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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.

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All sourcesNASA NTRSDOE OSTI
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 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 NTRS2020

Remote Sensing of Arctic Atmospheric Aerosols

In this chapter remote sensing techniques as applied to studies of Arctic aerosol are surveyed. They include the analysis of ground and shipborne observations of atmospheric aerosol using sunphotometers and also airborne/satellite observations using optical instrumentation (lidars, imagers, radiometers).

Aerosol↗
NASA NTRS1982

NORSEX 1979 microwave remote sensing data report

Airborne microwave remote sensing measurements obtained by NASA Langley Research Center in support of the 1979 Norwegian Remote Sensing Experiment (NORSEX) are summarized. The objectives of NORSEX were to investigate the capabilities of an active/passive microwave system to measure ice concentration and type in the vicinity of the marginal ice zone near Svalbard, Norway and to apply microwave techniques to the investigation of a thermal oceanic front near Bear Island, Norway. The instruments used during NORSEX include the stepped frequency microwave radiometer, airborne microwave scatterometer, precision radiation thermometer and metric aerial photography. The data are inventoried, summarized, and presented in a user-friendly format. Data summaries are presented as time-history plots which indicate when and where data were obtained as well as the sensor configuration. All data are available on nine-track computer tapes in card-image format upon request to the NASA Langley Technical Library.

Hennigar, H. F.↗
NASA NTRS2016

The Plant Phenology Monitoring Design for the National Ecological Observatory Network

Phenology is an integrative science that comprises the study of recurring biological activities or events. In an era of rapidly changing climate, the relationship between the timing of those events and environmental cues such as temperature, snowmelt, water availability, or day length are of particular interest. This article provides an overview of the observer-based plant phenology sampling conducted by the U.S. National Ecological Observatory Network (NEON), the resulting data, and the rationale behind the design. Trained technicians will conduct regular in situ observations of plant phenology at all terrestrial NEON sites for the 30-yr life of the observatory. Standardized and coordinated data across the network of sites can be used to quantify the direction and magnitude of the relationships between phenology and environmental forcings, as well as the degree to which these relationships vary among sites, among species, among phenophases, and through time. Vegetation at NEON sites will also be monitored with tower-based cameras, satellite remote sensing, and annual high-resolution airborne remote sensing. Ground-based measurements can be used to calibrate and improve satellite-derived phenometrics. NEON's phenology monitoring design is complementary to existing phenology research efforts and citizen science initiatives throughout the world and will produce interoperable data. By collocating plant phenology observations with a suite of additional meteorological, biophysical, and ecological measurements (e.g., climate, carbon flux, plant productivity, population dynamics of consumers) at 47 terrestrial sites, the NEON design will enable continental-scale inference about the status, trends, causes, and ecological consequences of phenological change.

phenology↗
NASA NTRS1992

Airborne Dial Remote Sensing of the Arctic Ozone Layer

A combined ozone and aerosol LIDAR was developed at the Institute of Physics of the Atmosphere at the DLR in Oberpfaffenhofen. It is an airborne version, that, based on the DIAL-principle, permits the recording of two-dimensional ozone profiles. This presentation will focus on the ozone-part; the aerosol subsection will be treated later.

Wirth, Martin↗
NASA NTRS1991

Applying kinematic GPS to airborne laser remote sensing

Results from the application of differential carrier phase tracking of the GPS constellation of satellites to precise positioning of an aircraft are presented. These aircraft positions are utilized in the process of providing geodetic quality position information for airborne laser footprint location on the surface of the earth. The combination of these techniques provides a rapid, cost effective means for collecting geodetic and topographic data, including sea surface topography. Operational techniques and constraints, along with result from recently collected data, are presented.

Krabill, William B.↗
NASA NTRS1972

Remote sensing of wet lands in irrigated areas

The use of airborne remote sensing techniques to: (1) detect drainage problem areas, (2) delineate the problem in terms of areal extent, depth to the water table, and presence of excessive salinity, and (3) evaluate the effectiveness of existing subsurface drainage facilities, is discussed. Experimental results show that remote sensing, as demonstrated in this study and as presently constituted and priced, does not represent a practical alternative as a management tool to presently used visual and conventional photographic methods in the systematic and repetitive detection and delineation of wetlands.

Ham, H. H.↗
NASA NTRS1989

Applying kinematic GPS to airborne laser remote sensing

Results from the application of differential carrier phase tracking of the Global Positioning System (GPS) constellation of satellites to precise positioning (sub-10 cm) of an aircraft are presented. These aircraft positions are utilized in the process of providing geodetic quality position information for airborne laser 'footprint' locations on the surface of the earth. The combination of these techniques provides a rapid, cost effective means for collecting geodetic and topographic data, including sea surface topography. Operational techniques and constraints, along with results from recently collected data, are presented.

Krabill, William B.↗
NASA NTRS2016

Scientific and Technical Assistance for the Deployment of a Flexible Airborne Spectrometer System During C-MAPExp and COMEX: COMEX Version - 1.9T

The COMEX (CO2 and MEthane eXperiment) campaign supports the mission definition of CarbonSat and HyspIRI (Hyperspectral Infrared Imager) by providing representative airborne remote sensing data ‐ MAMAP (Methane Airborne MAPper) for CarbonSat; the Airborne Visual InfraRed Imaging Spectrometer (Classic & Next Generation) AVIRIS‐C/AVIRIS‐NG for HyspIRI ‐ as well as ground-based and airborne in‐situ data. The objectives of the COMEX campaign activities are (see Campaign Implementation Plan (RD‐4)): 1. Investigate spatial/spectral resolution trade‐offs for CH4 anomaly detection and flux inversion by comparison of MAMAP‐derived emission estimates with AVIRIS/AVIRIS‐NG derived data. 2. Evaluate sun‐glint observation geometry on CH4 retrievals for marine sources. 3. Characterize the effect of Surface Spectral Reflectance (SSR) heterogeneity on trace gas retrievals of CO2 and CH4 for medium and low‐resolution spectrometry. 4. Identify benefits from joint SWIR/TIR (ShortWave InfraRed/Thermal InfraRed ) data for trace gas detection and retrieval by comparison of MAMAP and AVIRIS/AVIRIS‐NG NIR/SWIR data with MAKO (Aerospace Corp.)TIR data. The ability to derive emission source strength for a range of strong emitting targets by remote sensing will be evaluated from combined AVIRIS‐NG and MAMAP data, adding significant value to the HyspIRI campaign AVIRIS‐NG dataset. The data will be used to quantify anomalies in atmospheric CO2 and CH4 from strong local greenhouse gas sources e.g. localized industrial complexes, landfills, etc. and to derive CO2 and CH4 emissions estimates from atmospheric gradient measurements. The original campaign concept was developed by University of Bremen and BRI. The COMEX campaign is funded bilaterally by NASA and ESA (European Space Agency). Whereas NASA funds the US part of the project via a contract with Dr. Ira Leifer, BRI (Bubbleology Research International), the contribution of MAMAP to the COMEX campaign is funded by ESA within the COMEX‐E project and NASA with respect to a 50 percent contribution to the flight-related costs of flying MAMAP on a US aircraft. The Data Acquisition Report (RD‐9) describes the instrumentation used, the measurements made by the team during the COMEX campaign in May/June 2014 and August/September 2014 in California, and an initial assessment of the data quality.

Point Sources↗
NASA NTRS1974

Contribution of space platforms to a ground and airborne remote-sensing programme over active Italian volcanoes

ERTS-1 imagery of the volcanic areas of southern Italy was used primarily for the evaluation of space platform capabilties in the domains of regional geology, soil and rock-type classification and, more generally, to study the environment of active volcanoes. The test sites were selected and equipped primarily to monitor thermal emission, but ground truth data was also collected in other domains (reflectance of rocks, soils and vegetation). The test areas were overflown with a two channel thermal scanner, while a thermo camera was used on the ground to monitor the hot spots. The primary goal of this survey was to plot the changes in thermal emission with time in the framework of a research program for the surveillance of active volcanoes. However, another task was an evaluation of emissivity changes by comparing the outputs of the two thermal channels. These results were compared with the reflectance changes observed on multispectral ERTS-1 imagery.

Cassinis, R.↗
NASA NTRS1981

Design and preliminary tests of an IR-airborne LLWS remote sensing system

Recent history underscores the need for in-cockpit alerts of LLWS for takeoffs and landings. The 13-15 micron portion of the CO2 molecular spectrum can be used to remote sense LLWS in and around thunderstorms. A radiometer with a designed look-distance of about 10 km remote senses an average air temperature along a forward, horizontal path. Wind shear alerts are based on the difference between this forward air temperature and the air temperature near the aircraft. Although spectral ranging, a major design improvement of an IR LLWS alert system, is not at present feasible with noncooled detectors, it is an important technique to keep in mind, given the rapid advance in IR technology.

Caracena, F.↗
NASA NTRS1982

Cloud top remote sensing by airborne lidar

Observations of cloud top height, backscattering, and signal depolarization have been obtained by a lidar system operating onboard a high-altitude research aircraft. The transmitter for the cloud lidar system is a doubled Nd:YAG laser operating at 5 Hz. The system functions as a fully automated sensor under microprocessor control and operates from a nominal 19-km altitude. Measurements have been acquired over a wide variety of cloud cover in conjunction with passive visible and infrared measurements. Initial observation results are reported

Spinhirne, J. D.↗
NASA NTRS2018

SCI 236 AGARDograph: National Aeronautics and Space Administration Armstrong Flight Research Center Annex - Part Two

NASA AFRC is a United States government entity that conducts the integration and operation of new and unproven technologies into proven flight vehicles as well as the flight test of one-of-a-kind experimental aircraft. AFRC also maintains and operates several platform aircraft that allow the integration of a wide range of sensors to conduct airborne remote sensing, science observations and airborne infrared astronomy. To support these types of operations AFRC has the organization, facilities and tools to support the experimental flight test of unique vehicles and conduct airborne sensing/observing.

AGARDgraph↗