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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

The Earth Surface Mineral Dust Source Investigation: An Earth Science Imaging Spectroscopy Mission

The Earth Surface Mineral Dust Source Investigation, EMIT, is planned to operate from the International Space Station starting no earlier than the fall of 2021. EMIT will use visible to short wavelength infrared imaging spectroscopy to determine the mineral composition of the arid land dust source regions of the Earth to advance our knowledge of the radiative forcing effect of these aerosols. Mineral dust emitted into the atmosphere under high wind conditions is an element of the Earth system with many impacts to the Earth’s energy balance, atmosphere, surface, and oceans. The Earth’s mineral dust cycle with source, transport, and deposition phases are studied with advanced Earth System Models. Because the chemical composition, optical and surface properties of soil particles vary strongly with the mineral composition of the source, these models require knowledge of surface soil mineral dust source composition knowledge to accurately understand dust impacts on the Earth system now and in the future. At present, compositional knowledge of the Earth’s mineral dust source regions from existing data sets is uncertain as a result of limited measurements. EMIT will use spectroscopically derived surface mineral composition to update the prescribe boundary conditions for state-of-the-art Earth System Models. The EMIT-initialized models will be used to investigate the impact of direct radiative forcing in the Earth system that depends strongly on the composition of the mineral dust aerosols emitted into the atmosphere. These new measurements and related products will be used to address the EMIT science objectives and made available to the science community for additional investigations. An overview of the EMIT science, development, and mission is presented in this paper.

Green, Robert O.↗
NASA NTRS1999

Comparison of Continuous Wave CO2 Doppler Lidar Calibration Using Earth Surface Targets in Laboratory and Airborne Measurements

Routine backscatter, beta, measurements by an airborne or space-based lidar from designated earth surfaces with known and fairly uniform beta properties can potentially offer lidar calibration opportunities. This can in turn be used to obtain accurate atmospheric aerosol and cloud beta measurements on large spatial scales. This is important because achieving a precise calibration factor for large pulsed lidars then need not rest solely on using a standard hard target procedure. Furthermore, calibration from designated earth surfaces would provide an inflight performance evaluation of the lidar. Hence, with active remote sensing using lasers with high resolution data, calibration of a space-based lidar using earth's surfaces will be extremely useful. The calibration methodology using the earth's surface initially requires measuring beta of various earth surfaces simulated in the laboratory using a focused continuous wave (CW) CO2 Doppler lidar and then use these beta measurements as standards for the earth surface signal from airborne or space-based lidars. Since beta from the earth's surface may be retrieved at different angles of incidence, beta would also need to be measured at various angles of incidences of the different surfaces. In general, Earth-surface reflectance measurements have been made in the infrared, but the use of lidars to characterize them and in turn use of the Earth's surface to calibrate lidars has not been made. The feasibility of this calibration methodology is demonstrated through a comparison of these laboratory measurements with actual earth surface beta retrieved from the same lidar during the NASA/Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission on NASA's DC8 aircraft from 13 - 26 September, 1995. For the selected earth surface from the airborne lidar data, an average beta for the surface was established and the statistics of lidar efficiency was determined. This was compared with the actual lidar efficiency determined with the standard calibrating hard target.

Jarzembski, Maurice A.↗
NASA NTRS1998

Comparison of Continuous-Wave CO2 Lidar Calibration by use of Earth-Surface Targets in Laboratory and Airborne Measurements

Backscatter of several Earth surfaces was characterized in the laboratory as a function of incidence angle with a focused continuous-wave 9.1 micro meter CO2 Doppler lidar for use as possible calibration targets. Some targets showed negligible angular dependence, while others showed a slight increase with decreasing angle. The Earth-surface signal measured over the complex Californian terrain during a 1995 NASA airborne mission compared well with laboratory data. Distributions of the Earth's surface signal shows that the lidar efficiency can be estimated with a fair degree of accuracy, preferably with uniform Earth-surface targets during flight for airborne or space-based lidar.

Jarzembski, Maurice A.↗
NASA NTRS1999

Comparison of Continuous Wave CO2 Doppler Lidar Calibration using Earth Surface Targets in Laboratory and Airborne Measurements

Earth's surface signal was measured using a continuous wave 9.1 micron lidar over varying Californian terrain during a 1995 NASA airborne mission. These measurements were compared with laboratory backscatter measurements of various Earth surfaces giving good agreement, suggesting that the lidar efficiency can be estimated fairly well using Earth's surface signal.

Jarzembski, Maurice A.↗
NASA NTRS2020

Optical Design of the Earth Surface Mineral Dust Source Investigation (EMIT) Imaging Spectrometer

The Earth Surface Mineral Dust Source Investigation (EMIT) instrument is a high fidelity imaging spectrometer developed to characterize surface mineralogy of the Earth’s dust source regions over the spectral range of 380- 2500 nm and spectral sampling of 7.4 nm. EMIT will close the current knowledge gap in dust source mineral composition by collecting over 1 billion high signal-to-noise ratio spectra in this region of our planet. These new measurements will be used in conjunction with state-of-the-art Earth System Models to understand and reduce the uncertainty in the radiative forcing effect of mineral dust aerosols. EMIT will be deployed on the International Space Station that has an orbit that is well suited for measuring the arid land regions of the Earth. The optical design utilizes a Dyson spectrometer to reduce volume and mass for a fast (F/1.8) and wide swath (1240 samples) optical system. An overview of the EMIT optical design, development, and current status are discussed.

Green, Robert O.↗
NASA NTRS2018

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

In this paper we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Earth observations↗
NASA NTRS1993

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Lure, Y. M. Fleming↗
NASA NTRS2000

Remote Sensing of Aerosol Backscatter and Earth Surface Targets By Use of An Airborne Focused Continuous Wave CO2 Doppler Lidar Over Western North America

Airborne lidar systems are used to determine wind velocity and to measure aerosol or cloud backscatter variability. Atmospheric aerosols, being affected by local and regional sources, show tremendous variability. Continuous wave (cw) lidar can obtain detailed aerosol loading with unprecedented high resolution (3 sec) and sensitivity (1 mg/cubic meter) as was done during the 1995 NASA Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission over western North America and the Pacific Ocean. Backscatter variability was measured at a 9.1 micron wavelength cw focused CO2 Doppler lidar for approximately 52 flight hours, covering an equivalent horizontal distance of approximately 30,000 km in the troposphere. Some quasi-vertical backscatter profiles were also obtained during various ascents and descents at altitudes that ranged from approximately 0.1 to 12 km. Similarities and differences for aerosol loading over land and ocean were observed. Mid-tropospheric aerosol backscatter background mode was approximately 6 x 10(exp -11)/ms/r, consistent with previous lidar datasets. While these atmospheric measurements were made, the lidar also retrieved a distinct backscatter signal from the Earth's surface from the unfocused part of the focused cw lidar beam during aircraft rolls. Atmospheric backscatter can be highly variable both spatially and temporally, whereas, Earth-surface backscatter is relatively much less variant and can be quite predictable. Therefore, routine atmospheric backscatter measurements by an airborne lidar also give Earth surface backscatter which can allow for investigating the Earth terrain. In the case where the Earth's surface backscatter is coming from a well-known and fairly uniform region, then it can potentially offer lidar calibration opportunities during flight. These Earth surface measurements over varying Californian terrain during the mission were compared with laboratory backscatter measurements using the same lidar of various Earth surfaces giving good agreement, suggesting that the lidar efficiency, and thus a lidar calibration factor for detection, can be estimated fairly well using Earth's surface signal.

Jarzembski, Maurice A.↗
NASA NTRS2001

Radiometric Calibration of an Airborne CO2 Pulsed Doppler Lidar Using a Natural Earth Surface

Radiometric calibration of an airborne CO2 pulsed Doppler lidar has been accomplished using surface retro-reflection signals from the White Sands National Monument, New Mexico, USA. Two circular passes were made at altitudes of 6.26 and 9.26 km. The computed calibration factors for both altitudes are in excellent agreement with the value derived from standard ground-based measurements involving a fixed sandpaper target of known reflectance. This finding corroborates a previous study that successfully calibrated an airborne continuous-wave Doppler lidar using a variety of natural Earth surfaces. The present results indicate that relatively uniform Earth-surface targets can be used for in-flight calibration of pulsed airborne, and, in principal, spaceborne lidars.

Cutten, Dean R.↗
NASA NTRS2006

Applying Parallel Adaptive Methods with GeoFEST/PYRAMID to Simulate Earth Surface Crustal Dynamics

This viewgraph presentation reviews the use Adaptive Mesh Refinement (AMR) in simulating the Crustal Dynamics of Earth's Surface. AMR simultaneously improves solution quality, time to solution, and computer memory requirements when compared to generating/running on a globally fine mesh. The use of AMR in simulating the dynamics of the Earth's Surface is spurred by future proposed NASA missions, such as InSAR for Earth surface deformation and other measurements. These missions will require support for large-scale adaptive numerical methods using AMR to model observations. AMR was chosen because it has been successful in computation fluid dynamics for predictive simulation of complex flows around complex structures.

GeoFEST↗
NASA NTRS2011

Forty-Year Calibrated Record of Earth-Surface Reflected Radiance from Landsat: A Review

Sensors on Landsat satellites have been collecting images of the Earth's surface for nearly 40 years. These images have been invaluable for characterizing and detecting changes in the land cover and land use of the world. Although initially conceived as primarily picture generating sensors, even the early sensors were radiometrically calibrated and spectrally characterized prior to launch and incorporated some capabilities to monitor their radiometric calibration once on orbit. Recently, as the focus of studies has shifted to monitoring Earth surface parameters over significant periods of time, serious attention has been focused toward bringing the data from all these sensors onto a common radiometric scale over this 40-year period. This effort started with the most recent systems and then was extended back in time. Landsat-7 ETM+, the best-characterized sensor of the series prior to launch and once on orbit, and the most stable system to date, was chosen to serve as the reference. The Landsat-7 project was the first of the series to build an image assessment system into its ground system, allowing systematic characterization of its sensors and data. Second, the Landsat-5 TM (still operating at the time of the Landsat-7 launch and continues to operate) calibration history was reconstructed based on its internal calibrator, vicarious calibrations, pseudo-invariant sites and a tie to Landsat-7 ETM+ at the time of the commissioning of Landsat-7. This process was performed in two iterations: the earlier one relied primarily on the TM internal calibrator. When this was found to have some deficiencies, a revised calibration was based more on pseudo-invariant sites, though the internal calibrator was still used to establish the short-term variations in response due to icing build up on the cold focal plane. As time progressed, a capability to monitor the Landsat-5 TM was added to the image assessment system. The Landsat-4 TM, which operated from 1982-1992, was the third system to which the radiometric scale was extended. The limited and broken use of the Landsat-4 TM made this analysis more difficult. Eight-day separated image pairs from Landsat-5 combined with analysis of pseudo invariant sites established this history. The fourth and most challenging effort was making the Landsat-1 to -5 MSS sensors' data internally radiometrically consistent. This effort was particularly complicated by the age of the MSS data, varying formats and processing levels in the archive, limited datasets, and limited documentation available. Ultimately, pseudo-invariant sites were identified in North America and used for this effort. Note that most of the Landsat-MSS archived data had already been calibrated using the MSS internal calibrators, so this processing was imbedded in the result. The final effort was developing an absolute scale for Landsat MSS similar to what was already established for the "TM" sensors. This was accomplished by using simultaneous data from Landsat-5 MSS and Landsat-5 TM, accounting for spectral differences between the sensors using EO-1 Hyperion data. The recalibrated history of the Landsat data and implications to users are discussed. The key result from this work is a consistently calibrated Landsat data archive that spans nearly 40 years with total uncertainties on the order of 10% or less for most sensors and bands.

Markham, Brian↗
NASA NTRS2001

A Geosynchronous Synthetic Aperture Provides for Disaster Management, Measurement of Soil Moisture, and Measurement of Earth-Surface Dynamics

A GEO-based Synthetic Aperture Radar (SAR) could provide daily coverage of basically all of North and South America with very good temporal coverage within the mapped area. This affords a key capability to disaster management, tectonic mapping and modeling, and vegetation mapping. The fine temporal sampling makes this system particularly useful for disaster management of flooding, hurricanes, and earthquakes. By using a fairly long wavelength, changing water boundaries caused by storms or flooding could be monitored in near real-time. This coverage would also provide revolutionary capabilities in the field of radar interferometry, including the capability to study the interferometric signature immediately before and after an earthquake, thus allowing unprecedented studies of Earth-surface dynamics. Preeruptive volcano dynamics could be studied as well as pre-seismic deformation, one of the most controversial and elusive aspects of earthquakes. Interferometric correlation would similarly allow near real-time mapping of surface changes caused by volcanic eruptions, mud slides, or fires. Finally, a GEO SAR provides an optimum configuration for soil moisture measurement that requires a high temporal sampling rate (1-2 days) with a moderate spatial resolution (1 km or better). From a technological point of view, the largest challenges involved in developing a geosynchronous SAR capability relate to the very large slant range distance from the radar to the mapped area. This leads to requirements for large power or alternatively very large antenna, the ability to steer the mapping area to the left and right of the satellite, and control of the elevation and azimuth angles. The weight of this system is estimated to be 2750 kg and it would require 20 kW of DC-power. Such a system would provide up to a 600 km ground swath in a strip-mapping mode and 4000 km dual-sided mapping in a scan-SAR mode.

Madsen, Soren↗