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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Performance Assessment of the Eastern Range False Cape 915-MHz Doppler Radar Wind Profiler

The United States Space Force (USSF) is responsible for space vehicle launches at its Eastern Range (ER), which includes the Cape Canaveral Space Force Station (CCSFS). Multiple systems are used to measure the atmosphere at the ER, including suites of Doppler Radar Wind Profilers (DRWPs) operating at 915 MHz that measure winds within the lowest few kilometers of the atmosphere. Observations of boundary layer winds can be used for multiple applications, including serving as input to toxic dispersion models and characterizing winds for low-level aborts. The USSF upgraded the False Cape DRWP, which collected data during the autumn of 2020. The USSF also requested NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NE) to evaluate wind output from this DRWP system. This report describes the system and the analyses that MSFC NE conducted to demonstrate the system’s wind accuracy relative to balloons from the Automated Meteorological Profiling System (AMPS), data availability, and effective vertical resolution (EVR).

BJ Barbre↗
NASA NTRS2022

A Novel Machine Learning-Based Gap-Filling of Fine-Resolution Remotely Sensed Snow Cover Fraction Data By Combining Downscaling and Regression

Satellite-based remotely sensed observations of snow cover fraction (SCF) can have data gaps in spatially distributed coverage from sensor and orbital limitations. We mitigate these limitations in the example fine-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data by gap-filling using auxiliary 1-km datasets that either aid in downscaling from coarser-resolution (5 km) MODIS SCF wherever not fully covered by clouds, or else by themselves via regression wherever fully cloud covered. This study’s prototype predicts a 1-km version of the 500-m MOD10A1 SCF target. Due to noncollocatedness of spatial gaps even across input and auxiliary datasets, we consider a recent gap-agnostic advancement of partial convolution in computer vision for both training and predictive gap-filling. Partial convolution accommodates spatially consistent gaps across the input images, effectively implementing a two-dimensional masking. To overcome reduced usable data from noncollocated spatial gaps across inputs, we innovate a fully generalized three-dimensional masking in this partial convolution. This enables a valid output value at a pixel even if only a single valid input variable and its value exist in the neighborhood covered by the convolutional filter zone centered around that pixel. Thus, our gap-agnostic technique can use significantly more examples for training (∼67%) and prediction (∼100%), instead of only less than 10% for the previous partial convolution. We train an example simple three-layer legacy super-resolution convolutional neural network (SRCNN) to obtain downscaling and regression component performances that are better than baseline values of either climatology or MOD10C1 SCF as relevant. Our generalized partial convolution can enable multiple Earth science applications like downscaling, regression, classification, and segmentation that were hindered by data gaps.

Soni Yatheendradas↗
NASA NTRS2021

Performance Assessment of the Eastern Range Titusville-Cocoa 915-MHz Doppler Radar Wind Profiler

The United States Space Force (USSF) is responsible for space vehicle launches at its Eastern Range (ER), which includes the Cape Canaveral Space Force Station (CCSFS). Multiple systems are used to measure the atmosphere at the ER, including suites of Doppler Radar Wind Profilers (DRWPs)that operate at 915MHz and measure winds within the lowest few kilometers of the atmosphere. Observations of boundary layer winds can be used for multiple applications, including serving as input to toxic dispersion models and characterizing winds for low-level aborts. The USSF upgraded the Titusville-Cocoa(TICO)DRWP, which collected data during the spring and summer of 2020. The USSF also requested NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NE) to evaluate wind output from this DRWP system. This report describes the system and the analyses that MSFC NE conducted to demonstrate the system’s wind accuracy relative to balloons from the Automated Meteorological Profiling System (AMPS), data availability, and effective vertical resolution (EVR).

B. J. Barbre↗
NASA NTRSDate not supplied

Photonic Integrated Circuit TUned for Reconnaissance and Exploration (PICTURE)

The mid-infrared (MIR) spectral range (3-5 μm) is of particular interest for remotely sensing gaseous molecules such as H2O, CO2, CH4, N2O, CO, NH3, and other compounds. The infrared spectra of planets, moons, comets, and asteroids are rich in information, including gas composition and surface mineralogy. Significant advances in technology have emerged for ground-based telescopes, including the higher spectral resolution permitted by cross-dispersed instruments and heterodyne techniques. New technologies offer the opportunity to break this barrier, by using solid- state photonics. In the past three years, under the NASA ROSES PICASSO program, we have been developing key components for a revolutionary MIR spectrometer: Photonic Integrated Circuit TUned for Reconnaissance and Exploration (PICTURE), which is based on integrated photonics technology that offers ultra-small size, weight, and power (SWaP) with non-moving parts and low cost for future planetary missions. In this paper, we will describe our science and technology development progress leading to demonstrating the concept and functionalities of the PICTURE instrument. The photonic integrated circuit spectrometer (PICS) of the PICTURE instrument uses an integrated heterodyne detection scheme to significantly reduce SWaP and improve sensitivity. Our program goals are to advance the building blocks needed for the PICS, which include arrayed waveguide gratings (AWGs), quantum cascade lasers (QCLs) as local oscillators, and quantum cascade detectors (QCDs) as heterodyne detectors. In addition, we are leveraging a NASA SBIR program to develop the toolsets needed to fabricate MIR photonics lanterns (PL). The PL is a critical component that enables PICTURE to bring a signal from the collecting telescope to the PICS, which requires single optical mode inputs. PICTURE focuses on the CO spectral band at 4.6-4.8 μm that is of key importance to cometary science. We also continue to explore future instrument concepts that exploit the broad wavelength potential of the PICS design to perform spectroscopy spanning the full MIR and longwave IR (LWIR) bands. This will have wide applicability in planetary science, for example, to probe the strongest CO2, H2O, and CH4 transitions that are difficult (CH4) or impossible (CO2, H2O) to detect using Earth-based telescopes due to atmospheric opacity. Each integrated-photonics-spectrometer chip will feature a single heterodyne room-temperature laser with a wide wavelength tuning range, or multiple local-oscillator lasers for much broader spectral coverage. The fully developed PICTURE instrument will provide a cost-effective, high-resolution spectrometer for future space applications.

Anthony W Yu↗
NASA NTRSDate not supplied

Photonic Integrated Circuit TUned for Reconnaissance and Exploration (PICTURE)

The mid-infrared (MIR) spectral range (3-5 μm) is of particular interest for remotely sensing gaseous molecules such as H2O, CO2, CH4, N2O, CO, NH3, and other compounds. The infrared spectra of planets, moons, comets, and asteroids are rich in information, including gas composition and surface mineralogy. Significant advances in technology have emerged for ground-based telescopes, including the higher spectral resolution permitted by cross-dispersed instruments and heterodyne techniques. New technologies offer the opportunity to break this barrier, by using solid-state photonics. In the past three years, under the NASA ROSES PICASSO program, we have been developing key components for a revolutionary MIR spectrometer: Photonic Integrated Circuit TUned for Reconnaissance and Exploration (PICTURE), which is based on integrated photonics technology that offers ultra-small size, weight, and power (SWaP) with non-moving parts and low cost for future planetary missions. In this paper, we will describe our science and technology development progress leading to demonstrating the concept and functionalities of the PICTURE instrument. The photonic integrated circuit spectrometer (PICS) of the PICTURE instrument uses an integrated heterodyne detection scheme to significantly reduce SWaP and improve sensitivity. Our program goals are to advance the building blocks needed for the PICS, which include arrayed waveguide gratings (AWGs), quantum cascade lasers (QCLs) as local oscillators, and quantum cascade detectors (QCDs) as heterodyne detectors. In addition, we are leveraging a NASA SBIR program to develop the toolsets needed to fabricate MIR photonics lanterns (PL). The PL is a critical component that enables PICTURE to bring a signal from the collecting telescope to the PICS, which requires single optical mode inputs. PICTURE focuses on the CO spectral band at 4.6-4.8 μm that is of key importance to cometary science. We also continue to explore future instrument concepts that exploit the broad wavelength potential of the PICS design to perform spectroscopy spanning the full MIR and longwave IR (LWIR) bands. This will have wide applicability in planetary science, for example, to probe the strongest CO2, H2O, and CH4 transitions that are difficult (CH4) or impossible (CO2, H2O) to detect using Earth-based telescopes due to atmospheric opacity. Each integrated-photonics-spectrometer chip will feature a single heterodyne room-temperature laser with a wide wavelength tuning range, or multiple local-oscillator lasers for much broader spectral coverage. The fully developed PICTURE instrument will provide a cost-effective, high-resolution spectrometer for future space applications.

Anthony W Yu↗
NASA NTRSDate not supplied

Photonic Integrated Circuit TUned for Reconnaissance and Exploration (PICTURE)

The mid-infrared (MIR) spectral range (3-5 μm) is of particular interest for remotely sensing gaseous molecules such as H2O, CO2, CH4, N2O, CO, NH3, and other compounds. The infrared spectra of planets, moons, comets, and asteroids are rich in information, including gas composition and surface mineralogy. Significant advances in technology have emerged for ground-based telescopes, including the higher spectral resolution permitted by cross-dispersed instruments and heterodyne techniques. New technologies offer the opportunity to break this barrier, by using solid-state photonics. In the past three years, under the NASA ROSES PICASSO program, we have been developing key components for a revolutionary MIR spectrometer: Photonic Integrated Circuit TUned for Reconnaissance and Exploration (PICTURE), which is based on integrated photonics technology that offers ultra-small size, weight, and power (SWaP) with non-moving parts and low cost for future planetary missions. In this paper, we will describe our science and technology development progress leading to demonstrating the concept and functionalities of the PICTURE instrument. The photonic integrated circuit spectrometer (PICS) of the PICTURE instrument uses an integrated heterodyne detection scheme to significantly reduce SWaP and improve sensitivity. Our program goals are to advance the building blocks needed for the PICS, which include arrayed waveguide gratings (AWGs), quantum cascade lasers (QCLs) as local oscillators, and quantum cascade detectors (QCDs) as heterodyne detectors. In addition, we are leveraging a NASA SBIR program to develop the toolsets needed to fabricate MIR photonics lanterns (PL). The PL is a critical component that enables PICTURE to bring a signal from the collecting telescope to the PICS, which requires single optical mode inputs. PICTURE focuses on the CO spectral band at 4.6-4.8 μm that is of key importance to cometary science. We also continue to explore future instrument concepts that exploit the broad wavelength potential of the PICS design to perform spectroscopy spanning the full MIR and longwave IR (LWIR) bands. This will have wide applicability in planetary science, for example, to probe the strongest CO2, H2O, and CH4 transitions that are difficult (CH4) or impossible (CO2, H2O) to detect using Earth-based telescopes due to atmospheric opacity. Each integrated-photonics-spectrometer chip will feature a single heterodyne room-temperature laser with a wide wavelength tuning range, or multiple local-oscillator lasers for much broader spectral coverage. The fully developed PICTURE instrument will provide a cost-effective, high-resolution spectrometer for future space applications.

Anthony W. Yu↗
NASA NTRS2013

Estimating the Concentration of Large Raindrops from Polarimetric Radar and Disdrometer Observations

Estimation of rainfall integral parameters, including radar observables, and empirical relations between them are sensitive to the truncation of the drop size distribution (DSD), particularly at the large drop end. The sensitivity of rainfall integral parameters to the maximum drop diameter (D(sub max)) is exacerbated at C‐band since resonance effects are pronounced for large drops in excess of 5 mm diameter (D). Due to sampling limitations, it is often difficult to reliably estimate D(sub max) with disdrometers. The resulting uncertainties in D(sub max0 potentially increase errors in radar retrieval methods, particularly at C‐band, that rely on disdrometer observations for DSD input to radar models. In fact, D(sub max) is typically an assumed DSD parameter in the development of radar retrieval methods. Because of these very uncertainties, it is difficult to independently confirm disdrometer estimates of D(sub max) with polarimetric radar observations. A couple of approaches can be taken to reduce uncertainty in large drop measurement. Longer integration times can be used for the collection of larger disdrometer samples. However, integration periods must be consistent with a radar resolution volume (RRV) and the temporal and spatial scales of the physical processes affecting the DSD therein. Multiple co‐located disdrometers can be combined into a network to increase the sample size within a RRV. However, over a reasonable integration period, a single disdrometer sample volume is many orders of magnitudes less than a RRV so it is not practical to devise a network of disdrometers that has an equivalent volume to a typical RRV. Since knowledge of DSD heterogeneity and large drop occurrence in time and space is lacking, the specific accuracy or even general representativeness of disdrometer based D(sub max) and large drop concentration estimates within a RRV are currently unknown. To address this complex issue, we begin with a simpler question. Is the frequency of occurrence of large rain drops (D > 5 mm) in disdrometer observations, either stand alone or networked, generally representative and consistent with polarimetric radar observations? We first show from simulations that the concentration of large (D > 5 mm) rain drops (N(sub T5)) can be estimated from polarimetric observations of specific differential phase (K(sub dp)) and differential reflectivity (Z(sub dr)), N(sub T5)=F(K(sub dp),Z(sub dr)), or horizontal reflectivity (Z(sub h)) and Z(sub dr), N(sub T5)=(Z(sub h),Z(sub dr)). We assess the error associated with polarimetric retrieval of N(sub T5), including sensitivity to D(sub max) parameterization assumptions and measurement error in the radar simulations. Polarimetric measurements at S‐band and C‐band will then be used to retrieve estimates of N(sub T5) and compared to disdrometer estimates of N(sub T5). After careful consideration of retrieval error, we will check consistency between disdrometer and polarimetric radar estimates of N(sub T5) and the frequency of occurrence of large rain drops in a variety of precipitating regimes using data from NASA's Global Precipitation Measurement (GPM) Ground Validation (GV) program, including field campaigns such as MC3E (Oklahoma) and IFloodS (Iowa) and extended measurements over Huntsville, Alabama and NASA Wallops Flight Facility in coastal Virginia.

Carey, Lawrence D.↗
NASA NTRS2014

Probabilistic Assessment of Hypobaric Decompression Sickness Treatment Success

The Hypobaric Decompression Sickness (DCS) Treatment Model links a decrease in computed bubble volume from increased pressure (DeltaP), increased oxygen (O2) partial pressure, and passage of time during treatment to the probability of symptom resolution [P(symptom resolution)]. The decrease in offending volume is realized in 2 stages: a) during compression via Boyle's Law and b) during subsequent dissolution of the gas phase via the O2 window. We established an empirical model for the P(symptom resolution) while accounting for multiple symptoms within subjects. The data consisted of 154 cases of hypobaric DCS symptoms along with ancillary information from tests on 56 men and 18 women. Our best estimated model is P(symptom resolution) = 1 / (1+exp(-(ln(Delta P) - 1.510 + 0.795×AMB - 0.00308×Ts) / 0.478)), where (DeltaP) is pressure difference (psid), AMB = 1 if ambulation took place during part of the altitude exposure, otherwise AMB = 0; and where Ts is the elapsed time in mins from start of the altitude exposure to recognition of a DCS symptom. To apply this model in future scenarios, values of DeltaP as inputs to the model would be calculated from the Tissue Bubble Dynamics Model based on the effective treatment pressure: (DeltaP) = P2 - P1 | = P1×V1/V2 - P1, where V1 is the computed volume of a spherical bubble in a unit volume of tissue at low pressure P1 and V2 is computed volume after a change to a higher pressure P2. If 100% ground level O2 (GLO) was breathed in place of air, then V2 continues to decrease through time at P2 at a faster rate. This calculated value of (DeltaP then represents the effective treatment pressure at any point in time. Simulation of a "pain-only" symptom at 203 min into an ambulatory extravehicular activity (EVA) at 4.3 psia on Mars resulted in a P(symptom resolution) of 0.49 (0.36 to 0.62 95% confidence intervals) on immediate return to 8.2 psia in the Multi-Mission Space Exploration Vehicle. The P(symptom resolution) increased to near certainty (0.99) after 2 hrs of GLO at 8.2 psia or with less certainty on immediate pressurization to 14.7 psia [0.90 (0.83 - 0.95)]. Given the low probability of DCS during EVA and the prompt treatment of a symptom with guidance from the model, it is likely that the symptom and gas phase will resolve with minimum resources and minimal impact on astronaut health, safety, and productivity.

Conkin, Johnny↗
NASA NTRSDate not supplied

NASA Earth Systems Digital Twins (ESDT)

"Similarly to artificial intelligence, which is now revolutionizing many aspects of our daily lives, Earth system digital twin technologies have the potential to revolutionize the way Earth Science research will be conducted in the future, and how results and knowledge from this research will provide information to support decision making and yield impactful societal benefits. An Earth System Digital Twin or ESDT is a dynamic and interactive information system that first provides a digital replica of the past and current states of the Earth or Earth system as accurately and timely as possible; second, allows for computing forecasts of future states under nominal assumptions and based on the current replica; and third, offers the capability to investigate many hypothetical scenarios under varying impact assumptions. In other words, an ESDT provides the integrated What-Now, What-Next, and What-If pictures of the Earth or Earth system, by continuously ingesting newly observed data and by leveraging multiple interconnected models, machine learning as well advanced computing and visualization capabilities. Digital twins have been developed in engineering since 2002, but the interest in digital twins for the Earth domain is more recent and stems from the convergence of several developments: - The huge amount of diverse data that has now been collected continuously for more than 50 years, and that is becoming more and more difficult to access, understand, and utilize. - At the same time, because of climate change and its impacts the information produced by all of this data is becoming of interest to many new non-traditional users for analyzing and predicting various phenomena. - Because of advances in computational and visualization capabilities and the parallel unprecedented development of machine learning (ML), extracting relevant information from these large amounts of data and running complex models faster has become possible. As a result, it is becoming necessary and possible to build intuitive and interactive frameworks that will enable users with various skill levels and/or organizational hierarchy levels to easily access large amounts of targeted information along with the relevant tools and models (Earth system and human activity models), to support them in analyzing and visualizing this information, to help them understand interactions among models, to visualize the potential outcomes of various impacts, and to support decision or policy making. The full power of digital twins is that, through an integrated representation and standardized tools and software technologies, the same digital replica can address the needs of multiple users at various resolutions (spatial and temporal) and for various applications (science, economic, policy, etc.) – “from farmer to scientist”. With all these interests at stake, the challenges of building optimal digital twins are many and complex. The first challenge is to determine if a Digital Twin should be global or local, and multi-domain or thematic. For example, some domains such as Climate or Weather will require a global Digital Twin or Digital Twin capabilities while science areas such as Biodiversity might be more local. We can also envision that multiple thematic ESDTs, e.g., Air Quality, Wildfires, Hydrology could be federated or provide input to other ESDTs, either on a regional level or to a more global ESDT. Overall, we can imagine a future “web” of Digital Twins co-existing in a hierarchy or in a network, and capable of being connected or federated depending on the needs. This last point brings up the very important challenge of interoperability, including standards and protocols that will need to be built into these systems from the beginning. Each individual digital twin would have full flexibility in internal construction but would need standards-based interfaces (input and output) or hooks to make it compatible with others. Another challenge when building digital twins will be to decide how to organize each digital replica. Based on the applications targeted by the DT under implementation, various amounts and types of raw data, Analysis Ready Data (ARD) and information will need to be incorporated. Depending on the required latencies and needs of the users, various solutions can be considered, including Data Cubes, Data Lakes, pointers, or computing information on demand. We envision that each ESDT will choose a solution adapted to its specific objectives. Another important challenge is the type(s) of visualization that will be used, as well as the level of interactivity and refresh rate that will be required. Again, this will depend on the objectives of the ESDT, but also on the various users’ needs. In most cases, several types of visualizations and human interfaces will need to be offered depending on the projected users of that system. In parallel to the challenges highlighted above, there are also many tools and technologies that will need to be developed or improved for all types of digital twins. Among those are improved machine learning technologies, for example providing explainability, but also ML techniques for causality and providing a better integration of physics models. Additionally, reliable uncertainty quantification methods will be needed for all ESDT components, from validating data fusion and assimilation to assessing the accuracy of ML models and weighing the values of decisions supported by those systems. This presentation introduces the ESDT concept, presents several ESDT use cases, and a proposed ESDT architecture framework, as well as various technologies being developed by the Advanced Information Systems Technology (AIST) Program."

Earth Science Remote Sensing; Information Systems↗
NASA NTRS2013

A Parameter Estimation Scheme for Multiscale Kalman Smoother (MKS) Algorithm Used in Precipitation Data Fusion

A new approach is presented in this paper to effectively obtain parameter estimations for the Multiscale Kalman Smoother (MKS) algorithm. This new approach has demonstrated promising potentials in deriving better data products based on data of different spatial scales and precisions. Our new approach employs a multi-objective (MO) parameter estimation scheme (called MO scheme hereafter), rather than using the conventional maximum likelihood scheme (called ML scheme) to estimate the MKS parameters. Unlike the ML scheme, the MO scheme is not simply built on strict statistical assumptions related to prediction errors and observation errors, rather, it directly associates the fused data of multiple scales with multiple objective functions in searching best parameter estimations for MKS through optimization. In the MO scheme, objective functions are defined to facilitate consistency among the fused data at multiscales and the input data at their original scales in terms of spatial patterns and magnitudes. The new approach is evaluated through a Monte Carlo experiment and a series of comparison analyses using synthetic precipitation data. Our results show that the MKS fused precipitation performs better using the MO scheme than that using the ML scheme. Particularly, improvements are significant compared to that using the ML scheme for the fused precipitation associated with fine spatial resolutions. This is mainly due to having more criteria and constraints involved in the MO scheme than those included in the ML scheme. The weakness of the original ML scheme that blindly puts more weights onto the data associated with finer resolutions is overcome in our new approach.

multiscale↗
NASA NTRS1992

Task definition, decoupling and redundancy resolution by nonlinear feedback in multi-robot object handling

The problem of rigid object handling by multiple robot arms is investigated. The primary goal is to make the object exhibit a prescribed behavior while in contact with a fully known environment. Point contacts are assumed between the object and the arms. The aspect of task definition to achieve decoupling and linearizing control laws is discussed. Control laws are first formulated at the object level to provide decoupled force and position servo loops. It is then used to form control laws for the individual arms. Redundancies exist at the object and arm levels. The object level redundancy is used to achieve secondary goals in object handling. The arm level redundancies are the zero dynamics and can be controlled by redundant inputs. Full use of the available inputs are used to control the system as a whole. Numerical simulations for a dual-arm situation illustrate the validity of the approach.

Ramadorai, A. K.↗
DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗
NASA NTRS2017

GC13I-0857: Designing a Frost Forecasting Service for Small Scale Tea Farmers in East Africa

Kenya is the third largest tea exporter in the world, producing 10% of the world's black tea. Sixty percent of this production occurs largely by small scale tea holders, with an average farm size of 1.04 acres, and an annual net income of $1,075. According to a recent evaluation, a typical frost event in the tea growing region causes about $200 dollars in losses which can be catastrophic for a small holder farm. A 72-hour frost forecast would provide these small-scale tea farmers with enough notice to reduce losses by approximately 80 USD annually. With this knowledge, SERVIR, a joint NASA-USAID initiative that brings Earth observations for improved decision making in developing countries, sought to design a frost monitoring and forecasting service that would provide farmers with enough lead time to react to and protect against a forecasted frost occurrence on their farm. SERVIR Eastern and Southern Africa, through its implementing partner, the Regional Centre for Mapping of Resources for Development (RCMRD), designed a service that included multiple stakeholder engagement events whereby stakeholders from the tea industry value chain were invited to share their experiences so that the exact needs and flow of information could be identified. This unique event allowed enabled the design of a service that fit the specifications of the stakeholders. The monitoring service component uses the MODIS Land Surface Temperature product to identify frost occurrences in near-real time. The prediction component, currently under testing, uses the 2-m air temperature, relative humidity, and 10-m wind speed from a series of high-resolution Weather Research and Forecasting (WRF) numerical weather prediction model runs over eastern Kenya as inputs into a frost prediction algorithm. Accuracy and sensitivity of the algorithm is being assessed with observations collected from the farmers using a smart phone app developed specifically to report frost occurrences, and from data shared through our partner network developed at the stakeholder engagement meeting. This presentation will illustrate the efficacy of our frost forecasting algorithm, and a way forward for incorporating these forecasts in a meaningful way to the key decision makers - the small-scale farmers of East Africa.

frost↗
DOE OSTI2025

Computational Fluid Dynamics-Based Modeling of Methane Flows Around Oil and Gas Equipment

Recent studies estimate that emissions from oil and gas production facilities contribute between 20 and 50% of the total methane ( CH 4 ) emitted in the US; therefore, quantifying and reducing these emissions are crucial for achieving climate goals. Methane quantification depends on both measuring methane concentrations and converting them to emissions through a modeling framework. Currently, simple atmospheric dispersion models are primarily used to quantify emissions and concentrations, but these estimates are highly uncertain when quantifying emissions from complex aerodynamic sources, such as oil and gas facilities. This investigation used a CFD modeling approach, which can account for aerodynamic complexity but has hitherto not been used to model methane concentrations downwind of a methane release of a known rate, and compared it against in situ measurements. High-time-resolution (1 Hz) methane concentration and meteorological data were measured during experiments conducted at the METEC on 21 March and 11 July 2024. The METEC site configuration, measured wind data, and controlled emission rates were used as input for the CONVERGE CFD model to model downwind CH 4 concentration. The modeling was carried out between 20 and 70 m, from two different points of release in two separate controlled-release experiments, one from a separator and another from a wellhead. In these experiments, we found that the CFD model could predict the CH 4 concentrations downwind of the release to a good degree. The model was evaluated on multiple metrics to assess its performance in estimating methane concentrations at typical fence line distances (∼30 m). These results help us to understand external flows and the ability of CFD models to predict downwind concentrations in aerodynamically complex environments.

03 NATURAL GAS↗
NASA NTRS2013

On-Orbit Lunar Modulation Transfer Function Measurements for the Moderate Resolution Imaging Spectroradiometer

Spatial quality of an imaging sensor can be estimated by evaluating its modulation transfer function (MTF) from many different sources such as a sharp edge, a pulse target, or bar patterns with different spatial frequencies. These well-defined targets are frequently used for prelaunch laboratory tests, providing very reliable and accurate MTF measurements. A laboratory-quality edge input source was included in the spatial-mode operation of the Spectroradiometric Calibration Assembly (SRCA), which is one of the onboard calibrators of the Moderate Resolution Imaging Spectroradiometer (MODIS). Since not all imaging satellites have such an instrument, SRCA MTF estimations can be used as a reference for an on-orbit lunar MTF algorithm and results. In this paper, the prelaunch spatial quality characterization process from the Integrated Alignment Collimator and SRCA is briefly discussed. Based on prelaunch MTF calibration using the SRCA, a lunar MTF algorithm is developed and applied to the lifetime on-orbit Terra and Aqua MODIS lunar collections. In each lunar collection, multiple scan-directionMoon-to-background transition profiles are aligned by the subpixel edge locations from a parametric Fermi function fit. Corresponding accumulated edge profiles are filtered and interpolated to obtain the edge spread function (ESF). The MTF is calculated by applying a Fourier transformation on the line spread function through a simple differentiation of the ESF. The lifetime lunar MTF results are analyzed and filtered by a relationship with the Sun-Earth-MODIS angle. Finally, the filtered lunarMTF values are compared to the SRCA MTF results. This comparison provides the level of accuracy for on-orbit MTF estimations validated through prelaunch SRCA measurements. The lunar MTF values had larger uncertainty than the SRCA MTF results; however, the ratio mean of lunarMTF fit and SRCA MTF values is within 2% in the 250- and 500-m bands. Based on the MTF measurement uncertainty range, the suggested lunar MTF algorithm can be applied to any on-orbit imaging sensor with lunar calibration capability.

Choi, Taeyong↗
NASA NTRS2014

Software Suite to Support In-Flight Characterization of Remote Sensing Systems

A characterization software suite was developed to facilitate NASA's in-flight characterization of commercial remote sensing systems. Characterization of aerial and satellite systems requires knowledge of ground characteristics, or ground truth. This information is typically obtained with instruments taking measurements prior to or during a remote sensing system overpass. Acquired ground-truth data, which can consist of hundreds of measurements with different data formats, must be processed before it can be used in the characterization. Accurate in-flight characterization of remote sensing systems relies on multiple field data acquisitions that are efficiently processed, with minimal error. To address the need for timely, reproducible ground-truth data, a characterization software suite was developed to automate the data processing methods. The characterization software suite is engineering code, requiring some prior knowledge and expertise to run. The suite consists of component scripts for each of the three main in-flight characterization types: radiometric, geometric, and spatial. The component scripts for the radiometric characterization operate primarily by reading the raw data acquired by the field instruments, combining it with other applicable information, and then reducing it to a format that is appropriate for input into MODTRAN (MODerate resolution atmospheric TRANsmission), an Air Force Research Laboratory-developed radiative transport code used to predict at-sensor measurements. The geometric scripts operate by comparing identified target locations from the remote sensing image to known target locations, producing circular error statistics defined by the Federal Geographic Data Committee Standards. The spatial scripts analyze a target edge within the image, and produce estimates of Relative Edge Response and the value of the Modulation Transfer Function at the Nyquist frequency. The software suite enables rapid, efficient, automated processing of ground truth data, which has been used to provide reproducible characterizations on a number of commercial remote sensing systems. Overall, this characterization software suite improves the reliability of ground-truth data processing techniques that are required for remote sensing system in-flight characterizations.

Stanley, Thomas↗
NASA NTRS1978

A modular multiple use system for precise time and frequency measurement and distribution

A modular CAMAC based system is described which was developed to meet a variety of precise time and frequency measurement and distribution needs. The system was based on a generalization of the dual mixer concept. By using a 16 channel 100 ns event clock, the system can intercompare the phase of 16 frequency standards with subpicosecond resolution. The system has a noise floor of 26 fs and a long term stability on the order of 1 ps or better. The system also used a digitally controlled crystal oscillator in a control loop to provide an offsettable 5 MHz output with subpicosecond phase tracking capability. A detailed description of the system is given including theory of operation and performance. A method to improve the performance of the dual mixer technique is discussed when phase balancing of the two input ports cannot be accomplished.

Reinhardt, V. S.↗
NASA NTRSDate not supplied

Lidar Simulations of Backscatter and Extinction Uncertainty Estimates for ACCP Assessments

As part of the NASA Aerosols and Clouds, Convection, and Precipitation (ACCP) pre-formulation study, several lidar instruments are being assessed for their capabilities in advancing the science objectives enumerated in the most recent Earth Sciences Decadal Survey. These assessments are conducted using the NASA Langley Research Center(LaRC) lidar simulator, which produces profiles of backscatter and extinction uncertainty estimates for a given set of input parameters. Specifically, attention is focused onevaluating the science benefits and improvements of a candidate two-wavelength space-based High Spectral Resolution Lidar (HSRL) compared to an elastic backscatter lidar with similar capabilities to the Cloud-Aerosol Lidar with Orthogonal Polarization(CALIOP), flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. In this talk, simulations of satellite-based HSRL and those of a CALIOP-like system are compared for different atmospheric scenes that capture varying total aerosol loadings, aerosol vertical distributions, and aerosol types.The results of these analyses are presented as functions of averaging resolution(horizontal/vertical), lighting conditions (daytime/nighttime), surface type (land/ocean),and wavelength (532 nm/1064 nm). Also, simulations of multiple aerosol layers and of aerosols beneath transparent cirrus clouds are shown to demonstrate the consequent impacts on underlying backscatter and extinction uncertainties, and to better differentiate the performance of HSRL compared to that of CALIOP for real-world atmospheric scenarios.

Travis D. Toth↗