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At least 127 records · Page 7

Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPAR(sub chl)) and Leaf Water Content (LWC)

This study presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetic active radiation (PAR) absorbed by chlorophyll of a canopy (fAPAR(sub chl)) and leaf water content (LWC), for future HyspIRI implementation at 60 m spatial resolution. For this, we used existing 30 m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRI-like images were atmospherically corrected to obtain surface reflectance, and spectrally resampled to produce 60 m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest[1]. With this study, we provide additional evidence that the fAPARchl product is more realistic for describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPAR(sub canopy)), and thus should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle studies and ecosystem studies.

Zhang, Qingyuan↗

Support Routines for In Situ Image Processing

This software consists of a set of application programs that support ground-based image processing for in situ missions. These programs represent a collection of utility routines that perform miscellaneous functions in the context of the ground data system. Each one fulfills some specific need as determined via operational experience. The most unique aspect to these programs is that they are integrated into the large, in situ image processing system via the PIG (Planetary Image Geometry) library. They work directly with space in situ data, understanding the appropriate image meta-data fields and updating them properly. The programs themselves are completely multimission; all mission dependencies are handled by PIG. This suite of programs consists of: (1)marscahv: Generates a linearized, epi-polar aligned image given a stereo pair of images. These images are optimized for 1-D stereo correlations, (2) marscheckcm: Compares the camera model in an image label with one derived via kinematics modeling on the ground, (3) marschkovl: Checks the overlaps between a list of images in order to determine which might be stereo pairs. This is useful for non-traditional stereo images like long-baseline or those from an articulating arm camera, (4) marscoordtrans: Translates mosaic coordinates from one form into another, (5) marsdispcompare: Checks a Left Right stereo disparity image against a Right Left disparity image to ensure they are consistent with each other, (6) marsdispwarp: Takes one image of a stereo pair and warps it through a disparity map to create a synthetic opposite- eye image. For example, a right eye image could be transformed to look like it was taken from the left eye via this program, (7) marsfidfinder: Finds fiducial markers in an image by projecting their approximate location and then using correlation to locate the markers to subpixel accuracy. These fiducial markets are small targets attached to the spacecraft surface. This helps verify, or improve, the pointing of in situ cameras, (8) marsinvrange: Inverse of marsrange . given a range file, re-computes an XYZ file that closely matches the original. . marsproj: Projects an XYZ coordinate through the camera model, and reports the line/sample coordinates of the point in the image, (9) marsprojfid: Given the output of marsfidfinder, projects the XYZ locations and compares them to the found locations, creating a report showing the fiducial errors in each image. marsrad: Radiometrically corrects an image, (10) marsrelabel: Updates coordinate system or camera model labels in an image, (11) marstiexyz: Given a stereo pair, allows the user to interactively pick a point in each image and reports the XYZ value corresponding to that pair of locations. marsunmosaic: Extracts a single frame from a mosaic, which will be created such that it could have been an input to the original mosaic. Useful for creating simulated input frames using different camera models than the original mosaic used, and (12) merinverter: Uses an inverse lookup table to convert 8-bit telemetered data to its 12-bit original form. Can be used in other missions despite the name.

Deen, Robert G.↗

Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPAR(sub chl)) and Leaf Water Content(LWC)

This paper presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetically active radiation (PAR) absorbed by chlorophyll of a canopy (fAPARchl) and leaf water content (LWC), for future HyspIRI implementation at 60-m spatial resolution. For this, we used existing 30-m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRIlike images were atmospherically corrected to obtain surface reflectance and spectrally resampled to produce 60-m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest. With this paper, we provide additional evidence that the fAPARchl product is more realistic in describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPARcanopy), and thus, it should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle and ecosystem studies.

Earth Observing One↗

An Analysis of the Side Slither On-Orbit Calibration Technique Using the DIRSIG Model

Pushbroom-style imaging systems exhibit several advantages over line scanners when used on space-borne platforms as they typically achieve higher signal-to-noise and reduce the need for moving parts. Pushbroom sensors contain thousands of detectors, each having a unique radiometric response, which will inevitably lead to streaking and banding in the raw data. To take full advantage of the potential exhibited by push broom sensors, a relative radiometric correction must be performed to eliminate pixel-to-pixel non-uniformities in the raw data. Side slither is an on-orbit calibration technique where a 90-degree yaw maneuver is performed over an invariant site to flatten the data. While this technique has been utilized with moderate success for the QuickBird satellite and the RapidEye constellation, further analysis is required to enable its implementation for the Landsat 8 sensors, which have a 15-degree field-of-view and a 0.5% pixel-to-pixel uniformity requirement. This work uses the DIRSIG model to analyze the side slither maneuver as applicable to the Landsat sensor. A description of favorable sites, how to adjust the maneuver to compensate for the curvature of "linear" arrays, how to efficiently process the data, and an analysis to assess the quality of the side slither data, are presented.

Side slither↗

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring (Invited)

Many land applications require more frequent observations than can be obtained from a single 'Landsat class' sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a '30-meter MODIS' global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for approximately 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site (https://hls.gsfc.nasa.gov). A wall-to-wall North America data set is being prepared for 2018. This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

Reflectance↗

Digital correction of geometric and radiometric errors in ERTS data.

The sensor systems of the ERTS-A satellite are discussed and sources of geometric and radiometric errors in the received images are identified. Digital algorithms are presented for detection of reseau and ground control points, for rapid implementation of geometric corrections, and for radiometric correction of errors caused by shading, image motion, modulation transfer function, and quantum and systematic noise.

Bakis, R.↗

Atmospheric corrections to satellite radiometric data over rugged terrain

Radiometric measurements from satellites in the solar portion of the electromagnetic spectrum can be converted to measurements of surface exitance. Over rugged terrain, the satellite image must be precisely registered to a terrain data set. For small areas a first-order polynomial interpolation scheme is generally satisfactory for the geometric rectification. If there are saturated pixels, a nearest-neighbor procedure is used for the interpolated satellite radiance numbers; otherwise a cubic-convolution algorithm is used. Path radiance and path transmittance are calculated with a simple spectral model, which requires an estimate of the water vapor and aerosol content of the atmosphere.

Dozier, J.↗

LANDSAT-4 Radiometric and Geometric Correction and Image Enhancement Results

Techniques were developed or improved to calibrate, enhance, and geometrically correct LANDSAT-4 satellite data. Statistical techniques to correct data radiometry were evaluated and were found to minimize striping and banding. Conventional techniques cause striping even with perfect calibration parameters. Intensity enhancement techniques were improved to display image data with large variation in intensity or brightness. Data were geometrically corrected to conform to a 1:100,000 map reference and image products produced with the map overlay. It is shown that these products can serve as accurate map products. A personal computer was experimentally used for digital image processing.

Bernstein, R.↗

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.↗

Radiometric calibration requirements and atmospheric correction

The need for independent, radundant, absolute radiometric calibration methods is discussed with reference to the Thematic Mapper. Uncertainty requirements for absolute calibration of between 0.5 percent and 4 percent are defined based on the accuracy of reflectance retrievals at an agricultural site. It is shown that even very approximate atmospheric corrections can reduce the error in reflectance retrieval to 0.02 over the reflectance range 0 to 0.4.

Slater, Philip N.↗

Production and analysis of output data products for Landsat-4 in the engineering check-out phase

The Landsat-D (now Landsat-4) program was initiated by NASA in the mid-1970's. The spacecraft was launched on July 16, 1982. Instruments on the satellite include the fourth Multispectral Scanner (MSS) and the new higher-resolution Thematic Mapper (TM). In order to achieve the planned engineering and scientific objectives, attention has to be given to the validation of spacecraft and instrument performance, the adjustment of ground processing procedures, and the definition of the measures of the TU utility. To satisfy these requirements, a Landsat Assessment System (LAS) was conceived, and the Applications Developmental Data System (ADDS) was instituted. The set of component systems collectively became known as the 'Scrounge' system. The present investigation is concerned with the Scrounge system and the results of radiometric and geometric data evaluations. Attention is given to the TM geometric correction, TM data resampling, a radiometric correction functional description, and the results of the TM geometric and radiometric correction.

Lyon, J. C.↗

Evaluation of the radiometric quality of the TM data using clustering and multispectral distance measures

Radiometrically and geometrically corrected TM data from three different geographic locations were examined. Histograms were inspected for each band to determine the dynamic range of the data, the shape of the distributions, and to verify whether empty bins were introduced by the radiometric correction process. The effect of geometric correction on the radiometry of the resampled pixels was determined. The information content between TM and MSS data sets were compared and the TM data were used to map the thermal effluent discharge into a river ecosystem from a nuclear thermal power plant, and application only possible previously only possible through the acquisition of thermal infrared scanner data from aircraft altitudes.

Bartolucci, L. A.↗

Radiometric and spectral stray light correction for the Portable Remote Imaging Spectrometer (PRISM) coastal ocean sensor

The airborne Portable Remote Imaging Spectrometer (PRISM) instrument is based on a fast (F/1.8) Dyson spectrometer operating at 350-1050 nm and a two-mirror telescope combined with a Teledyne HyViSI 6604A detector array. Raw PRISM data contain electronic and optical artifacts that must be removed prior to radiometric calibration. We provide an overview of the process transforming raw digital numbers to calibrated radiance values. Electronic panel artifacts are first corrected using empirical relationships developed from laboratory data. The instrument spectral response functions (SRF) are reconstructed using a measurement-based optimization technique. Removal of SRF effects from the data improves retrieval of true spectra, particularly in the typically low-signal near-ultraviolet and near-infrared regions. As a final step, radiometric calibration is performed using corrected measurements of an object of known radiance. Implementation of the complete calibration procedure maximizes data quality in preparation for subsequent processing steps, such as atmospheric removal and spectral signature classification.

Thompson, David R.↗

Advanced Land Imager Assessment System

The Advanced Land Imager Assessment System (ALIAS) supports radiometric and geometric image processing for the Advanced Land Imager (ALI) instrument onboard NASA s Earth Observing-1 (EO-1) satellite. ALIAS consists of two processing subsystems for radiometric and geometric processing of the ALI s multispectral imagery. The radiometric processing subsystem characterizes and corrects, where possible, radiometric qualities including: coherent, impulse; and random noise; signal-to-noise ratios (SNRs); detector operability; gain; bias; saturation levels; striping and banding; and the stability of detector performance. The geometric processing subsystem and analysis capabilities support sensor alignment calibrations, sensor chip assembly (SCA)-to-SCA alignments and band-to-band alignment; and perform geodetic accuracy assessments, modulation transfer function (MTF) characterizations, and image-to-image characterizations. ALIAS also characterizes and corrects band-toband registration, and performs systematic precision and terrain correction of ALI images. This system can geometrically correct, and automatically mosaic, the SCA image strips into a seamless, map-projected image. This system provides a large database, which enables bulk trending for all ALI image data and significant instrument telemetry. Bulk trending consists of two functions: Housekeeping Processing and Bulk Radiometric Processing. The Housekeeping function pulls telemetry and temperature information from the instrument housekeeping files and writes this information to a database for trending. The Bulk Radiometric Processing function writes statistical information from the dark data acquired before and after the Earth imagery and the lamp data to the database for trending. This allows for multi-scene statistical analyses.

Chander, Gyanesh↗

Earth Observing-1 Advanced Land Imager Flight Performance Assessment: Absolute Radiometry and Stability During the First Year

The absolute radiometry of the Advanced Land Imager during the first year on orbit (November 21,2000 - November 21, 2001) is presented. Results derived from solar, lunar, ground truth, and internal reference lamp measurements are presented. An 18% drop in the radiometric response of the Band 1p data since preflight calibration at Lincoln Laboratory is observed using all techniques. This decrease cannot be accounted for by preflight calibration errors, stray light, or contamination of the focal plane. A slight drooping of the VNIR response toward the blue and a 5-12% increase in the Band 5 response is also apparent in all the data. Radiometric response correction factors have been calculated and preflight calibration coefficients have been updated in order to provide +/- 5% agreement between the measured solar, lunar, and ground truth data and the expected values. The radiometric stability of the ALI during the first year of operation is also presented for each spectral band. Internal reference lamp data indicate the focal plane has been stable to within 1% for bands 1p, 1, 2, 5p, 5, 7, pan and 3% for Bands 3,4, 4p since launch. Solar, lunar, and ground truth measurements indicate the optical train and solar diffuser of the instrument has been stable to within 1% since initial measurements on orbit in late December 2000.

Mendenhall, J. A.↗

Processing TES Level-1B Data

TES L1B Subsystem is a computer program that performs several functions for the Tropospheric Emission Spectrometer (TES). The term "L1B" (an abbreviation of "level 1B"), refers to data, specific to the TES, on radiometric calibrated spectral radiances and their corresponding noise equivalent spectral radiances (NESRs), plus ancillary geolocation, quality, and engineering data. The functions performed by TES L1B Subsystem include shear analysis, monitoring of signal levels, detection of ice build-up, and phase correction and radiometric and spectral calibration of TES target data. Also, the program computes NESRs for target spectra, writes scientific TES level-1B data to hierarchical- data-format (HDF) files for public distribution, computes brightness temperatures, and quantifies interpixel signal variability for the purpose of first-order cloud and heterogeneous land screening by the level-2 software summarized in the immediately following article. This program uses an in-house-developed algorithm, called "NUSRT," to correct instrument line-shape factors.

DeBaca, Richard C.↗

Evaluation of Atmospheric Loading and Improved Troposphere Modelling

Forward modeling of non-tidal atmospheric loading displacements at geodetic tracking stations have not routinely been included in Doppler Orbitography and Radiopositionning Integrated by Satellite (DORIS) or Satellite Laser Ranging (SLR) station analyses for either POD applications or reference frame determination. The displacements which are computed from 6-hourly models such as the ECMWF and can amount to 3-10 mm in the east, north and up components depending on the tracking station locations. We evaluate the application of atmospheric loading in a number ways using the NASA GSFC GEODYN software: First we assess the impact on SLR & DORIS-determined orbits such as Jason-2, where we evaluate the impact on the tracking data RMS of fit and how the total orbits are changed with the application of this correction. Preliminary results show an RMS radial change of 0.5 mm for Jason-2 over 54 cycles and a total change in the Z-centering of the orbit of 3 mm peak-to-peak over one year. We also evaluate the effects on other DORIS-satellites such as Cryosat-2, Envisat and the SPOT satellites. In the second step, we produce two SINEX time series based on data from available DORIS satellites and assess the differences in WRMS, scale and Helmert translation parameters. Troposphere refraction is obviously an important correction for radiometric data types such as DORIS. We evaluate recent improvements in DORIS processing at GSFC including the application of the Vienna Mapping Function (VMF1) grids with a-priori hydrostatic (VZHDs) and wet (VZWDs) zenith delays. We reduce the gridded VZHD at the stations height using pressure and temperature derived from GPT (strategy 1) and Saastamoinen. We discuss the validation of the VMF1 implementation and its application to the Jason-2 POD processing, compared to corrections using the Niell mapping function and the GMF. Using one year of data, we also assess the impact of the new troposphere corrections on the DORIS-only solutions, most importantly on the scale of the weekly solutions.

Zelensky, Nikita P.↗

High-Resolution Image Products Acquired from Mid-Sized Uncrewed Aerial Systems for Land–Atmosphere Studies

We assess the viability of deploying commercially available multispectral and thermal imagers designed for integration on small uncrewed aerial systems (sUASs, <25 kg) on a mid-size Group-3-classification UAS (weight: 25–600 kg, maximum altitude: 5486 m MSL, maximum speed: 128 m/s) for the purpose of collecting a higher spatial resolution dataset that can be used for evaluating the surface energy budget and effects of surface heterogeneity on atmospheric processes than those datasets traditionally collected by instrumentation deployed on satellites and eddy covariance towers. A MicaSense Altum multispectral imager was deployed on two very similar mid-sized UASs operated by the Atmospheric Radiation Measurement (ARM) Aviation Facility. This paper evaluates the effects of flight on imaging systems mounted on UASs flying at higher altitudes and faster speeds for extended durations. We assess optimal calibration methods, acquisition rates, and flight plans for maximizing land surface area measurements. We developed, in-house, an automated workflow to correct the raw image frames and produce final data products, which we assess against known spectral ground targets and independent sources. We intend this manuscript to be used as a reference for collecting similar datasets in the future and for the datasets described within this manuscript to be used as launching points for future research.

47 OTHER INSTRUMENTATION↗