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NASA NTRS2022

Determining the Primary Sources of Uncertainty in Retrieval of Marine Remote Sensing Reflectance From Satellite Ocean Color Sensors

Uncertainties in the retrieval of the remote sensing reflectance, R_rs, from Ocean Color (OC) satellite sensors have a strong impact on the performance of algorithms for the estimation of chlorophyll-a, mineral concentrations, and inherent optical properties (IOPs). The uncertainties are highest in the blue bands. The total radiance measured at the top of the atmosphere captures the instantaneous state of the atmosphere-ocean system: the in-water conditions, sky and Sun glint reflected from the wind-roughened ocean surface, as well as light scattered from molecules and aerosols in the atmosphere. Each of these components has associated uncertainties, and when combined with the additional uncertainties from the instrument noise and the atmospheric correction process, they contribute to the total uncertainty budget for the retrieved R_rs. We analyzed the contribution of each component uncertainties to the total R_rs uncertainties in SNPP-VIIRS level 2 products, taking advantage of the spectral differences between the components. We examined multiple scenes in the open ocean and coastal waters at spatial resolutions ranging from 2250 to 5250 m by comparing the retrieved R_rs to in situ measurements made at several AERONET-OC sites and at the MOBY site. It was shown that uncertainties associated with the molecular (Rayleigh) scattering play the most significant role, while the contributions of other components are usually smaller. Uncertainties in Rayleigh scattering are primarily attributed to the variability of Rayleigh optical thickness (ROT) with a standard deviation of approximately 1.5% of ROT, which can largely explain the frequency of negative R_rs retrievals as observed using the current standard atmospheric correction process employed by NASA. Variability of the sky light reflected from the ocean surface in some conditions also contributed to uncertainties in the blue; water variability proportional to R_rs had a very pronounced peak in the green at coastal sites.

remote sensing reflectance↗
NASA NTRS2000

Comparison of Sunphotometric Measurements During the Fall 1997 ARM Intensive Observation Period

In the Fall of 1997 the Atmospheric Radiation Measurement (ARM) program held an intensive observation period (IOP) to study atmospheric aerosols using in situ and remote sensing techniques at its Southern Great Plains (SGP) site near Lamont, Oklahoma. As part of this experiment five automated, tracking sunphotometers were present to measure total column aerosol optical depth over the three-week period. which included many clear days or parts of days that were clear. The World Meteorological Organization (WMO 1993) has recommended a comparison of tracking sunphotometers to assess the ability of different instruments to arrive at similar aerosol optical depths. It was further recommended that the comparison be staged at a clean mountain site. In fact, this comparison has not occurred, but the comparison that we describe in this paper is representative of what contemporary instruments may accomplish in an environment more typical of sites where aerosols measurements will be required. The measurements were made over the period 15 September to 5 October 1997. The aerosol loading varied from extremely clean to moderately turbid conditions. In the next section the instruments will be described along with a brief explanation of the calibration techniques. The third section contains the results compared graphically on moderately turbid and fairly clean days and in a table representing the whole period. The paper ends with a section of discussion and a summary of the results.

Michalsky, J. J.↗
NASA NTRS2018

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗
NASA NTRS2018

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗
NASA NTRSDate not supplied

PACE Microphysical Aerosol Properties from Polarimetry (PACE-MAPP)

We present the Plankton, Aerosols, Clouds and Ecosystems Microphysical Aerosol Properties from Polarimetry (PACE-MAPP) polarimetric remote sensing algorithm developed for the newly launched NASA PACE satellite observing system. The objective of PACE-MAPP is to retrieve detailed fine-mode (marine, pollution and smoke) and coarse-mode (sea-salt and dust) aerosol properties over the ocean for a range of light to heavy aerosol loadings using PACE’s polarimetric-imaging capabilities at multiple angles and wavelengths from the ultraviolet (UV) to the near-infrared (NIR). An additional objective for PACE-MAPP is to discriminate aerosols from thin clouds. The PACE-MAPP polarimetric remote sensing retrieval algorithm uses coupled atmosphere-ocean vector radiative transfer, optimal estimation, artificial intelligence and powerful inherent optical property look-up-tables for the Earth’s aerosol, cloud, and hydrosol particles. PACE-MAPP is the only retrieval algorithm designed to invert aerosol/ocean products using both polarimeters onboard PACE. We present results using PACE-MAPP to retrieve aerosol and ocean remote sensing products from measurements by the Hyper-Angular Rainbow Polarimeter #2 (HARP2) and Spectro-polarimeter for Planetary Exploration one (SPEXone) polarimeter instruments onboard PACE.

Snorre Stamnes↗
NASA NTRSDate not supplied

Hyper-Spectral Infrared Remote Sensing for Wildfire-Related Research and Air Quality Monitoring

The National Airborne Sounder Testbed-Interferometer (NAST-I) is an airborne FTS remote sensor that nominally flies on NASA high-altitude aircraft to serve as a spaceborne instrument simulator. NAST-I continues to serve as a pathfinder for future satellite FTS systems and the next generation advanced atmospheric sounders in general. NAST-I provides high resolution spectrally resolved infrared radiances. NAST-I retrieval products characterizing the surface (i.e., skin temperature and spectral emissivity), atmosphere (i.e., profiles of temperature, moisture, ozone, carbon monoxide, and other trace species), and clouds (e.g., optical depth, particle size, temperature, and height) can be used to support fire-related monitoring and research. NAST-I provided 3-d characterizations of wildfire-induced plumes of CO during the FIREX-AQ field campaign (conducted during 2019) which showed the intensity and size evolution of wildfire plumes at high spatial and temporal resolutions. Wildfire-induced CO plumes, in conjunction with their evolution, transport, and age have been identified and recently published in scientific journals. Other research applications, such as surface emissivity changes due to fire burning of ground landscape, have been under investigation. These products could be used in support of wildfire management to better inform decision making and operations for pre-, active, and post-fire environments.

remote sensing↗
NASA NTRS1971

An interim report on remote sensing of environmental pollutants with a Fourier interference spectrometer.

A small Fourier interference spectrometer for sensing environmental pollutants from spacecraft has been developed at the Jet Propulsion Laboratory. The instrument is intended for obtaining high spectral resolution infrared absorption spectra in the 1.2 to 5.5 micron region at speeds sufficiently high for medium altitude orbital satellite surveys. The paper reviews basic details of the instrument servo and infrared detection systems, previously described, as well as recent developments. In particular, the data-handling system, data reduction techniques and optical tolerance problems are discussed. Preliminary results are included.

Schindler, R. A.↗
NASA NTRS1991

Infrared technology XVII; Proceedings of the Meeting, San Diego, CA, July 22-26, 1991

Recent advances in IR technologies and their application to all types of IR systems are reported focusing on the JPL Space Infrared Telescope Facility (SIRTF), JPL instruments and systems for observation of earth and the atmosphere, staring arrays and thermal imaging, ten-year updates of IR techniques, infrared in the USSR, simulation and testing, focal-plane and optical technologies, and military and scientific applications. Particular attention is given to SIRTF stray light analysis, SIRTF focal-plane technologies, long-wave IR detectors based on III-V materials, IR lidars for atmospheric remote sensing, a firefly system concept, a high-fill-factor monolithic IR image sensor, atmospheric laser-transmission tables simply generated, ORION semiconductor optical detectors, postprocessing of thermograms in IR nondestructive testing, evaluation of the IR signature of dynamic air targets, the current status of InGaAs detector arrays for 1-3 microns, a dual-band optical system for IR multicolor signal processing, and blackbody radiators for field calibration.

Andresen, Bjorn F.↗
NASA NTRS1993

An Imaging Interferometer for Terrestrial Remote Sensing

A prototype imaging interferometer called DASI (digital array scanned interferometer) is under development at our laboratories. Our objective is to design an instrument for remote sensing of Earth's atmosphere and surface. This paper describes the unusual characteristics of DASIs which make them promising candidates for ground and aircraft-based terrestrial measurements. These characteristics include superior signal-to-noise, design simplicity and compactness, relative to dispersion based imaging spectrometers. Perhaps one of the most notable features of DASIs is their ability to acquire an entire interferogram simultaneously without any moving optical elements. We also describe selected laboratory and ground based field measurements using the prototype DASI. A CCD detector array was placed at the DASI detector plane for wavelength coverage from 0.4 to 1.0 micron. A NICMOS MCT detector was used for coverage from 1.1 to 2.2 micron. The DASI was configured to have a spectral resolution of about 300 1/cm, a spatial field of view of 5 degrees, and a constant number of transverse spatial elements (detector dependent) for each exposure frame. Frame exposure rates were up to 0.6 Hz with the potential to achieve 5 Hz. Image cube measurements of laboratory targets and terrestrial scenes were obtained by multiple frame scanning over the field of view. These data sets reveal the potential science yields from obtaining simultaneous high resolution spatial and spectral information.

Hammer, Philip D.↗
NASA NTRS2003

A Secondary Ion Mass Analyzer for Remote Surface Composition Analysis of the Galilean Moons

Galileo in-situ dust measurements have shown that the Galilean moons are surrounded by tenuous dust clouds formed by collisional ejecta from their icy surfaces, kicked up by impacts of interplanetary micrometeoroids. The majority of the ejecta dust particles have been sensed at altitudes below five between 0.5 and 1 micron, just above the detector threshold, indicating a size distribution decreasing towards bigger particles. their parent bodies. They carry information about the properties of the surface from which they have been kicked up. In particular, these grains may carry organic compounds and other chemicals of biological relevance if they exist on the icy Galilean moons. In-situ analysis of the grain composition with a sophisticated dust analyzer instrument flying on a Jupiter Icy Moons Orbiter can provide important information about geochemical and geophysical processes during the evolutionary histories of these moons which are not accessible with other techniques from an orbiter spacecraft. Thus, spacecraft-based in-situ dust measurements can be used as a diagnostic tool for the analysis of the surface composition of the moons. This way, the in-situ measurements turn into a remote sensing technique by using the dust instrument like a telescope for surface investigation. An instrument capable of very high resolution composition analysis of dust particles is the Cometary Secondary Ion Mass Analyzer (COSIMA). The instrument was originally developed for the Comet Rendezvous and Asteroid Flyby (CRAF) mission and has now been built for ESA'S comet orbiter Rosetta. Dust particles are collected on a target and are later located by an optical microscope camera. A pulsed primary indium ion gun partially ionizes the dust grains. The generated secondary ions are accelerated in an electric field and travel through a reflectron-type time-of-flight ion mass spectrometer.

Krueger, H.↗
NASA NTRS2022

Space-based Passive Aerosol Remote Sensing from the Multi-angle Imaging SpectroRadiometer (MISR) Aboard NASA’s Terra Satellite

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been acquiring multi-angle imagery of the Earth aboard NASA’s Terra satellite since February 2000, providing an ongoing record of atmosphere and surface properties more than two decades long. MISR offers a combination of moderately high spatial resolution imagery at nine view angles in each of four visible/near-infrared spectral bands, global coverage about once per week, and carefully maintained onboard radiometric calibration. Unique algorithms retrieve aerosol column-amount and constraints on particle microphysical and optical properties, as well as the heights and motion vectors of aerosol plumes from sources such as wildfires, volcanic eruptions, and dust storms. Applications of MISR aerosol data to climate and air quality are discussed here along with a summary of some key scientific findings enabled by the instrument’s unique measurement approach.

aerosols↗
NASA NTRS1994

BIOME: An Ecosystem Remote Sensor Based on Imaging Interferometry

Until recent times, optical remote sensing of ecosystem properties from space has been limited to broad band multispectral scanners such as Landsat and AVHRR. While these sensor data can be used to derive important information about ecosystem parameters, they are very limited for measuring key biogeochemical cycling parameters such as the chemical content of plant canopies. Such parameters, for example the lignin and nitrogen contents, are potentially amenable to measurements by very high spectral resolution instruments using a spectroscopic approach. Airborne sensors based on grating imaging spectrometers gave the first promise of such potential but the recent decision not to deploy the space version has left the community without many alternatives. In the past few years, advancements in high performance deep well digital sensor arrays coupled with a patented design for a two-beam interferometer has produced an entirely new design for acquiring imaging spectroscopic data at the signal to noise levels necessary for quantitatively estimating chemical composition (1000:1 at 2 microns). This design has been assembled as a laboratory instrument and the principles demonstrated for acquiring remote scenes. An airborne instrument is in production and spaceborne sensors being proposed. The instrument is extremely promising because of its low cost, lower power requirements, very low weight, simplicity (no moving parts), and high performance. For these reasons, we have called it the first instrument optimized for ecosystem studies as part of a Biological Imaging and Observation Mission to Earth (BIOME).

Peterson, David L.↗
NASA NTRS2002

NASA's New Laser Risk Reduction Program For Future Space Lidar Missions

NASA has been performing ground, airborne, and space-based scientific measurements since it was formed in 1958. Initial ground and airborne measurements were made with in situ instruments. By necessity, initial earth observation space-based missions were accomplished with passive remote sensing. Active microwave radar was added to the sensor repertoire in the late 1970s. A few key measurements important to NASA remain unaccomplished, however, despite the passive and radar successes. These critical measurements include space-based altimetry; and high spatial resolution profiling of aerosol properties, wind velocity, clouds, and molecular concentrations. Fortunately, a new technology, active optical radar or laser radar or lidar, has matured to the point that the last decade has seen a growing consideration of lidar for space missions. Part of the surge in consideration of lidar has been the tremendous progress in solid-state lasers fueled by advances in crystal growth quality and pump laser diode technology.

Michael J. Kavaya↗
NASA NTRS2019

Cloud Remote Sensing with EPIC/DSCOVR Observations: A Sensitivity Study with Radiative Transfer Simulations

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) views nearly the whole sunlit face of the Earth with 10 spectral bands ranging from the UV to the near-infrared, including two oxygen absorbing bands centered at 764 nm (A-band) and 687.75 nm (B-band). Clouds are among the primary remote sensing targets using EPIC images because of their important impacts on the Earth’s radiation budget. In order to facilitate the EPIC cloud data product development, we have built a radiative transfer simulator featuring flexible cloud microphysical parameters, gas absorptions, and the instrument line shape functions for each EPIC band. The radiative transfer simulator is used to explore the sensitivity of EPIC observations on liquid-phase cloud microphysical parameters, including optical depth, geometric thickness, and cloud top height. We found that the ratios of the reflectances in the oxygen A and B bands to their respective continuum measurements can be used to increase the confidence level of cloud masking over scenes with sun-glint. In addition, the 388 nm band can be used to differentiate low and high clouds with the uncertainty of roughly 2–3 km. Combining this information with the oxygen absorption bands, the cloud geometric thickness can be obtained with the rough uncertainty of 3–4 km.

atmospheric and ocean optics↗
NASA NTRSDate not supplied

The Ring Current ENA Instrument on the NASA STORIE Mission

NASA has recently selected the Storm Time O+ Ring current Imaging Evolution (STORIE) mission to study the evolution of Earth’s ring current and the role of composition and dynamics during geomagnetic storms. STORIE addresses this inner magnetospheric science through the use of a Ring current Energetic Neutral Atom (RENA) instrument hosted on the International Space Station (ISS). This novel vantage point for ENA imaging has a number of scientific and implementation advantages. RENA is a high sensitivity remote sensing ENA imager and composition instrument with a field of view of 90 x 2 degrees, and an angular resolution of 2 x 2 degrees. The instrument aperture points zenith and its long dimension is oriented perpendicular to the ISS ram direction. As a result, RENA acts as a “push broom” imager building up a complete sky scan of the ring current in a single 90-minute ISS orbit. The instrument employs electrostatic optics along with a foil-MCP TOF x PHA x Delay-Line position measurement technique to resolve H and O energy spectra in the energy range 10-500 KeV for each look direction. Furthermore, it employs triple+ time and position coincidence to effectively reduce background noise from geocoronal and black sky UV as well as penetrating radiation. The abundant mass, power, and telemetry, resources of the ISS allow for large instrument aperture, very high sensitivity, complex data product and simplified operations, altogether contributing towards a high signal to noise (S/N) measurement.

Space Science↗
NASA NTRSDate not supplied

An Overview of the NASA ADM-Aeolus Cal/Val Test Flight Campaign

Lidars are uniquely capable of collecting high precision and high spatio-temporal observations that have been used for atmospheric process studies from the ground, aircraft, and space for over 30 years. The Atmospheric Dynamics Mission Aeolus (ADM-Aeolus), the first-ever spaceborne Doppler wind lidar, was developed by the European Space Agency and launched in August 2018. The ADM-Aeolus Atmospheric Laser Doppler Instrument (ALADIN) observes profiles of the component of the wind vector and aerosol optical properties along the instrument’s line-of-sight direction on a global scale. Two airborne lidar systems have been developed at NASA Langley Research Center in recent years that collect measurements in support of several NASA Earth Science Division focus areas. The Doppler Aerosol WiNd (DAWN) lidar measures vertical profiles of horizontal wind speed and direction. The High Altitude Lidar Observatory (HALO) measure high resolution profiles of atmospheric water vapor (WV) and aerosol and cloud optical properties. Though new space-based missions with advanced capabilities such as Aeolus are continuously being conceived and developed, there are limitations in terms of spatial and vertical detail and measurement precision that can be accomplished from space, thus airborne remote sensing observations like those from DAWN and HALO are required to fill these observational gaps as well as to calibrate and validate space-based measurements. Over a two-week period in April 2019 during their Aeolus Cal/Val Test Flight campaign, NASA conducted five research flights over the Eastern Pacific Ocean with the DC-8 aircraft to 1) demonstrate the DAWN Doppler wind lidar, HALO high spectral resolution lidar aerosol/cloud measurement and differential absorption lidar WV measurement capabilities across a range of atmospheric conditions, 2) demonstrate Aeolus Cal/Val flight strategies and compare DAWN and HALO measurements with Aeolus to gain an initial perspective of Aeolus performance, and 3) demonstrate how atmospheric dynamic processes can be resolved and better understood through simultaneous observations of wind, WV, and aerosol profile observations, coupled with numerical model and other remote sensing observations. This paper provides a brief description of the DAWN and HALO instruments, discusses the synergistic observations collected across a wide range of atmospheric conditions sampled during the DC-8 flights, and a summary of the validation of DAWN, HALO, and Aeolus observations and comparisons.

Kristopher M. Bedka↗
NASA NTRS2006

An Intercomparison of Microphysical Retrieval Algorithms for Upper Tropospheric Ice Clouds

The large horizontal extent, location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud scale processes in large-scale models and for accurately predicting the earth's future climate. A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade, however, there is room for improvement. Members of the Atmospheric Radiation measurement program (ARM) Cloud properties Working Group are involved in an intercomparison of optical depth(tau), ice water path, and characteristic particle size in clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for improvement.

Comstock, Jennifer M.↗
NASA NTRS2000

SMART Ground-based Radiation Measurements during PRIDE

We deployed a suite of ground-based remote sensing instruments - SMART (Surface Measurements for Atmospheric Radiative Transfer), at the Roosevelt Road Naval Station in Puerto Rico during the Puerto Rico Dust Experiment (PRIDE). The instruments include several solar and infrared broadband radiometers, a sunphotometer, a shadow-band radiometer, a micro-pulse lidar, a total-sky imager, a microwave radiometer, and two solar spectrometers. These radiometers were set up on a mobile platform and a solar tracker. During 27 June - 23 July, about 25 days of data were acquired under partially cloudy sky conditions. The diurnal air temperature was fluctuating around 28.6 C to within a few degrees. Daytime average of solar irradiance reaching at the surface was ranged from about 400 W/sq m on a rainy day to about 640 W/sq m on a cloud-free day. The infrared irradiance at the surface during the measurement period was averaged about 408 W/sq m. The heights of boundary layer, dusts and clouds were captured by lidar images. Based on sunphotometer and shadow-band radiometer retrievals, the aerosol optical thickness varied from below 0.1 to over 0.6. Combining with radiative transfer modeling and other in-situ and remote sensing measurements, our ground-based measurements provide vital information on understanding the long-range transport of African dust into the Caribbean.

Tsay, Si-Chee↗