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193 records · Page 11

High-Resolution Mid-Infrared Molecular Line Survey of the Orion Hot Core

The basic building blocks of life are synthesized in space as part of the natural stellar evolutionary cycle, whereby elements ejected into the interstellar medium by dying stars are incorporated back into the dense clouds, which form the next generation of stars and planets. The formation of stars and planets are fundamental to the evolution of matter in the Universe as complex molecules are created and destroyed during this step. Understanding these processes will allow us to answer “What is the relation between the molecules we see in the ISM and the molecular inventory of Earth and the terrestrial planets in the Solar System?” Measuring and cataloging the inventory of organic molecules and understanding their evolution requires observations over a broad wavelength range (IR, MIR, FIR, (sub)mm, and radio) to cover all stages of this evolutionary cycle needed to link interstellar material to that delivered to planets. High-resolution molecular line surveys provide chemical inventories for star forming regions and are essential for studying their chemistry, kinematics and physical conditions. Previous high spectral resolution surveys have been limited to radio, sub-mm and FIR wavelengths; however, Mid-infrared observations are the only way to study symmetric molecules that have no dipole moment and thus cannot be detected in the (sub)mm line surveys from ALMA. Past midinfrared missions such as ISO and Spitzer had low to moderate resolving power that were only able to link broad features with particular molecular bands and could not resolve the individual rovibrational transitions. JWST will provide exceptional sensitivity in the MIR, but will also not have sufficient spectral resolution, which can lead to confusion in identifying the contribution from strong to moderate strength molecular species. We present new results from an on-going high resolution (R ~ 60,000) line survey of the Orion hot core between 12.5 - 28.3 μm and 7 - 8 μm, using the EXES instrument on the SOFIA airborne observatory. SOFIA's higher-resolution and smaller beam compared to ISO allows us to spatially and spectrally isolate the emission towards the hot core. This survey will provide the best infrared measurements (to date) of molecular column densities and physical conditions, providing strong constraints on the current chemical network models for star forming regions. This survey will greatly enhance the inventory of resolved line features in the MIR, making it an invaluable reference to be used by the JWST and ALMA scientific communities.

Rangwala, Naseem↗

Refractory Ceramic Foams for Novel Applications

Workers at NASA Ames Research center are endeavoring to develop durable, oxidation-resistant, foam thermal protection systems (TPSs) that would be suitable for covering large exterior spacecraft surfaces, would have low to moderate densities, and would have temperature capabilities comparable to those of carbon-based TPSs [reusable at 3,000 F (.1,650 C)] with application of suitable coatings. These foams may also be useful for repairing TPSs while in orbit. Moreover, on Earth as well as in outer space, these foams might be useful as catalyst supports and filters. Preceramic polymers are obvious candidates for use in making the foams in question. The use of these polymers offers advantages over processing routes followed in making conventional ceramics. Among the advantages are the ability to plastically form parts, the ability to form pyrolized ceramic materials at lower temperatures, and the ability to form high-purity microstructures having properties that can be tailored to satisfy requirements. Heretofore, preceramic polymers have been used mostly in the production of such low-dimensional products as fibers because the loss of volatiles during pyrolysis of the polymers leads to porosity and large shrinkage (in excess of 30 percent). In addition, efforts to form bulk structures from preceramic polymers have resulted in severe cracking during pyrolysis. However, because the foams in question would consist of networks of thin struts (in contradistinction to nonporous dense solids), these foams are ideal candidates for processing along a preceramic-polymer route.

Stackpoole, M.↗

Satellite Remote Sensing of Snow/Ice Albedo over the Himalayas

The Himalayan glaciers and snowpacks play an important role in the hydrological cycle over Asia. The seasonal snow melt from the Himalayan glaciers and snowpacks is one of the key elements to the livelihood of the downstream densely populated regions of South Asia. During the pre-monsoon season (April-May-June), South Asia not only experiences the reversal of the regional meridional tropospheric temperature gradient (i.e., the onset of the summer monsoon), but also is being bombarded by dry westerly airmass that transports mineral dust from various Southwest Asian desert and arid regions into the Indo-Gangetic Plains in northern India. Mixed with heavy anthropogenic pollution, mineral dust constitutes the bulk of regional aerosol loading and forms an extensive and vertically extended brown haze lapping against the southern slopes of the Himalayas. Episodic dust plumes are advected over the Himalayas, and are discernible in satellite imagery, resulting in dust-capped snow surface. Motivated by the potential implications of accelerated snowmelt, we examine the changes in radiative energetics induced by aerosol transport over the Himalayan snow cover by utilizing space borne observations. Our objective lies in the investigation of potential impacts of aerosol solar absorption on the Top-of-Atmosphere (TOA) spectral reflectivity and the broadband albedo, and hence the accelerated snowmelt, particularly in the western Himalayas. Lambertian Equivalent Reflectivity (LER) in the visible and near-infrared wavelengths, derived from Moderate Resolution Imaging Spectroradiometer radiances, is used to generate statistics for determining perturbation caused due to dust layer over snow surface in over ten years of continuous observations. Case studies indicate significant reduction of LER ranging from 5 to 8% in the 412-860nm spectra. Broadband flux observations, from the Clouds and the Earth's Radiant Energy System, are also used to investigate changes in shortwave TOA flux over dust-laden and dust-free snow covered regions. Additionally, spatio-temporal and intra-seasonal variations of LER, along with snow cover information, are used to characterize the seasonal melt pattern and thus to distinguish the outstanding aerosol-induced snowmelt signal. Results from this observational work are expected to provide better understanding of the radiative impact of aerosols over snow surface, especially its role in the Himalayan hydro-glacialogical variability.

Hsu, N. Christina↗

A Robust Hybrid Deep Learning Model for Spatiotemporal Image Fusion

Dense time-series remote sensing data with detailed spatial information are highly desired for the monitoring of dynamic earth systems. Due to the sensor tradeoff, most remote sensing systems cannot provide images with both high spatial and temporal resolutions. Spatiotemporal image fusion models provide a feasible solution to generate such a type of satellite imagery, yet existing fusion methods are limited in predicting rapid and/or transient phenological changes. Additionally, a systematic approach to assessing and understanding how varying levels of temporal phenological changes affect fusion results is lacking in spatiotemporal fusion research. The objective of this study is to develop an innovative hybrid deep learning model that can effectively and robustly fuse the satellite imagery of various spatial and temporal resolutions. The proposed model integrates two types of network models: super-resolution convolutional neural network (SRCNN) and long short-term memory (LSTM). SRCNN can enhance the coarse images by restoring degraded spatial details, while LSTM can learn and extract the temporal changing patterns from the time-series images. To systematically assess the effects of varying levels of phenological changes, we identify image phenological transition dates and design three temporal phenological change scenarios representing rapid, moderate, and minimal phenological changes. The hybrid deep learning model, alongside three benchmark fusion models, is assessed in different scenarios of phenological changes. Results indicate the hybrid deep learning model yields significantly better results when rapid or moderate phenological changes are present. It holds great potential in generating high-quality time-series datasets of both high spatial and temporal resolutions, which can further benefit terrestrial system dynamic studies. The innovative approach to understanding phenological changes’ effect will help us better comprehend the strengths and weaknesses of current and future fusion models.

spatiotemporal fusion↗

Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.

Riggs, George A.↗

Methods to Reduce Communication Workload for UAM Operations

Implementation of Urban Air Mobility (UAM) operations, or air passenger transportation systems within densely populated metropolitan areas, seeks to mitigate increasing traffic congestion. However, the development and integration of UAM operations into the national airspace system comes with its own unique challenges, such as vehicle requirements, flight planning and scheduling, and coordination between UAM flights and air traffic controllers. In particular, verbal coordination will play an integral part in the determined success of UAM operations and its ability to meet projected high consumer demands. In order to meet demands and higher traffic volumes on UAM routes, verbal communication between the UAM pilot and controller must be streamlined to reduce the controller's workload while helping to maintain safety within a given airspace. One method of reducing verbal workload are Letters Of Agreement (LOAs) that outline responsibilities and procedures for operations in an airspace. These LOAs will specify the operations, procedures, and routes for UAM flights. The proposed study will examine the usability of two route formatting styles for LOAs; (i) Verbal route descriptions and (ii) Tower En Route Control (TECs) routes. Verbal route descriptions will include the route name and associated visual cues on the route. The TEC route versions will include relevant waypoints and charts outlining the route with waypoints marked. The study will be part of a UAM X1 human in the loop (HITL) simulation. Controller participants will handle traditional air traffic including moderate levels of UAM traffic on current and modified helicopter routes within the Dallas Fort-Worth area. Scenarios will be counterbalanced and repeated to test both route formatting versions. After each trial, participants will rate the usability of the LOA used in the previous trial via a subjective questionnaire. We expect that controllers will prefer the LOA with TEC routes due to simplicity and visual elements available.

aerospace human factors↗

Estimating Surface Soil Moisture from SMAP Observations Using a Neural Network Technique

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m(exp. 3)m(exp. -3), 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m(exp. 3)m(exp. -3), 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Soil Moisture Remote Sensing↗

Assimilation of AERONET and MODIS AOT Observations Using Variational and Ensemble Data Assimilation Methods and Its Impact on Aerosol Forecasting Skill

Data assimilation of Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness (AOT) for aerosol forecasting was tested within the Navy Aerosol Analysis Prediction System (NAAPS) framework, using variational and ensemble data assimilation methods. Navy aerosol forecasting currently makes use of a deterministic NAAPS simulation coupled to Navy Variational Data Assimilation System for aerosol optical depth, a two-dimensional variational data assimilation system, for MODIS AOT assimilation. An ensemble version of NAAPS (ENAAPS) coupled to an ensemble adjustment Kalman filter (EAKF) from the Data Assimilation Research Testbed was recently developed, allowing for a range of data assimilation and forecasting experiments to be run with deterministic NAAPS and ENAAPS. The main findings are that the EAKF, with its flow-dependent error covariances, makes better use of sparse observations such as AERONET AOT. Assimilating individual AERONET observations in the two-dimensional variational system can increase the analysis errors when observations are located in high AOT gradient regions. By including AERONET with MODIS AOT assimilation, the magnitudes of peak aerosol events (AOT> 1) were better captured with improved temporal variability, especially in India and Asia where aerosol prediction is a challenge. Assimilating AERONET AOT with MODIS had little impact on the 24 h forecast skill compared to MODIS assimilation only, but differences were found downwind of AERONET sites. The 24 h forecast skill was approximately the same for forecasts initialized with analyses from AERONET AOT assimilation alone compared to MODIS assimilation, particularly in regions where the AERONET network is dense; including the United States and Europe, indicating that AERONET could serve as a backup observation network for over-land synoptic-scale aerosol events.

Rubin, Juli I.↗

The circumstellar environment of IRAS 05338-0624

Millimeter continuum and spectral line observations with 10 sec, 30 sec, and 60 sec resolution are used to characterize the structure and chemistry of the gas around the young, embedded star, IRAS 05338-0624. On arcminute scales, emission from dense gas tracers outline an isolated condensation centered on the IRAS source position. The condensation is characterized by a size of approximately 60 sec, a density of 2 x 10(exp 5)/cc, and a virial mass of 40 solar mass. Interferometric CS J = 2-1 observations show two peaks, one toward the continuum peak and the other toward a position 14 sec west and 8 sec south. Single-dish maps of SO, CH3OH, and SiO show pronounced wing emission to the west of the IRAS source, which interferometer observations reveal to be a compact region of outflow activity. CS emission at redshifted and blueshifted velocities reveals a bipolar outflow oriented with a position angle of 45 deg, while SiO emission appears to be tracing a fast shock interaction region at the CS red-lobe peak, 14 sec west and 8 sec south of the IRAS source. Finally, H(13)CO(+) emission traces clumps of quiescent gas toward the IRAS source and adjacent to the blue lobe of the outflow. Column densities and molecular fractional abundances are derived to explore the interaction between the surrounding condensation and the young stellar object. We find evidence for gas phase depletions within the overall condensation in several gas tracers (CO, CS, HCN, SO) but not in the region immediately around the young stellar object. Enhanced abundances of SO, CH3OH, and SiO (by factors of 4, greater than 100, greater than 1000, respectively) are observed in the shocked gas; these enhancements may be explained in terms of a nondissociative shock liberating mantle materials that contain some amount of refractory materials, a moderate velocity dissociative shock in which only minor sputtering of Si occurs, or a shock that impacts surrounding material with a range of speeds.

Mcmullin, Joseph P.↗

Assimilation of MODIS Snow Cover Through the Data Assimilation Research Testbed and the Community Land Model Version 4

To improve snowpack estimates in Community Land Model version 4 (CLM4), the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) was assimilated into the Community Land Model version 4 (CLM4) via the Data Assimilation Research Testbed (DART). The interface between CLM4 and DART is a flexible, extensible approach to land surface data assimilation. This data assimilation system has a large ensemble (80-member) atmospheric forcing that facilitates ensemble-based land data assimilation. We use 40 randomly chosen forcing members to drive 40 CLM members as a compromise between computational cost and the data assimilation performance. The localization distance, a parameter in DART, was tuned to optimize the data assimilation performance at the global scale. Snow water equivalent (SWE) and snow depth are adjusted via the ensemble adjustment Kalman filter, particularly in regions with large SCF variability. The root-mean-square error of the forecast SCF against MODIS SCF is largely reduced. In DJF (December-January-February), the discrepancy between MODIS and CLM4 is broadly ameliorated in the lower-middle latitudes (2345N). Only minimal modifications are made in the higher-middle (4566N) and high latitudes, part of which is due to the agreement between model and observation when snow cover is nearly 100. In some regions it also reveals that CLM4-modeled snow cover lacks heterogeneous features compared to MODIS. In MAM (March-April-May), adjustments to snowmove poleward mainly due to the northward movement of the snowline (i.e., where largest SCF uncertainty is and SCF assimilation has the greatest impact). The effectiveness of data assimilation also varies with vegetation types, with mixed performance over forest regions and consistently good performance over grass, which can partly be explained by the linearity of the relationship between SCF and SWE in the model ensembles. The updated snow depth was compared to the Canadian Meteorological Center (CMC) data. Differences between CMC and CLM4 are generally reduced in densely monitored regions.

data assimilation↗

Si-Cr-Al-Mn Alloy for High Specific Resistivity

Laboratory material produced in budget period one met the target resistivity, mechanical and magnetic requirements for the Go/No-Go decision to move to industrial trials. The chosen chemistry settled on a high Cr strategy, with moderate Mn and Al additions, providing a good comprise on core loss and induction with minimal impact on mechanical properties, important to successful downstream processing. Industrial trials began in budget period two with the chosen chemistry, referred to as Alloy X. Difficulties occurred during initial hot rolling trials. Reheating the material using the standard NOES practice caused slab cracking from high thermal gradients in areas exposed to the roof burners, this was solved using a modified reheat practice. High Cr caused poor dynamic recrystallization during hot rolling, which was solved using a modified hot rolling practice. The high Cr content of the steel also caused poor decarburization during final annealing, which necessitated lowering the melt carbon aim for the final heat, together with a modified decarburization practice. Steel was finished to final thicknesses of 0.20 – 0.50 mm and evaluated for magnetic and mechanical properties. Although the target core loss for the 0.25 and 0.35 mm material was not achieved, significant reductions in high frequency core loss were measured, compared to equivalent commercially available material. Alloy X at 0.35 mm showed a 26 % and 23 % improvement at 400 HZ and 1000 Hz respectively, over Cliffs’ M-19 (0.35 mm) commercially available NOES. At 0.25 mm, Alloy X showed a 23 % and a 26 % improvement at 400 HZ and 1000 Hz respectively, over Cliffs’ HF-10 (0.25 mm) commercially available NOES. The 0.25 mm product was chosen for motor efficiency evaluation. ORNL collaborated with Cleveland-Cliffs (CC) to build, assemble, and test two 5HP motors: a baseline motor with M19 steel and a motor made with high efficiency steel (Alloy X) developed for the project. Overall, results were as expected with comparable performance at low speeds, and with more than 8% efficiency improvement for high speeds. Increased motor steel efficiency at high frequencies not only results in direct efficiency improvements but can yield reductions in motor size and cost by facilitating higher operation speeds, or by increasing the number of poles in the machine. This allows the production of more power-dense motors which are sometimes avoided with conventional material due to increased core losses. The material developed on this project provides more viable options for achieving improved motor efficiency or reduced motor size and cost.

36 MATERIALS SCIENCE↗

Power spectrum, correlation function, and tests for luminosity bias in the CfA redshift survey

We describe and apply a method for directly computing the power spectrum for the galaxy distribution in the extension of the Center for Astrophysics Redshift Survey. Tests show that our technique accurately reproduces the true power spectrum for k greater than 0.03 h Mpc(exp -1). The dense sampling and large spatial coverage of this survey allow accurate measurement of the redshift-space power spectrum on scales from 5 to approximately 200 h(exp -1) Mpc. The power spectrum has slope n approximately equal -2.1 on small scales (lambda less than or equal 25 h(exp -1) Mpc) and n approximately -1.1 on scales 30 less than lambda less than 120 h(exp -1) Mpc. On larger scales the power spectrum flattens somewhat, but we do not detect a turnover. Comparison with N-body simulations of cosmological models shows that an unbiased, open universe CDM model (OMEGA h = 0.2) and a nonzero cosmological constant (CDM) model (OMEGA h = 0.24, lambda(sub zero) = 0.6, b = 1.3) match the CfA power spectrum over the wavelength range we explore. The standard biased CDM model (OMEGA h = 0.5, b = 1.5) fails (99% significance level) because it has insufficient power on scales lambda greater than 30 h(exp -1) Mpc. Biased CDM with a normalization that matches the Cosmic Microwave Background (CMB) anisotropy (OMEGA h = 0.5, b = 1.4, sigma(sub 8) (mass) = 1) has too much power on small scales to match the observed galaxy power spectrum. This model with b = 1 matches both Cosmic Background Explorer Satellite (COBE) and the small-scale power spect rum but has insufficient power on scales lambda approximately 100 h(exp -1) Mpc. We derive a formula for the effect of small-scale peculiar velocities on the power spectrum and combine this formula with the linear-regime amplification described by Kaiser to compute an estimate of the real-space power spectrum. Two tests reveal luminosity bias in the galaxy distribution: First, the amplitude of the pwer spectrum is approximately 40% larger for the brightest 50% of galaxies in volume-limited samples that have M(sub lim) greater than M*. This bias in the power spectrum is independent of scale, consistent with the peaks-bias paradigm for galaxy formation. Second, the distribution of local density around galaxies shows that regions of moderate and high density contain both very bright (M less than M* = -19.2 + 5 log h) and fainter galaxies, but that voids preferentially harbor fainter galaxies (approximately 2 sigma significance level).

Park, Changbom↗

Effectiveness of Redundant Communications Systems in Maintaining Operational Control of Small Unmanned Aircraft

NASA has been researching prototype technologies for an Unmanned Aircraft System (UAS) Traffic Management (UTM) system to facilitate enabling of safe and efficient civilian low-altitude airspace and UAS operations, in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for beyond visual line-of-sight (BVLOS) operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 will build on the earlier TCLs and focus on technologies and requirements for operations in higher-density urban areas for tasks such as news gathering, package delivery and for managing large-scale contingencies. This paper describes a communications test conducted in TCL3 and discusses insights gained from the test. In the test, operators were directed to equip UAS with redundant Command and Control (C2) communications systems, send a maneuver command to Unmanned Aircraft (UA) via the primary system, then verify execution of the sent command. This exercise was repeated with each redundant system. The test was designed to assess effectiveness of redundant C2 systems in maintaining operational control of UA. Several UAS were configured with varying arrangements to achieve redundancy, including two identical radio modems using the same frequency band, WiFi and Long-Term Evolution (LTE) cellular modems, etc. From the test, digital data such as time maneuver command sent, time maneuver verified, etc., were collected. Descriptions of methods to detect loss of C2 communications and contingency steps for such event were collected and assessed. The final paper will include a detailed analysis of the collected data leading to the following insights. First, effectiveness of redundant C2 systems depends on several factors, such as operational environment and communications service availability. For example, use of two identical point-to-point radio to connect operator and UA on the same frequency band can be effective in mitigating radio malfunction when operating in an environment where possibility of Radio Frequency (RF) interference is low, such as over open plains. However, the same arrangement may not be effective where high level of RF transmissions in broad spectrum ranges can be expected, such as over or near urban areas. For redundant systems that consist of external communications services, such as cellular and satellite communications network, redundancy is maintained only in the areas where more than one services are available. Therefore, UAS operators should have the means to plan for and monitor the performance of external communications services they are relying on to control UA. Second, communications performance needs, such as the minimum data transfer rate and the maximum tolerable latency, should be assessed to reflect the potential hazard that can come from loss of UA control. For example, UA operations over desolate area pose less hazard to people than operations over densely populated area and performance need for the former would be less than the latter.

Jung, Jaewoo↗