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Improving Atmospheric Correction Across the Indian Subcontinent: Initial Project Results
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ACIX - Atmospheric Correction Inter-comparison eXercise
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Prototyping of LAI and FPAR Retrievals from MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) Data
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Revision of the Atmospheric Delay Correction for ICESat-2 Laser Altimeter Ranges
In 2001 Herring and Quinn proposed the algorithm for correction for atmospheric delay to ICESat-1 GLAS laser altimeter. The purpose of this document is to provide a revision of the algorithm suitable for processing the data from ICESat-2 mission scheduled for launch in 2016. The goal of the revision is to provide a procedure for atmospheric delay correction that would be precise to 1 mm level. The actual accuracy of delay computation will be somewhat less, but it will be limited only by imperfection of the used numerical weather model.
Identification of Terrestrial Reflectance From Remote Sensing
Correcting for atmospheric effects is an essential part of surface-reflectance recovery from radiance measurements. Model-based atmospheric correction techniques enable an accurate identification and classification of terrestrial reflectances from multi-spectral imagery. Successful and efficient removal of atmospheric effects from remote-sensing data is a key factor in the success of Earth observation missions. This report assesses the performance, robustness and sensitivity of two atmospheric-correction and reflectance-recovery techniques as part of an end-to-end simulation of hyper-spectral acquisition, identification and classification.
An expert system shell for inferring vegetation characteristics: Atmospheric techniques (Task G)
The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The VEG Subgoals have been reorganized into categories. A new subgoal category 'Atmospheric Techniques' containing two new subgoals has been implemented. The subgoal Atmospheric Passes allows the scientist to take reflectance data measured at ground level and predict what the reflectance values would be if the data were measured at a different atmospheric height. The subgoal Atmospheric Corrections allows atmospheric corrections to be made to data collected from an aircraft or by a satellite to determine what the equivalent reflectance values would be if the data were measured at ground level. The report describes the implementation and testing of the basic framework and interface for the Atmospheric Techniques Subgoals.
Fire Island Water Resources: Assessing Sediment Dynamics and Turbidity Changes Along Fire Island National Seashore Using Satellite Data
Fire Island National Seashore has experienced damaging effects as a result of coastal erosion. Erosion has become an increasingly damaging problem that has led to the destruction of park and community infrastructure, contributed to rising groundwater tables, and posed a serious threat to a globally rare holly maritime forest. Beach nourishment project efforts have been made to mitigate damage, but dredging is expensive and can be thwarted by high rates of erosion. The NASA DEVELOP team partnered with the National Park Service and Fire Island National Seashore and used imagery from Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), and Sentinel-2 MultiSpectral Instrument (MSI) to analyze turbidity and sediment dynamics through surface reflectance data from 2000-2021. Imagery was atmospherically corrected using Atmospheric Correction for OLI Lite (ACOLITE) and visualized in SeaWiFS Data Analysis Systems (SeaDAS). Additionally, shoreline change was analyzed using high-resolution imagery from WorldView-2 acquired from Maxar for pre-Hurricane Sandy on July 25th, 2010 and post-Hurricane Sandy on December 18th, 2019. The results of this analysis showed that turbidity is highest in the winter seasons. The shoreline analysis estimated total shoreline loss of about 62 acres on the ocean side, and 11 acres on the bay side of the island. These results will be used to better inform future partner-designed shoreline management projects in the face of further erosion and sea level rise.
GEO-LEO Reflective Band Inter-Comparison with BRDF and Atmospheric Scattering Corrections
The inter-comparison of the reflective solar bands (RSB) between the instruments onboard a geostationary orbit satellite and a low Earth orbit satellite is very helpful in assessing their calibration consistency. Himawari-8 was launched 7 October 2014 and GOES-R was launched on 19 November 2016. Unlike previous GOES instruments, the Advanced Himawari Imager (AHI) on Himawari-8 and the Advanced Baseline Imager (ABI) on GOES-R have onboard calibrators for the RSB. Independent assessment of calibration is nonetheless important to enhance their product quality. MODIS (Moderate Resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) can provide good references for sensor calibration. In this work, the inter-comparison between AHI and VIIRS is performed over a pseudo-invariant target. The use of stable and uniform calibration sites provides comparison with accurate adjustment for band spectral difference, reduction of impact from pixel mismatching, and consistency of BRDF (Bidirectional Reflectance Distribution Function) and atmospheric correction. The site used is the Strzelecki Desert in Australia. Due to the difference in solar and view angles, two corrections must be applied in order to compare the measurements. The first is the atmospheric scattering correction applied to the top of atmosphere reflectance measurements. The second correction is applied to correct the BRDF effect. The atmospheric correction is performed using a vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) model and the BRDF correction is performed using a semi-empirical model. Our results show that AHI band 1 (0.47 microns) has a good agreement with VIIRS band M3 within 0.15 percent. AHI band 5 (1.61 microns) shows the largest difference (5.09 percent) with VIIRS band M10, while AHI band 5 shows the least difference (1.87 percent) in comparison with VIIRS band I3. The methods developed in this work can also be directly applied to assess GOES-16/ABI (Geostationary Operational Environment Satellite16 / Advanced Baseline Imager) calibration consistency, a topic we will address in the future.
Atmospheric refractivity corrections in satellite laser ranging
Atmospheric refraction can cause significant errors in satellite laser ranging (SLR) systems. There are two techniques which can be used to correct for these errors. Atmospheric models based upon surface measurements of pressure, temperature, and relative humidity have been shown by ray tracing to be accurate to within a few centimeters at 20 deg elevation angle. The residual errors in the models are thought to be primarily caused by horizontal gradients in the refractivity. Although models have been developed to predict the gradient effects, initial studies show that they can be sensitive to local topographic effects. Atmospheric turbulence can introduce random fluctuations in the refractivity, but only introduces centimeter level errors at elevation angles below 10 deg. Pulsed two-color ranging systems can directly measure the atmospheric delay in satellite ranging. These systems require mode-locked multiple-frequency lasers and streak-camera-based receivers and currently appear capable of measuring the atmospheric delay with an accuracy of 0.5 cm or better.
Task 10: an ERTS Experiment for Mapping Iron Compounds, 1383
The author has identified the following significant results. Preliminary results of a spectral ratioing technique are shown for a region at the southern end of the Wind River Range, Wyoming. Digital ratio graymaps and analog ratio images have been produced for the test site, but ground truth is not yet available for thorough interpretation of these products. ERTS-1 analog ratio images were found generally better than either ERTS-1 single channel images or high altitude aerial photos for the discrimination of vegetation from non-vegetation in the test site region. Some linear geological features smaller than the ERTS-1 spatial resolution are seen as well in ERTS-1 ratio and single channel images as in high altitude aerial photography. Geochemical information appears to be extractable from ERTS-1 data. Good preliminary quantitative agreement between ERTS-1 derived ratios and laboratory derived reflectance ratios of rocks and minerals encourage plans to use lab data as training sets for a simple ratio gating logic approach to automatic recognition maps. Empirical atmospheric corrections indicate that atmospheric corrections are needed to make the ratio method, and possibly other types of data processing, consistent over large geographical and temporal displacements.
The Algorithm Theoretical Basis Document for the Atmospheric Delay Correction to GLAS Laser Altimeter Ranges
NASA s Ice, Cloud, and Land Elevation Satellite (ICESat) mission will be launched late 2001. It s primary instrument is the Geoscience Laser Altimeter System (GLAS) instrument. The main purpose of this instrument is to measure elevation changes of the Greenland and Antarctic icesheets. To accurately measure the ranges it is necessary to correct for the atmospheric delay of the laser pulses. The atmospheric delay depends on the integral of the refractive index along the path that the laser pulse travels through the atmosphere. The refractive index of air at optical wavelengths is a function of density and molecular composition. For ray paths near zenith and closed form equations for the refractivity, the atmospheric delay can be shown to be directly related to surface pressure and total column precipitable water vapor. For ray paths off zenith a mapping function relates the delay to the zenith delay. The closed form equations for refractivity recommended by the International Union of Geodesy and Geophysics (IUGG) are optimized for ground based geodesy techniques and in the next section we will consider whether these equations are suitable for satellite laser altimetry.
PACE Technical Report Series, Volume 7: Ocean Color Instrument (OCI) Concept Design Studies
Extending OCI hyperspectral radiance measurements in the ultraviolet to 320 nm on the blue spectrograph enables quantitation of atmospheric total column ozone (O3) for use in ocean color atmospheric correction algorithms. The strong absorption by atmospheric ozone below 340 nm enables the quantification of total column ozone. Other applications are possible but were not investigated due to their exploratory nature and lower priority.The first step in the atmospheric correction processing, which converts top-of-the-atmosphere radiances to water-leaving radiances, is removal of the absorbance by atmospheric trace gases such as water vapor, oxygen, ozone and nitrogen dioxide. Details of the atmospheric correction process currently used by the Ocean Biology Processing Group (OBPG) and will be employed for PACE with appropriate modifications, are described by Mobley et al. [2016]. Atmospheric ozone absorbs within the visible to near-infrared spectrum between ~450 nm and 800nm and most appreciably between 530 nm and 650 nm, a spectral region critical for maintaining NASA's chlorophyll-a climate data record and for PACE algorithms planned to characterize phytoplankton community composition and other ocean color products.While satellite-based observations will likely be available during PACE's mission lifetime, the difference in acquisition time with PACE, the coarseness in their spatial resolution, and differences in viewing geometries will introduce significant levels of uncertainties in PACE ocean color data products.
FORTRAN program for analyzing ground-based radar data: Usage and derivations, version 6.2
A postflight FORTRAN program called 'radar' reads and analyzes ground-based radar data. The output includes position, velocity, and acceleration parameters. Air data parameters are also provided if atmospheric characteristics are input. This program can read data from any radar in three formats. Geocentric Cartesian position can also be used as input, which may be from an inertial navigation or Global Positioning System. Options include spike removal, data filtering, and atmospheric refraction corrections. Atmospheric refraction can be corrected using the quick White Sands method or the gradient refraction method, which allows accurate analysis of very low elevation angle and long-range data. Refraction properties are extrapolated from surface conditions, or a measured profile may be input. Velocity is determined by differentiating position. Accelerations are determined by differentiating velocity. This paper describes the algorithms used, gives the operational details, and discusses the limitations and errors of the program. Appendices A through E contain the derivations for these algorithms. These derivations include an improvement in speed to the exact solution for geodetic altitude, an improved algorithm over earlier versions for determining scale height, a truncation algorithm for speeding up the gradient refraction method, and a refinement of the coefficients used in the White Sands method for Edwards AFB, California. Appendix G contains the nomenclature.
Comparison of diverse methods for the correction of atmospheric effects on LANDSAT and SKYLAB images
Earth's atmosphere reduces a sensors ability in currently discriminating targets. Using radiometric correction to reduce the atmospheric effects may improve considerably the performance of an automatic image interpreter. Several methods for radiometric correction from the open literature are compared leading to the development of an atmospheric correction system.