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NASA NTRS2007

Remote Raman Sensor System for Testing of Rocks and Minerals

Recent and future explorations of Mars and lunar surfaces through rovers and landers have spawned great interest in developing an instrument that can perform in-situ analysis of minerals on planetary surfaces. Several research groups have anticipated that for such analysis, Raman spectroscopy is the best suited technique because it can unambiguously provide the composition and structure of a material. A remote pulsed Raman spectroscopy system for analyzing minerals was demonstrated at NASA Langley Research Center in collaboration with the University of Hawaii. This system utilizes a 532 nm pulsed laser as an excitation wavelength, and a telescope with a 4-inch aperture for collecting backscattered radiation. A spectrograph equipped with a super notch filter for attenuating Rayleigh scattering is used to analyze the scattered signal. To form the Raman spectrum, the spectrograph utilizes a holographic transmission grating that simultaneously disperses two spectral tracks on the detector for increased spectral range. The spectrum is recorded on an intensified charge-coupled device (ICCD) camera system, which provides high gain to allow detection of inherently weak Stokes lines. To evaluate the performance of the system, Raman standards such as calcite and naphthalene are analyzed. Several sets of rock and gemstone samples obtained from Ward s Natural Science are tested using the Raman spectroscopy system. In addition, Raman spectra of combustible substances such acetone and isopropanol are also obtained. Results obtained from those samples and combustible substances are presented.

Garcia, Christopher S.↗

NASA NTRS1973

Feasibility study of the application of existing techniques to remotely monitor hydrochloric acid in the atmosphere

A critical evaluation of existing optical remote sensors for HCl vapor detection in solid propellant rocket plumes is presented. The P branch of the fundamental vibration-rotation band was selected as the most promising spectral feature to sense. A computation of transmittance for HCl vapor, an estimation of interferent spectra, the application of these spectra to computer modelled remote sensors, and a trade-off study for instrument recommendation are also included.

Zwick, H.↗

NASA NTRS2018

GEONEX: Challenges in Producing MODIS-Like Land Products from a New Generation of Geostationary Sensors

The new generation geostationary (GEO) remote sensors (GOES-R ABI, Himawari AHI, and FY4 AGRI) provide high frequency (5-15 minute) observations spatially/spectrally similar to MODIS/VIIRS for land monitoring. These new features of GEO satellite sensors make producing MODIS like land products for terrestrial monitoring possible. The NASA Earth Exchange (NEX) team developed the GEONEX pipeline that is containerized, deployable on NASA Pleiades supercomputer as well as public cloud platforms (e.g. AWS). The processing pipeline is designed to take Himawari Standard Data (HSD) and GOES-16 L1b to generate surface reflectance (SR) and other high-level land remote sensing products. In order to produce low-Earth-orbiting (LEO) remote sensing compatible land products, inter-comparison between Himawari AHI and MODIS Terra/Aqua has been conducted in this research work. Comparisons of TOA reflectance and surface reflectance between AHI and Terra/Aqua are presented. Ray-Matching method was used to locate the co-located pixels, where GEO and LEO sensors look at the land target with similar Viewing Zenith Angle (VZA) and Viewing Azimuth Angle (VAA) simultaneously. Here, we address challenges associated with the selection of qualified pixels of similar solar illumination condition and atmosphere path. We used strict criterion to constrain the pixel selection: the time difference between GEO and LEO observations is less than +-2.5 mins, the cosine of VZA difference is less than 1%, and the VAA difference is less than 10 deg. We also discuss the strong radiometric consistency that the new generation GEO sensors along with the popular LEO sensors would benefit the environmental remote sensing community.

Li, Shuang↗

DOE OSTI2025

Propagating information content: an example with advection

The mathematical algorithm to derive geophysical information from remote sensing observations is called a retrieval. The mathematics of many retrieval problems are ill-posed, and thus a priori information is used to help constrain the derived geophysical variable to realistic values. One quantity of interest, therefore, is the information content of the observation. Perfect information content in the observation would be achieved if the retrieval were able to capture any perturbation in the desired geophysical variable with the proper magnitude. Many new data products can be derived by combining geophysical variables retrieved from multiple different remote sensors. This paper explores, for the first time, how to derive the information content of these derived products. The approach uses traditional error propagation techniques to derive the uncertainty of the derived field twice, both when the observations are used in the retrieval and also when only the a priori information from each remote sensor is propagated. These two uncertainties are then used to provide an estimate of the information content of the derived geophysical variable. This study demonstrates how to propagate the uncertainties from six different instruments to provide the information content for water vapor and temperature advection. A multi-month analysis demonstrates that, in a mean sense, the information content for temperature advection is nearly unity for all heights below 700 m while, the information content for water vapor advection is somewhat more variable but still larger than 0.6 in the convective boundary layer.

Turner, David D. [National Oceanic and Atmospheric↗

DOE OSTI2021

High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Satellite Remote Sensing of Atmospheric and Surface Properties on Daily and Decadal Time Scales

Satellite and airborne remote sensors can provide high-quality atmospheric and surface products such as atmospheric temperature, water vapor, trace gas, and aerosol vertical profiles, cloud, and surface properties. In this presentation, I will give an overview of various advanced forward and inversion models developed to retrieve these quantities. The satellite data used in this study includes hyperspectral thermal infrared and solar remote sensors such as AIRS, CrIS, IASI, CPF, and EMIT. I will also show some results of aerosol microphysical property retrievals using lidar and polarimeters.

Xu Liu↗

NASA NTRS2015

Architectures Toward Reusable Science Data Systems

Science Data Systems (SDS) comprise an important class of data processing systems that support product generation from remote sensors and in-situ observations. These systems enable research into new science data products, replication of experiments and verification of results. NASA has been building systems for satellite data processing since the first Earth observing satellites launched and is continuing development of systems to support NASA science research and NOAAs Earth observing satellite operations. The basic data processing workflows and scenarios continue to be valid for remote sensor observations research as well as for the complex multi-instrument operational satellite data systems being built today. System functions such as ingest, product generation and distribution need to be configured and performed in a consistent and repeatable way with an emphasis on scalability. This paper will examine the key architectural elements of several NASA satellite data processing systems currently in operation and under development that make them suitable for scaling and reuse. Examples of architectural elements that have become attractive include virtual machine environments, standard data product formats, metadata content and file naming, workflow and job management frameworks, data acquisition, search, and distribution protocols. By highlighting key elements and implementation experience we expect to find architectures that will outlast their original application and be readily adaptable for new applications. Concepts and principles are explored that lead to sound guidance for SDS developers and strategists.

Data Processing↗

NASA NTRS2014

Architectures Toward Reusable Science Data Systems

Data Processing↗

NASA NTRS2019

Active Optical Remote Sensing Sensors and Instrumentation for NASA’s Future Earth and Space Science Measurements/Missions

Abstract—Active optical (Laser/Lidar) measurement techniques are critical for the future National Aeronautics and Space Administration (NASA) Earth, Planetary Science, Exploration, and Aeronautics measurements. The latest science decadal surveys recommend a number of missions requiring active optical systems to meet the science measurement objectives and the aeronautics community continues to use Laser/Lidar technologies to meet the aeronautics measurement objectives. This presentation will provide an overview of NASA efforts in developing and maturing state-of-the-art advanced solid-state flight laser/lidar systems for airborne and space-borne remote sensing measurements. The presentation will also provide details of a strategic approach for active optical technologies and techniques to meet the NASA’s future Earth and Space Science measurement ments for space-based applications.

Singh, Upendra N.↗

NASA NTRS1975

Application of EREP, LANDSAT, and aircraft image data to environmental problems related to coal mining

Remote sensing techniques were used to study coal mining sites within the Eastern Interior Coal Basin (Indiana, Illinois, and western Kentucky), the Appalachian Coal Basin (Ohio, West Virginia, and Pennsylvania) and the anthracite coal basins of northeastern Pennsylvania. Remote sensor data evaluated during these studies were acquired by LANDSAT, Skylab and both high and low altitude aircraft. Airborne sensors included multispectral scanners, multiband cameras and standard mapping cameras loaded with panchromatic, color and color infrared films. The research conducted in these areas is a useful prerequisite to the development of an operational monitoring system that can be peridically employed to supply state and federal regulatory agencies with supportive data. Further research, however, must be undertaken to systematically examine those mining processes and features that can be monitored cost effectively using remote sensors and for determining what combination of sensors and ground sampling processes provide the optimum combination for an operational system.

Amato, R. V.↗

NASA NTRS1985

Blended SST fields combined SMMR/ship data (summary of technique)

All remote sensors have bias problems which vary in space and time. The infrared measurements are very sparse in cloudy areas: the SMMR has coverage limitations due to the interference of land areas and only half time operation. If one simply averaged the data from these various sources, the combination of the biases and varying sampling would introduce artifacts into the analyzed product which would reflect the sampling and which could be quite misleading. The remote sensors provide reasonable estimates of gradients of SST over length scales greater than the sensor resolution but smaller than hemispheric. Ships can be considered unbiased but are poorly distributed on small scales except in the densest shipping lanes. An analysis scheme based on a suggestion by Holl was developed which exploits just this approximately complementarity to provide an improved SST analysis. The resulting accuracy appears to be in the required approx. 0.5 C range for the particular case of using SMMR and ship data to produce two degree latitude by two degrees longitude monthly analyses.

Wilheit, T. T.↗

NASA NTRS1992

Activities relating to understanding the initiation, organization and structure of moist convection in the Southeast environment

In the spring and summer of 1986, NASA/Marshall Space Flight Center (MSFC) will sponsor the Satellite Precipitation And Cloud Experiment (SPACE) to be conducted in the Central Tennessee, Northern Alabama, and Northeastern Mississippi area. The field program will incorporate high altitude flight experiments associated with meteorological remote sensor development for future space flight, and an investigation of precipitation processes associated with mesoscale and small convective systems. In addition to SPACE, the MIcroburst and Severe Thunderstorm (MIST) program, sponsored by the National Science Foundation (NSF), and the FAA-Lincoln Laboratory Operational Weather Study (FLOWS), sponsored by the Federal Aviation Administration (FAA), will take place concurrently within the SPACE experiment area. All three programs (under the joint acronym COHMEX (COoperative Huntsville Meteorological EXperiment)) will provide a data base for detailed analysis of mesoscale convective systems while providing ground truth comparisons for remote sensor evaluation. The purpose of this document is to outline the experiment design criteria for SPACE, and describe the special observing facilities and data sets that will be available under the COHMEX joint program. In addition to the planning of SPACE-COHMEX, this document covers three other parts of the program. The field program observations' main activity was the operation of an upper air rawinsonde network to provide ground truth for aircraft and spacecraft observations. Another part of the COHMEX program involved using boundary layer mesoscale models to study and simulate the initiation and organization of moist convection due to mesoscale thermal and mechanical circulations. The last part of the program was the collection, archival and distribution of the resulting COHMEX-SPACE data sets.

Mcnider, Richard T.↗

NASA NTRS1992

Acousto-optic tunable filter multispectral imaging system

This paper discusses recent activities of Jet Propulsion Laboratory in the development of a new type of remote sensing multispectral imaging instruments using acousto-optic tunable filter (AOTF) as programmable bandpass filter. This remote sensor provides real-time operation; observational flexibility; measurements of spectral, spatial, and polarization information using a single instrument; and compact, solid state structure without moving parts. Two microcomputer-controlled AOTF imaging spectrometer breadboard systems were designed and built. One operates in the wavelength range of 0.48-0.76 micron and the other in the range of 1.2-2.5 micron. Experiments were performed using these two systems to observe geological and botanical objects in laboratory and outdoor environment. Results have demonstrated the feasibility of using the AOTF multispectral imaging system as a real-time versatile remote sensor with operational flexibility for future Army tactical applications.

Cheng, Li-Jen↗

NASA NTRSDate not supplied

Providing Satellite-Assisted Particulate Matter (SAPM) Estimates for the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group

The Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group is an international forum that promotes collaboration amongst researchers of these three atmospheric aerosol communities. MIRA currently consists of a collection of five interdisciplinary and independently funded Topic groups with focused goals and generally involve requests for additional scientific datasets. Participants of the MIRA Satellite-Assisted Particulate Matter (SAPM) Topic group study particulate matter with diameters smaller than 2.5 microns (PM2.5), because of its substantial role in air pollution and the resulting negative impacts on human health. SAPM seeks to provide intercomparisons of different methods and techniques for obtaining surface PM2.5 proxies using spaceborne passive and active remote sensors, aerosol models, and in situ observations. The ultimate motivation of SAPM is to provide greater PM2.5 coverage than in situ ground stations, which are limited in some areas of the contiguous United States and large regions throughout the globe. In this poster presentation, we provide an overview of the PM2.5 estimation techniques applied by current SAPM team members, as well as the strengths and limitations of each technique. These approaches include spaceborne lidar (Cloud-Aerosol Lidar with Orthogonal Polarization) only, combined spaceborne lidar (Cloud Aerosol Transport System) and a model (Goddard Earth Observing System), and using aerosol optical depth (AOD) from a spaceborne passive remote sensor (Moderate Resolution Imaging Spectroradiometer) to explore city trends in AOD and relate those to city trends in PM2.5. Also in this poster presentation, we highlight results of our SAPM study of India, a country characterized by high levels of PM2.5 concentrations. We show the temporal and spatial variability of PM2.5 over India derived using various approaches and validation with ground-based in situ PM2.5 observations. The SAPM Topic group actively seeks additional collaborators, including those working with in situ aerosol measurements, and is interested in aerosol datasets to improve and/or validate the PM2.5 estimates.

Travis D Toth↗

NASA NTRS2013

Error Consistency Analysis Scheme for Infrared Ultraspectral Sounding Retrieval Error Budget Estimation

Great effort has been devoted towards validating geophysical parameters retrieved from ultraspectral infrared radiances obtained from satellite remote sensors. An error consistency analysis scheme (ECAS), utilizing fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of mean difference and standard deviation of error in both spectral radiance and retrieval domains. The retrieval error is assessed through ECAS without relying on other independent measurements such as radiosonde data. ECAS establishes a link between the accuracies of radiances and retrieved geophysical parameters. ECAS can be applied to measurements from any ultraspectral instrument and any retrieval scheme with its associated RTM. In this manuscript, ECAS is described and demonstrated with measurements from the MetOp-A satellite Infrared Atmospheric Sounding Interferometer (IASI). This scheme can be used together with other validation methodologies to give a more definitive characterization of the error and/or uncertainty of geophysical parameters retrieved from ultraspectral radiances observed from current and future satellite remote sensors such as IASI, the Atmospheric Infrared Sounder (AIRS), and the Cross-track Infrared Sounder (CrIS).

Zhou, Daniel K.↗

NASA NTRSDate not supplied

Satellite-Assisted Particulate Matter (SAPM) for the Models, In situ, and Remote Sensing of Aerosols (MIRA) Working Group

Models, In situ, and Remote sensing of Aerosols (MIRA) is an international working group that provides a forum for collaborations amongst these three atmospheric aerosol communities. MIRA consists of a collection of interdisciplinary and independently funded Topic/Project groups with clear goals and generally characterized by requests for additional scientific data. The Satellite-Assisted Particulate Matter (SAPM) Topic group focuses on the study of fine particulate matter (PM2.5), as it is a major contributor to air pollution and negatively impacts human health. Our group aims to provide intercomparisons of various methods and techniques for estimating surface PM2.5 assisted by satellite remote sensors (passive and active), global aerosol models, and in situ aerosol measurements. The overall motivation of our work is to enhance PM2.5 coverage beyond in situ ground stations, which can be limited. In this presentation, we provide an overview of various PM2.5 estimation approaches by current SAPM team members, as each approach has its own strengths and limitations. One approach uses near-surface aerosol extinction retrievals from the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and an assumed value of mass extinction efficiency to derive PM2.5 concentrations (Toth et al 2019). A study using this method found a promising agreement (R=0.60; slope=0.89) with U.S. Environmental Protection Agency (EPA) in situ PM2.5 measurements over the contiguous United States (CONUS) for a 12-year (2007-2018) period (Toth et al 2022). In a different approach combining spaceborne lidar and a model, the Cloud Aerosol Transport System (CATS) lidar and Goddard Earth Observing System (GEOS) model are blended in an ensemble variational assimilation scheme to retrieve aerosol extinction and convert speciated mass concentrations to total PM2.5. A recent study (Matus et al in prep.) found agreement within 2 μg/m3 over the CONUS on the 2016 annual mean when compared to EPA ground-based measurements. Another study explored trends in city aerosol optical depth (AOD) from a spaceborne passive remote sensor, Moderate Resolution Imaging Spectroradiometer (MODIS), and found that these trends agree well with trends in city surface PM2.5, which provides confidence in the use of city AOD for city PM2.5 trend studies (Vohra et al 2021). In a follow-on study, steep and significant trends (~2.5 to 7.8% a-1) in AOD are found for several South Asian cities (e.g., Bangalore and Hyderabad), suggesting rapid growth in PM2.5 (Vohra et al 2022). Also in this presentation, we report results on our current collective SAPM study of India, a country that exhibits high levels of PM2.5 pollution. We show the temporal (i.e., seasonal) and spatial variability of PM2.5 over India using the CALIOP and CATS+model approaches, comparisons between the estimated PM2.5 from the retrieval schemes, and validation with in situ PM2.5 ground-based observations from the Central Pollution Control Board in India. This region provides us with an excellent case study to test our PM2.5 retrievals in heavily polluted scenes and over a complex and varying topography. The SAPM Topic group actively seeks international participants/collaborators in our group, including those working with in situ aerosol measurements (e.g., ACTRIS). We are interested in aerosol datasets in order to either improve our PM2.5 estimates from various approaches (e.g., using in situ mass scattering/absorption coefficient and aerosol hygroscopic properties for various aerosol species) and/or validate the PM2.5 estimates (e.g., using in situ ground-based PM2.5 concentrations).

Travis D Toth↗

NASA NTRS1975

A theoretical/experimental program to develop active optical pollution sensors: Quantitative remote Raman lidar measurements of pollutants from stationary sources

Typical pollutant gas concentrations at the stack exits of stationary sources can be estimated to be about 500 ppm under the present emission standards. Raman lidar has a number of advantages which makes it a valuable tool for remote measurements of these stack emissions. Tests of the Langley Research Center Raman lidar at a calibration tank indicate that night measurements of SO2 concentrations and stack opacity are possible. Accuracies of 10 percent are shown to be achievable from a distance of 300 m within 30 min integration times for 500 ppm SO2 at the stack exits. All possible interferences were examined quantitatively (except for the fluorescence of aerosols in actual stack emissions) and found to have negligible effect on the measurements. An early test at an instrumented stack is strongly recommended.

Poultney, S. K.↗

NASA NTRS1976

Remote sensing of natural resources: Quarterly literature review

A quarterly review of technical literature concerning remote sensing techniques is presented. The format contains indexed and abstracted materials with emphasis on data gathering techniques performed or obtained remotely from space, aircraft, or ground-based stations. Remote sensor applications including the remote sensing of natural resources are presented.

Source record↗