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At least 883 records · Page 49

An Unobstructive Sensing Method for Indoor Air Quality Optimization and Metabolic Assessment within Vehicles

This work investigates the use of an intelligent and unobstructive sensing technique for maintaining vehicle cabin’s indoor air quality while simultaneously assessing the driver metabolic rate. CO 2 accumulation patterns are of great interest because CO 2 can have negative cognitive effects at higher concentrations and also since CO 2 accumulation rate can potentially be used to determine a person’s metabolic rate. The management of the vehicle’s ventilation system was controlled by periodically alternating the air recirculation mode within the cabin, which was actuated based on the CO 2 levels inside the vehicle’s cabin. The CO 2 accumulation periods were used to assess the driver’s metabolic rate, using a model that considered the vehicle’s air exchange rate. In the process of the method optimization, it was found that the vehicle’s air exchange rate (λ [h –1 ]) depends on the vehicle speeds, following the relationship: λ = 0.060 × (speed) – 0.88 when driving faster than 17 MPH. An accuracy level of 95% was found between the new method to assess the driver’s metabolic rate (1620 ± 140 kcal/day) and the reference method of indirect calorimetry (1550 ± 150 kcal/day) for a total of N = 16 metabolic assessments at various vehicle speeds. The new sensing method represents a novel approach for unobstructive assessment of driver metabolic rate while maintaining indoor air quality within the vehicle cabin.

passive sensing↗

Distributed Acoustic Sensing Based on Coherent Microwave Photonics Interferometry

A microwave photonics method has been developed for measuring distributed acoustic signals. This method uses microwave-modulated low coherence light as a probe to interrogate distributed in-fiber interferometers, which are used to measure acoustic-induced strain. By sweeping the microwave frequency at a constant rate, the acoustic signals are encoded into the complex microwave spectrum. The microwave spectrum is transformed into the joint time–frequency domain and further processed to obtain the distributed acoustic signals. The method is first evaluated using an intrinsic Fabry Perot interferometer (IFPI). Acoustic signals of frequency up to 15.6 kHz were detected. The method was further demonstrated using an array of in-fiber weak reflectors and an external Michelson interferometer. Two piezoceramic cylinders (PCCs) driven at frequencies of 1700 Hz and 3430 Hz were used as acoustic sources. The experiment results show that the sensing system can locate multiple acoustic sources. The system resolves 20 nε when the spatial resolution is 5 cm. The recovered acoustic signals match the excitation signals in frequency, amplitude, and phase, indicating an excellent potential for distributed acoustic sensing (DAS).

47 OTHER INSTRUMENTATION↗

Data for: A hybrid biophysical-machine learning framework for diurnal surface energy flux estimation using proximal sensing

Thermal-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal datasets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for specific surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of an ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81-0.94) and H (R2 = 0.46-0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical – machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

Agricultural Sciences↗

Remote Sensing Applied to Geology (Latest Citations from the Aerospace Database)

The bibliography contains citations concerning the use of remote sensing in geological resource exploration. Technologies discussed include thermal, optical, photographic, and electronic imaging using ground-based, aerial, and satellite-borne devices. Analog and digital techniques to locate, classify, and assess geophysical features, structures, and resources are also covered. Application of remote sensing to petroleum and minerals exploration is treated in a separate bibliography. (Contains 50-250 citations and includes a subject term index and title list.)

BIBLIOGRAPHIES↗

Spaceborne Radar Remote Sensing: Radar Interferometry, Scatterometry and Altimetry

Spaceborne remote sensing instruments allow the acquisition of global and synoptic information for Earth Science investigations. In particular, active microwave remote sensing that have contributed geophysical measurements of a scale and accuracy which surpass what could be accomplished with ariborne or in-situ observations.

Spaceborne Radar Remote Sensing Interferometry↗

Sensitivity of Multi-Angle Remote Sensing Observations to Aerosol Sphericity

Multi-angle, multi-spectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) Multi-angle Imaging SpectroRadiometer (MISR), can distinguish spherical from non-spherical particles over calm ocean for mineral-dust-like particles with the range of sizes and column amounts expected under natural conditions. The ability to make such distinctions is critical if remote sensing of atmospheric aerosol properties is to provide significant new contributions to our understanding of the global-scale, clear-sky solar radiation balance.

MISR aerosol aerosol properties↗

(abstract) Mount Rainier: New Remote Sensing Observations of a Decade Volcano

Mount Rainier was selected as a Decade Volcano by the International Association of Volcanology and Chemistry of the Earth's Interior. The purpose of this selection is to focus scientific and public attention on Mount Rainier during the current decade, the United Nations-designated International Decade of Natural Hazard Reduction. The Mount Rainier science plan calls for remote sensing surveys to monitor the volcano. To date, we have conducted airborne surveys with visible and near-infrared, thermal infrared, and interferometric radar instruments. Our preliminary analysis of some night-time time-series thermal infrared survey data sets of the summit suggests that, aside from seasonal variations in snow cover, there have been no qualitative changes in the size or pattern of the summit hot spots. Day-time airborne surveys were done to record the current surface appearance of the volcano and map hydrothermal alteration in the summit region. An interferometric radar survey yielded a high-resolution digital elevation model (DEM) which serves as a base for the registration of the other remote sensing data sets. More importantly, the DEM documents the current topography of glaciers and valleys. Planned biannual radar survey of mount rainier will produce a data set from which seasonal changes in glacier and valley topography can be characterized. Such characterization is essential if we are to recognize geothermally induced changes in snow and ice cover.

infrared radar interferometry glaciers seasonal va↗

Polarimetric Passive Remote Sensing of Wind-generated Sea Surfaces and Ocean Wind Vectors

This paper investigates the theory of polarimetric passive remote sensing of wind-generated sea surfaces. A two-scale polarimetric scattering and emission model of sea surfaces is developed to interpret existing active and passive remote sensing microwave signatures of sea surfaces, and to investigate the potential application of polarimetic radiometry to ocean surface winds.

Polarimetric Remote Sensing↗

(abstract) Deep Space Network Radiometric Remote Sensing Program

Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid,and precipitation , emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band becausecommunication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of watervapor-induced prop agation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity waveexperiments, and r adio science missions. During 1993, WVRs provided data for propagation mode development, supp orted planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily, monthly, and seasonal variations. Only long-term monitoring will prevent biases from being introduced by an exceptionally wet or dry year. Support for planetary missions included tropospheric calibration for the recent Mars Observer gravity wave experiments and Ka-band link experiment (KaBLE). Additionally, several proposed radio science experiments such as profiling planetary atmospheres using satellite occultations and Ka-band gravitational wave searches require advanced radiometer technology development. Finally, there has been a consistent advanced technology program to advance satellite navigational and tracking capabilities. This year that included an experiment with radiometer based tropospheric calibration for a series of VLBI catalog measurements.

microwave propagation Ka-band weather variations r↗

Deep Space Network Radiometric Remote Sensing Program

Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid, and precipitation, emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band because communication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of water vapor-induced propagation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity wave experiments, and radio science missions. During 1993, WVRs provided data for propagation model development, supported planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily, monthly, and seasonal variations. Only long-term monitoring will prevent biases from being introduced by an exceptionally wet or dry year. Support for planetary missions included tropospheric calibration for the recent Mars Observer gravity wave experiments and Ka-band link experiment (KaBLE). Additionally, several proposed radio science experiments such as profiling planetary atmospheres using satellite occultations and Ka-band gravitational wave searches require advanced radiometer technology development. Finally, there has been a consistent advanced technology program to advance satellite navigational and tracking capabilities. This year that included an experiment with radiometer based tropospheric calibration for a series of VLBI catalog measurements.

tropospheric calibration atmospheric water radio s↗

Semiconductor Reference Oscillator Development for Coherent Detection Optical Remote Sensing Applications

The NASA Earth Science Enterprise Advanced Technology Initiatives Program is supporting a program for the development of semiconductor laser reference oscillators for application to coherent optical remote sensing from Earth orbit. Local oscillators provide the frequency reference required for active spaceborne optical remote sensing concepts that involve heterodyne (coherent) detection. Two recent examples of such schemes are Doppler wind lidar and tropospheric carbon dioxide measurement by laser absorption spectrometry, both of which are being proposed at a wavelength of 2.05 microns. Frequency-agile local oscillator technology is important to such applications because of the need to compensate for large platform-induced Doppler components that would otherwise interfere with data interpretation. Development of frequency-agile local oscillator approaches has heretofore utilized the same laser material as the transmitter laser (Tm,Ho:YLF in the case of the 2.05-micron wavelength mentioned above). However, a semiconductor laser-based frequency-agile local oscillator offers considerable scope for reduced mechanical complexity and improved frequency agility over equivalent crystal laser devices, while their potentially faster tuning capability suggest the potential for greater scanning versatility. The program we report on here is specifically tasked with the development of prototype novel architecture semiconductor lasers with the power, tunability, and spectral characteristics required for coherent Doppler lidar. The baseline approach for this work is the distributed feedback (DFB) laser, in which gratings are etched into the semiconductor waveguide structures along the entire length of the laser cavity. However, typical DFB lasers at the wavelength of interest have linewidths that exhibit unacceptable growth when driven at the high currents and powers that are required for the Doppler lidar application. Suppression of this behavior by means of corrugation pitch-modulation (using a detuned central section to prevent intensity peaking in the center of the cavity) is currently under investigation to achieve the required performance goals.

distributed feedback (DFB) laser↗

The Challenge of Active Optical Sensing from Extreme Orbits

A review of the history and current state of atmospheric sensing lidar from Earth orbit was conducted and it was found that space based earth remote sensing is still in its infancy with only one limited success extended duration autonomous mission to date. An analysis of the basic requirements for some candidate geo-synchronous lidar concepts was completed and it was concluded that significant basic work is required in all areas of lidar development.

lidars↗

Increasing Access and Usability of Remote Sensing Data: The NASA Protected Area Archive

Although remote sensing data are now widely available, much of it at low or no-cost, many managers of protected conservation areas do not have the expertise or tools to view or analyze it. Thus access to it by the protected area management community is effectively blocked. The Protected Area Archive will increase access to remote sensing data by creating collections of satellite images of protected areas and packaging them with simple-to-use visualization and analytical tools. The user can easily locate the area and image of interest on a map, then display, roam, and zoom the image. A set of simple tools will be provided so the user can explore the data and employ it to assist in management and monitoring of their area. The 'Phase 1 ' version requires only a Windows-based computer and basic computer skills, and may be of particular help to protected area managers in developing countries.

remote sensing↗

Experimental Verification of Dispersed Fringe Sensing as a Segment Phasing Technique using the Keck Telescope

Dispersed fringe sensing (DFS) is an efficient and robust method for coarse phasing of segmented primary mirrors (from one quarter of a wavelength to as much as the depth of focus of a single segment, typically several tens of microns). Unlike phasing techniques currently used for ground-based segmented telescopes, DFS does not require the use of edge sensors in order to sense changes in the relative heights of adjacent segments; this makes it particularly well suited for phasing of space-borne segmented telescopes, such as the James Webb Space Telescope. We validate DFS by using it to measure the piston errors of the segments of one of the Keck telescopes. The results agree with those of the Shack-Hartmann-based phasing scheme currently in use at Keck to within 2% over a range of initial piston errors of +/-16 (mu)m.

algorithm↗

Data Fusion for Earth Science Remote Sensing

Beginning in 2004, NASA has supported the development of an international network of ground-based remote sensing installations for the measurement of greenhouse gas columns. This collaboration has been successful and is currently used in both carbon cycle investigations and in the efforts to validate the GOSAT space-based column observations of CO2 and CH4. With the support of a grant, this research group has established a network of ground-based column observations that provide an essential link between the satellite observations of CO2, CO, and CH4 and the extensive global in situ surface network. The Total Carbon Column Observing Network (TCCON) was established in 2004. At the time of this report seven sites, employing modern instrumentation, were operational or were expected to be shortly. TCCON is expected to expand. In addition to providing the most direct means of tying the in situ and remote sensing data sets together, TCCON provides a means of testing the retrieval algorithms of SCIAMACHY and GOSAT over the broadest variation in atmospheric state. TCCON provides a critically maintained and long timescale record for identification of temporal drift and spatial bias in the calibration of the space-based sensors. Finally, the global observations from TCCON are improving our understanding of how to use column observations to provide robust estimates of surface exchange of C02 and CH4 in advance of the launch of OCO and GOSAT. TCCON data are being used to better understand the impact of both regional fluxes and long-range transport on gradients in the C02 column. Such knowledge is essential for identifying the tools required to best use the space-based observations. The technical approach and methodology of retrieving greenhouse gas columns from near-IR solar spectra, data quality and process control are described. Additionally, the impact of and relevance to NASA of TCCON and satellite validation and carbon science are addressed.

data fusion↗

Radar Remote Sensing

This lecture was just a taste of radar remote sensing techniques and applications. Other important areas include Stereo radar grammetry. PolInSAR for volumetric structure mapping. Agricultural monitoring, soil moisture, ice-mapping, etc. The broad range of sensor types, frequencies of observation and availability of sensors have enabled radar sensors to make significant contributions in a wide area of earth and planetary remote sensing sciences. The range of applications, both qualitative and quantitative, continue to expand with each new generation of sensors.

remote sensing↗