Search NASA⌕ Search

SEARCH · Search NASA

Results for “lidar remote sensing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

The Winter 2010 and 2011 FRONT/NIRSS In-Flight Icing Hazard Detection Project

The NASA Icing Remote Sensing System (NIRSS) deploys a vertically-pointing K-band radar, a lidar ceiliometer, and a profiling microwave radiometer to obtain measurements for diagnosing local inflight icing conditions. RAL is working with NASA GRC to develop algorithms and data ingest and display software for the system. NASA has an ongoing activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. As part of that effort NASA teamed with NCAR to develop software that fuses data from multiple instruments into a single detected icing condition product. The multiple instrument approach, which is the current emphasis of this activity, utilizes a K-band vertical staring radar, a microwave radiometer that detects twelve frequencies between 22 and 59 GHz, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed in C++ program with a Java-based web display of resultant supercooled LWC profile and aircraft hazard identification. In 2010, a multi-channel scanning radiometer, designed and built by Radiometrics, Inc. under a SBIR grant,,was added to the system to assess its utility in improving icing diagnoses.

Serke, David↗
NASA NTRS2021

Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data

Domain adaptation techniques have been developed to handle data from multiple sources or domains. Most existing domain adaptation models assume that source and target domains are homogeneous, i.e., they have the same feature space. Nevertheless, many real world applications often deal with data from heterogeneous domains that come from completely different feature spaces. In our remote sensing application, data in source domain (from an active spaceborne Lidar sensor CALIOP onboard CALIPSO satellite) contain 25 attributes, while data in target domain (from a passive spectroradiometer sensor VIIRS onboard Suomi-NPP satellite) contain 20 different attributes. CALIOP has better representation capability and sensitivity to aerosol types and cloud phase, while VIIRS has wide swaths and better spatial coverage but has inherent weakness in differentiating atmospheric objects on different vertical levels. To address this mismatch of features across the domains/sensors, we propose a novel end-to-end deep domain adaptation with domain mapping and correlation alignment (DAMA) to align the heterogeneous source and target domains in active and passive satellite remote sensing data. It can learn domain invariant representation from source and target domains by transferring knowledge across these domains, and achieve additional performance improvement by incorporating weak label information into the model (DAMA-WL). Our experiments on a collocated CALIOP and VIIRS dataset show that DAMA and DAMA-WL can achieve higher classification accuracy in predicting cloud types.

domain adaptation↗
NASA NTRS2019

Early Lessons on Combining Lidar and Multi‑baseline SAR Measurements for Forest Structure Characterization

The estimation and monitoring of 3D forest structure at large scales strongly rely on the use of remote sensing techniques. Today, two of them are able to provide 3D forest structure estimates: lidar and synthetic aperture radar (SAR) configurations. The differences in wavelength, imaging geometry, and technical implementation make the measurements pro-vided by the two configurations different and, when it comes to the sensitivity to individual 3D forest structure components, complementary. Accordingly, the potential of combining lidar and SAR measurements toward an improved 3D forest structure estimation has been recognised from the very beginning. However, until today there is no established frame-work for this combination. This paper attempts to review differences, commonalities, and complementarities of lidar and SAR measurements. First, vertical lidar reflectance and SAR reflectivity profiles at different wavelengths are compared in different forest types. Then, current perspectives on their combination for the generation of enhanced structure products are discussed. Two promising frameworks for combining lidar and SAR measurements are reviewed. The first one is a model-based framework where lidar-derived parameters are used to initialize SAR scattering models, and relies on both the validity of the models and on the physical equivalence of the used lidar and SAR parameters. The second one is a structure-based framework based on the ability of lidar and SAR measurements to express physical forest structure by means of appropriate indices. These indices can then be used to establish a link between the two kind of measurements. The review is supported by experimental results achieved using space- and airborne data acquired in recent relevant mission and campaigns.

Matteo Pardini↗
NASA NTRS2013

Development of a Pulsed 2-Micron Integrated Path Differential Absorption Lidar for CO2 Measurement

Atmospheric carbon dioxide (CO2) is an important greenhouse gas that significantly contributes to the carbon cycle and global radiation budget on Earth. Active remote sensing of CO2 is important to address several limitations that contend with passive sensors. A 2-micron double-pulsed, Integrated Path Differential Absorption (IPDA) lidar instrument for ground and airborne atmospheric CO2 concentration measurements via direct detection method is being developed at NASA Langley Research Center. This active remote sensing instrument will provide an alternate approach of measuring atmospheric CO2 concentrations with significant advantages. A high energy pulsed approach provides high-precision measurement capability by having high signal-to-noise ratio level and unambiguously eliminates the contamination from aerosols and clouds that can bias the IPDA measurement. Commercial, on the shelf, components are implemented for the detection system. Instrument integration will be presented in this paper as well as a background for CO2 measurement at NASA Langley research Center

Singh, Upendra N.↗
NASA NTRS1999

New Generation Lidar Technology and Applications

Lidar has been a tool for atmospheric research for several decades. Until recently routine operational use of lidar was not known. Problems have involved a lack of appropriate technology rather than a lack of applications. Within the last few years, lidar based on a new generation of solid state lasers and detectors have changed the situation. Operational applications for cloud and aerosol research applications are now well established. In these research applications, the direct height profiling capability of lidar is typically an adjunct to other types of sensing, both passive and active. Compact eye safe lidar with the sensitivity for ground based monitoring of all significant cloud and aerosol structure and the reliability to operate full time for several years is now in routine use. The approach is known as micro pulse lidar (MPL). For MPL the laser pulse repetition rate is in the kilohertz range and the pulse energies are in the micro-Joule range. The low pulse energy permits the systems to be eye safe and reliable with solid state lasers. A number of MPL systems have been deployed since 1992 at atmospheric research sites at a variety of global locations. Accurate monitoring of cloud and aerosol vertical distribution is a critical measurement for atmospheric radiation. An airborne application of lidar cloud and aerosol profiling is retrievals of parameters from combined lidar and passive sensing involving visible, infrared and microwave frequencies. A lidar based on a large pulse, solid state diode pumped ND:YAG laser has been deployed on the NASA ER-2 high altitude research aircraft along with multi-spectral visible/IR and microwave imaging radiometers since 1993. The system has shown high reliability in an extensive series of experimental projects for cloud remote sensing. The retrieval of cirrus radiation parameters is an effective application for combined lidar and passive sensing. An approved NASA mission will soon begin long term lidar observation of atmospheric structure from space. The Geoscience Laser Altimeter System (GLAS) of the Earth Observing System is scheduled for deployment in the 2001 time frame. GLAS is both a cloud and aerosol lidar and a surface altimeter, principally for monitoring of polar ice sheets. The GLAS instrument is based on all solid state lasers operating at 40 Hz and high efficiency, solid state detectors. The design lifetime is three to five years. Data from the GLAS mission is expected to revolutionize some aspects of our understanding of the global distribution of cloud and aerosols for global climate prediction.

Spinhirne, James D.↗
NASA NTRS1995

NDSC and JPL stratospheric lidars

The Network for the Detection of Stratospheric Change is an international cooperation providing a set of high-quality, remote-sensing instruments at observing stations around the globe. A brief description of the NDSC and its goals is presented. Lidar has been selected as the NDSC instrument for measurements of stratospheric profiles of ozone, temperature, and aerosol. The Jet Propulsion Laboratory has developed and implemented two stratospheric lidar systems for NDSC. These are located at Table Mountain, California, and at Mauna Loa, Hawaii. These systems, which utilize differential absorption lidar, Rayleigh lidar, raman lidar, and backscatter lidar, to measure ozone, temperature, and aerosol profiles in the stratosphere are briefly described. Examples of results obtained for both long-term and individual profiles are presented.

McDermid, I. Stuart↗
NASA NTRS1990

Cirrus cloud characteristics derived from volume imaging lidar, high spectral resolution lidar, HIS radiometer, and satellite

Preliminary measurement results are presented from the Cirrus Remote Sensing Pilot Experiment which used a unique suite of instruments to simultaneously retrieve cirrus cloud visible and IR optical properties, while addressing the disparities between satellite volume averages and local point measurements. The experiment employed a ground-based high resolution interferometer sounder (HIS) and a second Fourier transform spectrometer to measure the spectral radiance in the 4-20 micron band, a correlated high spectral resolution lidar, a volume imaging lidar, a CLASS radiosonde system, the Scripps Whole Sky Imager, and multispectral VAS, HIRS, and AVHRR satellite data from polar orbiting and geostationary satellites. Data acquired during the month long experiment included continuous daytime monitoring with the Whole Sky Imager.

Grund, Christian J.↗
NASA NTRS1971

Raman scattering studies of pollutant systems.

Results and techniques for laboratory measurements of Raman scattering cross sections and depolarization ratios of atmospheric gases as a function of the incident photon energy are discussed. Referred to N2, the cross section of H2O changes by a factor of 2 as the incident photon energy is changed by 5%. Less striking results are obtained for SO2, NO and other atmospheric gases. Tentative results are given for spectral features of scattering from polluted air-water interfaces. Raman lidar is assessed as a potentially useful aid in remote sensing of atmospheric and water-borne pollution distributions at least in near-source concentrations.

Schwiesow, R. L.↗
NASA NTRS1991

Tunable 2.1-micron Ho lidar for simultaneous range-resolved measurements of atmospheric water vapor and aerosol backscatter profiles

An eye-safe tunable differential-absorption lidar system has been developed for the range-resolved measurement of aerosol backscatter and water vapor in the atmosphere. The lidar uses a flash-lamp-pumped, Q-switched, 10-mJ solid-state Ho:YSGG laser that is continuously tunable over a 20/cm wavelength range near 2.084 microns. Both path-averaged and range-resolved measurements were performed with the Ho differential-absorption lidar system. Preliminary measurements have been made of the temporal variation of atmospheric aerosol backscatter and water-vapor profiles at ranges out to 1 km. These results indicate that the Ho lidar has the potential for the eye-safe remote sensing of atmospheric water vapor and backscatter profiles at longer ranges if suitably enhanced in laser power and laser linewidth.

Cha, Sungdo↗
NASA NTRS2005

Compact, Engineered, 2-Micron Coherent Doppler Wind Lidar Prototype: A New NASA Instrument Incubator Program Project

A new project, selected in 2005 by NASA s Science Mission Directorate (SMD) under the Instrument Incubator Program (IIP), will be described. The 3-year effort is intended to design, fabricate, and demonstrate a packaged, rugged, compact, space-qualifiable coherent Doppler wind lidar (DWL) transceiver capable of future validation in an aircraft and/or Unmanned Aerial Vehicle (UAV). The packaged DWL will utilize the numerous advances in pulsed, solid-state, 2-micron laser technology at NASA s Langley Research Center (LaRC) in such areas as crystal composition, architecture, efficiency, cooling techniques, pulse energy, and beam quality. The extensive experience of Raytheon Space and Airborne Systems (RSAS) in coherent lidar systems, in spacebased sensors, and in packaging rugged lidar systems will be applied to this project. The packaged transceiver will be as close to an envisioned space-based DWL system as the resources and technology readiness allow. We will attempt to facilitate a future upgrade to a coherent lidar system capable of simultaneous wind and CO2 concentration profile measurements. Since aerosol and dust concentration is also available from the lidar signal, the potential for a triple measurement lidar system is attractive for both Earth and Mars remote sensing. A key follow on step after the IIP will be to add a telescope, scanner, and software for aircraft validation. This IIP should also put us in a position to begin a parallel formulation study in the 2006-2007 timeframe for a space-based DWL demonstration mission early next decade.

Kavaya, Michael J.↗
NASA NTRS2006

Comparison of Balloonsonde and Remote Sensing Atmospheric Measurements

As part of its aircraft icing research program, the NASA Glenn Research Center is conducting a program to develop technologies for the remote sensing of atmospheric conditions. A suite of instruments, currently ground-based, are used to identify a region of supercooled liquid water which is labeled as hazardous if its liquid water content is sufficiently high. During the recently completed Alliance Icing Research Study (AIRS II), these instruments were deployed in conjunction with those of other U.S. and Canadian researchers at the Mirabel Airport near Montreal. As part of the study, balloonsondes were employed to provide in-situ measurement of the atmospheric conditions that were being concurrently remotely sensed. Balloonsonde launches occurred daily at 1200 GMT to provide AIRS forecasters with local data and additionally when research aircraft were present in the airspace. In this paper, we compare the processed data from the NASA remote sensing instruments, which included an X-band radar, lidar and two radiometers, to the data gathered from the 70 soundings conducted while the NASA instruments were active. Among the parameters compared are cloud upper and lower boundaries, temperature and humidity profiles and freezing levels.

Brinker, David J.↗
NASA NTRS2012

G-LiHT: Goddard's LiDAR, Hyperspectral and Thermal Airborne Imager

Scientists at NASA's Goddard Space Flight Center have developed an ultra-portable, low-cost, multi-sensor remote sensing system for studying the form and function of terrestrial ecosystems. G-LiHT integrates two LIDARs, a 905 nanometer single beam profiler and 1550 nm scanner, with a narrowband (1.5 nanometers) VNIR imaging spectrometer and a broadband (8-14 micrometers) thermal imager. The small footprint (approximately 12 centimeters) LIDAR data and approximately 1 meter ground resolution imagery are advantageous for high resolution applications such as the delineation of canopy crowns, characterization of canopy gaps, and the identification of sparse, low-stature vegetation, which is difficult to detect from space-based instruments and large-footprint LiDAR. The hyperspectral and thermal imagery can be used to characterize species composition, variations in biophysical variables (e.g., photosynthetic pigments), surface temperature, and responses to environmental stressors (e.g., heat, moisture loss). Additionally, the combination of LIDAR optical, and thermal data from G-LiHT is being used to assess forest health by sensing differences in foliage density, photosynthetic pigments, and transpiration. Low operating costs (approximately $1 ha) have allowed us to evaluate seasonal differences in LiDAR, passive optical and thermal data, which provides insight into year-round observations from space. Canopy characteristics and tree allometry (e.g., crown height:width, canopy:ground reflectance) derived from G-LiHT data are being used to generate realistic scenes for radiative transfer models, which in turn are being used to improve instrument design and ensure continuity between LiDAR instruments. G-LiHT has been installed and tested in aircraft with fuselage viewports and in a custom wing-mounted pod that allows G-LiHT to be flown on any Cessna 206, a common aircraft in use throughout the world. G-LiHT is currently being used for forest biomass and growth estimation in the CONUS and Mexico in support of NASA's Carbon Monitoring System (CMS) and AMIGA-Carb (AMerican Icesat Glas Assessment of Carbon). For NASA's CMS, wall-to-wall G-LiHT data have been acquired over intensive study sites with historic LiDAR datasets, dense inventory data, stem maps and flux tower observations. For AMIGA-Carb, G-LiHT transects have been acquired over ICESat tracks and USDA-FS inventory plots throughout the CONUS, and similar data will be acquired in Mexico during 2013. This talk will highlight recent science results from continental-scale transects landscape-scale deployments of G-LiHT, as well as seasonal forest dynamics from repeat pass G-LiHT acquisitions.

Cook, Bruce↗
NASA NTRS2004

Surface-Satellite Measurements for Atmospheric Radiative Transfer (SMART)and Chemical, Optical and Microphysical Measurements of In-Situ Troposphere (COMMIT) Research Activities

The GSFC SMART consists of a suite of remote sensing instruments, including many commercially available radiometers, spectrometer, interferometer, and three in-house developed inskuments: micro-pulse lidar (MPL), scanning microwave radiometer (SMiR), and sun-sky-surface photometer (S(sup 3)). SMART cover the spectral range from UV to microwave, and passive to active remote sensing. This is to enrich the EOS-like research activities (i.e., EOS validation, innovative investigations, and long-term local environmental observations). During past years, SMART has been deployed in many NASA supported field campaigns to collocate with satellite nadir overpass for intercomparisons, and for initializing model simulations. Built on the successful experience of SMART, we are currently developing a new ground-based in-situ sampling package, COMMIT, including measurements of trace gases (CO, SO2, NOx, and O3,) concentrations, fine/coarse particle sizers and chemical composition, single- and three-wavelength nephelometers, and surface meteorological probes. COMMIT is built for seeking a relationship between surface in-situ measurements and boundary layer characteristics. This is to enrich EOS-like research on removing boundary layer signal from the entire column from space observation - to deduce the stable (less variability) free-troposphere observations. The COMMIT will try its best to link the chemical, microphysical, and optical properties of the boundary layer with radiation. The next major activities for SMART-COMMIT are scheduled for 2004-2006 in BASE-ASIA and EAST-AIRE. The expected close collaboration of BASE-ASIA with various research projects in Asia (i.e., ABC in South Asia, led by Ramanathan et al.; EAST-AIRE in East Asia, led by Li et al.; and APEX in Northeast Asia, led by Nakajima et al.) will definitely provide a better understanding of the impact of the biomass burning and air pollutants on regional-to-global climate, hydrological and carbon cycles, and tropospheric chemistry in Asia.

Tsay, Si-Chee↗
NASA NTRSDate not supplied

I’ve Looked at Clouds from Both Sides, Now: Viewpoints from Surface and Spaceborne Lidar Systems

Clouds play a critical role in the Earth’s climate system because they are inextricably linked to the hydrological cycle and radiation budget. Information about cloud height, thickness, occurrence, and amount are critical inputs for a host of numerical applications involving climate research. Therefore, it is important to have highly accurate and quantitative data records of cloud properties that span several years and geographic regions. Verification of even the most basic modeling processes demands long term and continuous observations of global cloud occurrence, if there is to be any confidence in their fidelity. For a number of reasons, however, it is impossible to gauge the complexities of clouds from a single source. Fundamentally, an array of remote sensing methods is needed in order to provide a complete picture. Within the Micropulse Lidar Network (MPLNET), we have developed a new algorithm to improve the quality of our cloud products. The largest impact of the changes to the cloud detection algorithm is evident with high clouds (those with cloud base > 5 km). Furthermore, polarized measurements enable us to determine the cloud thermodynamic phase. Naturally, the next step is to investigate how these improvements compare with observations from spaceborne lidars (e.g. CALIOP) which have a better (unobstructed) view of high clouds. Recent advances in remote sensing have revealed that cirrus clouds are the most common cloud genus observed in the atmosphere. Furthermore, cirrus skew highly towards relatively low cloud optical depths, as observed from both surface and spaceborne viewpoints. The radiative impacts of these findings are quite significant, considering the cumulative effect cirrus exhibit when compared to low clouds.

Jasper R Lewis↗
NASA NTRS2014

Amazon Forests Maintain Consistent Canopy Structure and Greenness During the Dry Season

The seasonality of sunlight and rainfall regulates net primary production in tropical forests. Previous studies have suggested that light is more limiting than water for tropical forest productivity, consistent with greening of Amazon forests during the dry season in satellite data.We evaluated four potential mechanisms for the seasonal green-up phenomenon, including increases in leaf area or leaf reflectance, using a sophisticated radiative transfer model and independent satellite observations from lidar and optical sensors. Here we show that the apparent green up of Amazon forests in optical remote sensing data resulted from seasonal changes in near-infrared reflectance, an artefact of variations in sun-sensor geometry. Correcting this bidirectional reflectance effect eliminated seasonal changes in surface reflectance, consistent with independent lidar observations and model simulations with unchanging canopy properties. The stability of Amazon forest structure and reflectance over seasonal timescales challenges the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions. Correcting optical remote sensing data for artefacts of sun-sensor geometry is essential to isolate the response of global vegetation to seasonal and interannual climate variability.

dry season↗
NASA NTRS2019

Overview of the New Version 3 NASA Micro-Pulse Lidar Network (MPLNET) Automatic Precipitation Detection Algorithm

Precipitation modifies atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially for low-intensity precipitation) within global scale models is crucial. In addition to improving our modeling of the hydrological cycle, this will reduce the associated uncertainty of global climate models in correctly forecasting future scenarios, and will enable the application of mitigation strategies. In this manuscript we present a proof of concept algorithm to automatically detect precipitation from lidar measurements obtained from the National Aeronautics and Space Administration Micropulse lidar network (MPLNET). The algorithm, once tested and validated against other remote sensing instruments, will be operationally implemented into the network to deliver a near real time (latency <1.5 h) rain masking variable that will be publicly available on MPLNET website as part of the new Version 3 data products. The methodology, based on an image processing technique, detects only light precipitation events (defined by intensity and duration) such as light rain, drizzle, and virga. During heavy rain events, the lidar signal is completely extinguished after a few meters in the precipitation or it is unusable because of water accumulated on the receiver optics. Results from the algorithm, in addition to filling a gap in light rain, drizzle, and virga detection by radars, are of particular interest for the scientific community as they help to fully characterize the aerosol cycle, from emission to deposition, as precipitation is a crucial meteorological phenomenon accelerating atmospheric aerosol removal through the scavenging effect. Algorithm results will also help the understanding of long term aerosol–cloud interactions, exploiting the multi-year database from several MPLNET permanent observational sites across the globe. The algorithm is also applicable to other lidar and/or ceilometer network infrastructures in the framework of the Global Aerosol Watch (GAW) aerosol lidar observation network (GALION).

Simone Lolli↗