation of surface properties such as reflectances and temperatures. A review of the activities performed by this group and a discussion of the importance of these activities in retrieving surface parameters is presented here.

Halthore, Rangasayi N.↗

NASA NTRS2019

Atmospheric Correction of Satellite Ocean-Color Imagery During the PACE Era

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will carry into space the Ocean Color Instrument (OCI), a spectrometer measuring at 5 nm spectral resolution in the ultraviolet (UV) to near infrared (NIR) with additional spectral bands in the shortwave infrared (SWIR), and two multi-angle polarimeters that will overlap the OCI spectral range and spatial coverage, i. e., the Spectrometer for Planetary Exploration (SPEXone) and the Hyper-Angular Rainbow Polarimeter (HARP2). These instruments, especially when used in synergy, have great potential for improving estimates of water reflectance in the post Earth Observing System (EOS) era. Extending the top-of-atmosphere (TOA) observations to the UV, where aerosol absorption is effective, adding spectral bands in the SWIR, where even the most turbid waters are black and sensitivity to the aerosol coarse mode is higher than at shorter wavelengths, and measuring in the oxygen A-band to estimate aerosol altitude will enable greater accuracy in atmospheric correction for ocean color science. The multi-angular and polarized measurements, sensitive to aerosol properties (e.g., size distribution, index of refraction), can further help to identify or constrain the aerosol model, or to retrieve directly water reflectance. Algorithms that exploit the new capabilities are presented, and their ability to improve accuracy is discussed. They embrace a modern, adapted heritage two-step algorithm and alternative schemes (deterministic, statistical) that aim at inverting the TOA signal in a single step. These schemes, by the nature of their construction, their robustness, their generalization properties, and their ability to associate uncertainties, are expected to become the new standard in the future. A strategy for atmospheric correction is presented that ensures continuity and consistency with past and present ocean-color missions while enabling full exploitation of the new dimensions and possibilities. Despite the major improvements anticipated with the PACE instruments, gaps/issues remain to be filled/tackled. They include dealing properly with whitecaps, taking into account Earth-curvature effects, correcting for adjacency effects, accounting for the coupling between scattering and absorption, modeling accurately water reflectance, and acquiring a sufficiently representative dataset of water reflectance in the UV to SWIR. Dedicated efforts, experimental and theoretical, are in order to gather the necessary information and rectify inadequacies. Ideas and solutions are put forward to address the unresolved issues. Thanks to its design and characteristics, the PACE mission will mark the beginning of a new era of unprecedented accuracy in ocean-color radiometry from space.

ocean color↗

NASA NTRS1983

Atmospheric correction analysis on LANDSAT data over the Amazon region

The Amazon Region natural resources were studied in two ways and compared. A LANDSAT scene and its attributes were selected, and a maximum likelihood classification was made. The scene was atmospherically corrected, taking into account Amazonic peculiarities revealed by (ground truth) of the same area, and the subsequent classification. Comparison shows that the classification improves with the atmospherically corrected images.

Parada, N. D. J.↗

NASA NTRS1997

Atmospheric Correction of Satellite Imagery Using Modtran 3.5 Code

When performing satellite remote sensing of the earth in the solar spectrum, atmospheric scattering and absorption effects provide the sensors corrupted information about the target's radiance characteristics. We are faced with the problem of reconstructing the signal that was reflected from the target, from the data sensed by the remote sensing instrument. This article presents a method for simulating radiance characteristic curves of satellite images using a MODTRAN 3.5 band model (BM) code to solve the radiative transfer equation (RTE), and proposes a method for the implementation of an adaptive system for automated atmospheric corrections. The simulation procedure is carried out as follows: (1) for each satellite digital image a radiance characteristic curve is obtained by performing a digital number (DN) to radiance conversion, (2) using MODTRAN 3.5 a simulation of the images characteristic curves is generated, (3) the output of the code is processed to generate radiance characteristic curves for the simulated cases. The simulation algorithm was used to simulate Landsat Thematic Mapper (TM) images for two types of locations: the ocean surface, and a forest surface. The simulation procedure was validated by computing the error between the empirical and simulated radiance curves. While results in the visible region of the spectrum where not very accurate, those for the infrared region of the spectrum were encouraging. This information can be used for correction of the atmospheric effects. For the simulation over ocean, the lowest error produced in this region was of the order of 105 and up to 14 times smaller than errors in the visible region. For the same spectral region on the forest case, the lowest error produced was of the order of 10-4, and up to 41 times smaller than errors in the visible region,

Gonzales, Fabian O.↗

NASA NTRS1992

Atmospheric corrections for TIMS estimated emittance

The estimated temperature of the average of 500 lines of Thermal Infrared Multispectral Scanner (TIMS) data of the Pacific Ocean, from flight line 94, collected on 30 Sep. 1988, at 1931 GMT is shown. With no atmospheric corrections, estimated temperature decreases away from nadir (the center of the scan line). A LOWTRAN modeled correction, using local radiosonde data and instrument scan angle information, results in reversed limb darkening effects for most bands, and does not adequately correct all bands to the same temperature. The atmosphere tends to re-radiate energy at the wavelengths at which it most absorbs, and thus the overall difference between corrected and uncorrected temperatures is approximately 40 C, despite the average LOWTRAN calculated transmittance of only 60 percent between 8.1 and 11.6 microns. An alternative approach to atmospheric correction is a black body normalization. This is done by calculating a normalization factor for each pixel position and wavelength, which when applied results in a single calculated temperature, as would be expected for a gray body with near uniform emittance. The black body adjustment is based on the atmospheric conditions over the sea. The ground elevation profile along the remaining 3520 scan lines (approximately 10 km) of flight line 94, up the slopes of Kilauea, determined from aircraft pressure and laser altimeter data is shown. This flight line includes a large amount of vegetation that is clearly discernible on the radiance image, being much cooler than the surrounding rocks. For each of the 3520 scan lines, pixels were classified as vegetation or 'other'. A moving average of 51 lines was applied to the composite vegetation emittance for each scan line, to reduce noise. Assuming vegetation to be like water, and to act as gray body with an emittance of 0.986 across the spectrum, it is shown that that the LOWTRAN induced artifacts are severe, and other than for the 0.9.9 micron channel, not significantly different from applying no corrections at all. As expected, with increasing elevation atmospheric effects are slightly reduced, because moisture tends to be concentrated in the lowermost part of the atmosphere. The black body adjustment is highly robust, and even at elevations nearly 600 meters above the sea, remains an alternative procedure for use in calculating emittance.

Warner, T. A.↗

NASA NTRS2011

Current Status of Multi-Angle Implementation of Atmospheric Correction (MAIAC) Algorithm

A new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has been developed for MODIS. MAIAC uses a time series and an image based rather than pixel-based processing to perform simultaneous retrievals of aerosol properties and surface bidirectional reflectance. It is a generic algorithm which works over all land surface types with the exception of snow. MAIAC has an internal Cloud Mask, a dynamic land-water-snow classification and a surface change mask which allows it to flexibly choose processing path over different surfaces. A distinct feature of MAIAC is a high 1 km resolution of aerosol retrievals including optical thickness and fine mode fraction, which is required in different applications including the air quality analysis. An overview of the algorithm, results of AERONET validation, and examples of comparison with MODIS Collection 5 aerosol product, including Deep Blue algorithm, will be presented for different parts of the world including continental USA, Persian Gulf region and India.

Lyapustin, A.↗

NASA NTRS1992

Radiometric calibration and atmospheric correction of satellite and aircraft data for FIFE

The satellite and aircraft radiometric calibration and atmospheric correction work carried out as part of the first International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) are summarized. A large volume (120 Gbytes) of radiometric data were acquired and derived from a number of different instruments on a variety of platforms. The same basic procedure was applied to each instrument: derive the most recent calibration coefficients for converting sensor counts to reflective spectral radiances; correct the radiances for earth-sun distance variations and incident solar spectral irradiance within the bandpass of each respective instrument channel at the top of the atmosphere; characterize the atmosphere for aerosols and absorbing gases; and derive apparent surface reflectance by correcting the exoatmospheric values for atmospheric attenuation. The same basic approach was used for surface temperature derivation. The results of this processing were verified by surface measurements, and corroborated by sensor intercomparisons.

Goetz, Scott J.↗

NASA NTRS1994

Atmospheric correction of LANDSAT TM thermal band using surface energy balance

Thermal infrared data of LANDSAT Thematic Mapper (TM) are hardly used, probably due to the difficulties met when trying to correct them for atmospheric effects. A method for correcting these data was designed, based on surface energy balance estimation of known wet and dry targets included in the TM image to be corrected. This method, only using the image itself and local meteorological data was tested and validated on various surfaces: agricultural, forest and rangeland. The root mean square error on corrected temperatures is on the order of 1C.

Vidal, Alain↗

NASA NTRS1973

Enhancement of Earth Resources Technology Satellite /ERTS/ and aircraft imagery using atmospheric corrections.

The studies considered are concerned with the magnitude of the atmospheric effects in multispectral earth resources data taken by satellites and aircraft. The atmospheric effects are present in all space oriented and aerial data even in the so-called atmospheric 'windows' through which all sensors observe the ground. Atmospheric effects are quite varied and depend on several parameters. An atmospheric model developed by Turner et al. (1971) is discussed. The model is applied to the test site, which is located in North Dakota. The results are used to obtain atmospheric correction data for ERTS-1 scanner data.

Sharma, R. D.↗

NASA NTRS2019

Atmospheric Correction of Satellite Ocean-Color Imagery During the PACE Era

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will carry into space the Ocean Color Instrument (OCI), a spectrometer measuring at 5 nm spectral resolution in the ultraviolet (UV) to near infrared (NIR) with additional spectral bands in the shortwave infrared (SWIR), and two multi-angle polarimeters that will overlap the OCI spectral range and spatial coverage, i. e., the Spectrometer for Planetary Exploration (SPEXone) and the Hyper-Angular Rainbow Polarimeter (HARP2). These instruments, especially when used in synergy, have great potential for improving estimates of water reflectance in the post Earth Observing System (EOS) era. Extending the top-of-atmosphere (TOA) observations to the UV, where aerosol absorption is effective, adding spectral bands in the SWIR, where even the most turbid waters are black and sensitivity to the aerosol coarse mode is higher than at shorter wavelengths, and measuring in the oxygen A-band to estimate aerosol altitude will enable greater accuracy in atmospheric correction for ocean color science. The multi-angular and polarized measurements, sensitive to aerosol properties (e.g., size distribution, index of refraction), can further help to identify or constrain the aerosol model, or to retrieve directly water reflectance. Algorithms that exploit the new capabilities are presented, and their ability to improve accuracy is discussed. They embrace a modern, adapted heritage two-step algorithm and alternative schemes (deterministic, statistical) that aim at inverting the TOA signal in a single step. These schemes, by the nature of their construction, their robustness, their generalization properties, and their ability to associate uncertainties, are expected to become the new standard in the future. A strategy for atmospheric correction is presented that ensures continuity and consistency with past and present ocean-color missions while enabling full exploitation of the new dimensions and possibilities. Despite the major improvements anticipated with the PACE instruments, gaps/issues remain to be filled/tackled. They include dealing properly with whitecaps, taking into account Earth-curvature effects, correcting for adjacency effects, accounting for the coupling between scattering and absorption, modeling accurately water reflectance, and acquiring a sufficiently representative dataset of water reflectance in the UV to SWIR. Dedicated efforts, experimental and theoretical, are in order to gather the necessary information and rectify inadequacies. Ideas and solutions are put forward to address the unresolved issues. Thanks to its design and characteristics, the PACE mission will mark the beginning of a new era of unprecedented accuracy in ocean-color radiometry from space.

Robert J Frouin↗

NASA NTRS2017

Revisiting Short-Wave-Infrared (SWIR) Bands for Atmospheric Correction in Coastal Waters

The shortwave infrared (SWIR) bands on the existing Earth Observing missions like MODIS have been designed to meet land and atmospheric science requirements. The future geostationary and polar-orbiting ocean color missions, however, require highly sensitive SWIR bands (greater than 1550nm) to allow for a precise removal of aerosol contributions. This will allow for reasonable retrievals of the remote sensing reflectance (R(sub rs)) using standard NASA atmospheric corrections over turbid coastal waters. Design, fabrication, and maintaining high-performance SWIR bands at very low signal levels bear significant costs on dedicated ocean color missions. This study aims at providing a full analysis of the utility of alternative SWIR bands within the 1600nm atmospheric window if the bands within the 2200nm window were to be excluded due to engineering/cost constraints. Following a series of sensitivity analyses for various spectral band configurations as a function of water vapor amount, we chose spectral bands centered at 1565 and 1675nm as suitable alternative bands within the 1600nm window for a future geostationary imager. The sensitivity of this band combination to different aerosol conditions, calibration uncertainties, and extreme water turbidity were studied and compared with that of all band combinations available on existing polar-orbiting missions. The combination of the alternative channels was shown to be as sensitive to test aerosol models as existing near-infrared (NIR) band combinations (e.g., 748 and 869nm) over clear open ocean waters. It was further demonstrated that while in extremely turbid waters the 1565/1675 band pair yields R(sub rs) retrievals as good as those derived from all other existing SWIR band pairs (greater than 1550nm), their total calibration uncertainties must be less than 1% to meet current science requirements for ocean color retrievals (i.e., delta R(sub rs) (443) less than 5%). We further show that the aerosol removal using the NIR and SWIR bands (available on the existing polar-orbiting missions) can be very sensitive to calibration uncertainties. This requires the need for monitoring the calibration of these bands to ensure consistent multi-mission ocean color products in coastal/inland waters.

atmospheric correction↗

NASA NTRS1988

Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery

An algorithm for automatic atmospheric correction of satellite imagery of the earth's surface is proposed which is applicable to low-resolution and high-resolution imagery of land areas. The algorithm is based on the satellite image being corrected and on the climatology of the area, and it requires that some pixels in the image correspond to dense dark vegetation as the surface cover. The algorithm is sensitive to the assumed reflectance of the dense dark vegetation, and the accuracy of the corrected surface reflectance is expected to be + or - 0.01. Using the method, aerosol optical thicknesses were derived from clear and hazy Landsat MSS images in the Washington, D.C. and Chesapeake Bay region, and the results are found to agree well with simultaneous sunphotometer ground measurements.

Kaufman, Yoram J.↗

NASA NTRS1988

Application of 3-D radiative transfer theory to atmospheric correction of land surface images

Three dimensional radiative transfer theory was applied to computation of atmospheric effects on remotely sensed imagery. The atmospheric correction algorithm derived is used to estimate aerosol opacity.

Diner, D. J.↗

NASA NTRS1973

A radiation model for calculating atmospheric corrections to remotely sensed infrared measurements, version 2

A numerical model is developed which calculates the atmospheric corrections to infrared radiometric measurements due to absorption and emission by water vapor, carbon dioxide, and ozone. The corrections due to aerosols are not accounted for. The transmissions functions for water vapor, carbon dioxide, and water are given. The model requires as input the vertical distribution of temperature and water vapor as determined by a standard radiosonde. The vertical distribution of carbon dioxide is assumed to be constant. The vertical distribution of ozone is an average of observed values. The model also requires as input the spectral response function of the radiometer and the nadir angle at which the measurements were made. A listing of the FORTRAN program is given with details for its use and examples of input and output listings. Calculations for four model atmospheres are presented.

Boudreau, R. D.↗

NASA NTRS1989

Evaluating atmospheric correction models for retrieving surface temperatures from the AVHRR over a tallgrass prairie

The effects of atmospheric attenuation on surface radiative temperatures obtained by the AVHRR over a tallgrass prairie area in the Flint Hills of Kansas are examined. Six atmospheric correction models developed primarily for sea-surface temperature studies are used to test their utility for retrieval of radiative temperatures over the land surface. An uncertainty of + or - 3.0 C was found for the AVHRR data, and used to evaluate the performance of a given model. When the difference between in situ and AVHRR surface temperatures was smaller than the uncertainty, the model was judged to be adequate. Among the six models evaluated, only the NOAA split-window model consistently adjusted the AVHRR surface temperatures within + or - 3.0 C of the in situ measurements.

Cooper, D. I.↗

NASA NTRS2021

The AOD Sensitivity Comparison between MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) and Standard MODIS Surface Reflectance

This study compares the Multi-Angle Implementation of Atmospheric Correction (MAIAC) and standard MODIS surface reflectance (SR) products (MOD09)for various aerosol optical depth (AOD) levels. Data from one MODIS tile in northern China for the whole year 2018 is compared. The results reveal that MAIAC SR has good stability for the full range of AOD for which SR is reported, whereas MOD09 SR shows increasing high bias with AOD increases. The cross-comparison of spectral characteristics between MAIAC SR and MOD09 SR shows a systematic MAIAC-MOD09 difference increasing from NIR to Blue. This pattern is consistent with the bias caused by Lambertian assumption used in MOD09 SR algorithm.

MAIAC↗

NASA NTRS1993

Validation of Atmospheric Correction of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Radiance Data Based on Radiative Transfer Modeling

An evaluation of atmospheric correction of AVIRIS data using radiative transfer codes LOWTRAN7 and MODTRAN is presented. The algorithm employed is based on a simple model of radiance L at each wavelength at the sensor that can be written approximately LAV=Lp+Tp, where subscript AV referes to AVIRIS, Lp is the path radiance and Tp is the diffuse + direct transmitted radiance of the atmosphere at AVIRIS.

Infrared Mapping↗

NASA NTRS1992

Atmospheric correction algorithm for NOAA-AVHRR products - Theory and application

The present evaluation of the effects of atmospheric constituents on NOAA AVHRR visible and near-IR data first gives attention to the general remote sensing equation and then addresses the magnitude of the atmospheric effects for AVHRR solar bands with respect to their impact on the normalized difference vegetation index (NDVI) and the surface bidirectional reflectance. Possible approaches to the acquisition of atmospheric data are then considered, and examples of atmospheric correction of surface reflectance and NDVI are discussed. The correction of the aerosol effect is essential in the case of NDVI study of densely vegetated areas.

Tanre, Didier↗