Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “nighttime detection”

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

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

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Improvements in Night-Time Low Cloud Detection and MODIS-Style Cloud Optical Properties from MSG SEVIRI

The MODIS cloud optical properties algorithm (MOD06IMYD06 for Terra and Aqua MODIS, respectively) slated for production in Data Collection 6 has been adapted to execute using available channels on MSG SEVIRI. Available MODIS-style retrievals include IR Window-derived cloud top properties, using the new Collection 6 cloud top properties algorithm, cloud optical thickness from VISINIR bands, cloud effective radius from 1.6 and 3.7Jlm and cloud ice/water path. We also provide pixel-level uncertainty estimate for successful retrievals. It was found that at nighttime the SEVIRI cloud mask tends to report unnaturally low cloud fraction for marine stratocumulus clouds. A correction algorithm that improves detection of such clouds has been developed. We will discuss the improvements to nighttime low cloud detection for SEVIRI and show examples and comparisons with MODIS and CALIPSO. We will also show examples of MODIS-style pixel-level (Level-2) cloud retrievals for SEVIRI with comparisons to MODIS.

Wind, Galina (Gala)↗
DOE OSTI2025

A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Final Technical Report)

Collision of birds and bats with wind turbines is a conservation concern for both land-based and offshore wind projects. The fatality rates of birds and bats at land-based turbines are well documented. The measurement strategies on land focus on finding carcasses following collision, estimating the number of carcasses missed through searcher efficiency, carcass persistence trials and carcass fall distributions, and modeling statistically robust fatality rates. Few technologies have been developed to monitor offshore bird and bat collisions, and many that have been developed focused on detecting collisions with large birds. The few studies that have attempted to document collisions at offshore turbines do not account for smaller bodied animals or for collisions that might be missed, which prevents the calculation of statistically robust fatality rates. The overall goal of this report, A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Project), was to develop an effective multi-sensor system for quantifying bird and bat collision rates, specifically for offshore wind facilities. The Project goal and resulting automated collision detection system was achieved through two major technological advancements: 1) refining The Netherlands Organisation for Applied Scientific Research’s (TNO’s) existing WT-Bird® vibration sensing system, that had successfully detected large bird collisions during daytime, to allow for improved detection of smaller birds and bats during both daytime and nighttime hours and 2) improving image processing systems and developing and integrating machine learning algorithms to automatically detect and classify small and large bird and bat collisions with offshore turbines. This final technical report (FTR) summarizes Methods , Results , Conclusions , and Lessons Learned during each of the five Tasks identified for this research and development effort. This FTR includes summaries of the following: Task 1. Initial Engineering Tests to Improve WT-Bird® Task 2. Installation of WT‐Bird® on a Utility-scale Turbine at the National Wind Technology Center – National Renewable Energy Laboratory Task 3. Field Tests and Refinement of the Object Detection System Task 4. Validation of WT-Bird® on a Land-based Turbine Task 5. Preparation for the Implementation of WT-Bird® on an Offshore Turbine. This research and development effort documented successful improvement of the WT Bird® collision detection system to detect small birds and bats, and WT-Bird® is the first collision detection system to validate results compared to land-based post-construction monitoring. The collision trials provide estimates of missed targets that can be used to estimate fatality rates, a significant improvement relative to other offshore collision monitoring systems. Advances were made in developing an edge-processing solution to reduce data storage requirements, which is important if the system is deployed for long periods of time at offshore turbines. The improved WT-Bird® system also provides an important option for wind operators on land or offshore who need to document specific details about when collisions occur, particularly efforts to further research on bat impact minimization, or when standard fatality searches are impractical (e.g. offshore) or inadequate (e.g. challenging locations on land).

17 WIND ENERGY↗
NASA NTRS1997

Results from Two Years of Global Lightning Observation with the Optical Transient Detector

The Optical Transient Detector (OTD) is an instrument designed specifically to detect and locate lightning during either daytime or nighttime. A predecessor of the Lightning Imaging Sensor (LIS), it has been in orbit for over two and half years. During this time global lightning activity has been observed on a quasi continuous basis. During this time an extensive effort has been under way to quantify and verify the OTD performance. OTD data has been compared with both the National Lightning Detection Network (NLDN) and the Lightning Detection and Ranging (LDAR) system at KSC. Results of these intercomparisons will be presented as well as estimates of OTD overall performance parameters. In addition, one year of OTD results will be presented showing the strong influence of the sun on global lightning activity. A month by month collage of global lightning maps will be used to demonstrate both the first order forcing and more subtle influences. Finally, initial results form the Lightning Imaging Sensor, an instrument on the Tropical Rainfall Measuring Mission (TRMM) will be presented.

Christian, H. J.↗
NASA NTRS2012

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

Yost, Christopher R.↗
NASA NTRS2022

Winds at the Mars 2020 Landing Site: 1. Near-Surface Wind Patterns at Jezero Crater

This is the first part of a two-part paper. NASA's Mars 2020 Perseverance rover measured winds on the Jezero crater floor close to the delta of an ancient river. A mostly repeatable diurnal cycle was observed and presented two regimes: (a) a convective regime, from dawn to sunset, with average easterly to southeasterly winds, during which maximum wind speeds were measured, and (b) a nighttime regime with westerly-northwesterly winds followed by a relatively calm period with highly variable wind directions as a function of sol and time of night. The timing and magnitude of the observed regimes are consistent with primary control by regional and local slope flows. Data suggest that the surface circulation at Jezero region in northern spring and summer is highly unaffected by large-scale circulation except during particular periods in the diurnal cycle or generally during dust storms, which is supported by MarsWRF model simulations. Consequently, the observed seasonal variability was weak. However, sol-to-sol and seasonal variability were measured, most of it during certain nighttime periods. Traveling waves consistent with baroclinic instability were clearly observed in surface winds at L_s ∼ 75°. The early MY36/2022A regional dust storm at L_s ∼ 153° disturbed the wind patterns with changes suggesting enhanced tidal flows. After sunset, the dust storm also produced detectable gravity wave activity, increasing the mixing in the nighttime planetary boundary layer during storm conditions. Inferred wind directions from dust devil movies strongly suggest that prevailing winds continued to be slope-driven during the late summer, fall and early winter seasons.

D. Viúdez-Moreiras↗
NASA NTRS2013

The Meteoroid Environment and Spacecraft

Difference between a meteoroid and asteroid? center dot It's all a matter of size, but there is no formal limit on the size of the biggest meteoroid or smallest asteroid. center dot Generally anything bigger than 10 meters in diameter is considered an asteroid. center dot However, the currently accepted process is that if it is detected in space and given a designation by the Minor Planet Center, it is an asteroid, no matter how big - example: 2008 TC3 is listed as an asteroid, despite being only 2 meters in diameter. Dynamical studies (e.g. Wiegert & Vaubaillon, 2008) indicate that - Helion sources originate mainly from Jupiter family comets (JFCs) - Apex sources from retrograde Halley family comets (HFCs) and long period comets. - Toroidal sources from prograde HFCs? center dot >90% of meteoroids in inner Solar System come from comets. Three main sources - Photographic (Super‐Schmidt) - Specular Radar center dot (Harvard Radio Meteor Project (HRMP) center dot CMOR center dot AMOR - HPLA center dot ALTAIR center dot Jicamarca center dot Arecibo center dot Photographic have lower number statistics and unique biases - Nighttime only - approx. V3.5 dependence on light production - Detection sensitivity is function of angular velocity center dot Radar has different biases - Ionization production also steep function of velocity (V3.5‐4) - Initial trail radius, finite velocity and diffusion attenuation center dot HPLA biases - Still controversy over how much and what sort of biases may or may not be present.

Cooke, William J.↗
NASA NTRS2017

Characterize Planetary Surfaces from a Single Point to a Large Area Using a Standoff Ultra-Compact µ-Raman Instrument

A standoff Ultra-Compact micro-Raman (SUCR) instrument is used for detection of minerals, organic, and biological materials in daylight and nighttime conditions. The standoff measurements from a SUCR instrument based on micro-Raman spectroscopy on a rover or lander platform is ideal for identifying various types of ices, minerals, organics and biogenic materials. The μ-Raman measurements can assist in determining the biological potential for habitability assessment of planetary bodies as well as amino acid detection for evidence of past or present life on Mars, Europa, and other solar bodies. The SUCR instrument is used to inspect minerals, organic, biomarkers, ice, and embedded materials inside ice, as well as to conduct Raman line scanning from a single point to a large area for standoff detection at a 6-cm target distance.

M Nurul Abedin↗
NASA NTRS2021

Volatiles and Refractories in Surface-Bounded Exospheres in the Inner Solar System

Volatiles and refractories represent the two end-members in the volatility range of species in any surface-bounded exosphere. Volatiles include elements that do not interact strongly with the surface, such as neon (detected on the Moon) and helium (detected both on the Moon and at Mercury), but also argon, a noble gas (detected on the Moon) that surprisingly adsorbs at the cold lunar nighttime surface. Refractories include species such as calcium, magnesium, iron, and aluminum, all of which have very strong bonds with the lunar surface and thus need energetic processes to be ejected into the exosphere. Here we focus on the properties of species that have been detected in the exospheres of inner Solar System bodies, specifically the Moon and Mercury, and how they provide important information to understand source and loss processes of these exospheres, as well as their dependence on variations in external drivers.

Moon↗
NASA NTRS1981

AE-C observations of electric fields around auroral arcs

Variations in the ion drift signatures observed by the Atmosphere Explorer-C satellite during passage through the auroral zone are discussed. Three mutually perpendicular components of ion drift velocity were derived, along with the ion concentrations and temperature. Electric field signatures detected in the vicinity of auroral arcs in the nighttime ionosphere are described, including the existence of auroral arcs both equatorward and poleward of the global convection reversal. It was also found that when electric field enhancements occur on one side of an auroral arc, particle precipitation is present on both sides, although the field-aligned potential drop associated with the accompanying particles is lower than that required for a discrete arc. Finally, it is noted that the region of the magnetosphere connected to discrete arcs has large and small areas in which adjacent flow regions are opposed to one another.

Heelis, R. A.↗
NASA NTRS2020

A Machine Learning-Based Cloud Detection and Thermodynamic Phase Classification Algorithm using Passive Spectral Observations

We trained two Random Forest (RF) machine-learning models for cloud mask and cloud thermodynamic phase detection using spectral observations from VIIRS on Suomi NPP (SNPP). Observations from CALIOP were carefully selected to provide reference labels. The two RF models were trained for all-day and daytime-only conditions using a 4-year collocated VIIRS/CALIOP dataset from 2013 to 2016. Due to the orbit difference, the collocated CALIOP and SNPP VIIRS training samples cover a broad viewing zenith angle range, which is a great benefit to overall model performance. The all-day model uses 3 VIIRS infrared (IR) bands (8.6,11, and 12 μm) and the daytime model uses 5 Near-IR (NIR) and Shortwave-IR (SWIR) bands (0.86, 1.24, 1.38, 1.64 and 2.25 μm) together with the 3 IR bands to detect clear, liquid water, and ice cloud pixels. Up to 7 surface types, namely, ocean/water, forest, cropland, grassland, snow/ice, barren/desert, and shrubland, were considered separately to enhance performance for both models. Detection of cloudy pixels and thermodynamic phase with the two RF models were compared against collocated CALIOP products from 2017. It is shown that, with a conservative screening process that excludes the most challenging cloudy pixels for passive remote sensing, the two RF models have high accuracy rates in comparison with the CALIOP reference for both cloud detection and thermodynamic phase. Other existing SNPP VIIRS and Aqua MODIS cloud mask and phase products are also evaluated, with results showing that the two RF models and the MODIS MYD06 optical property phase product are the top 3 algorithms with respect to lidar observations during the daytime. During the nighttime, the RF all-day model works best for both cloud detection and phase, in particular for pixels over snow/ice surfaces. The present RF models can be extended to other similar passive instruments if training samples can be collected from CALIOP or other lidars. However, the quality of reference labels and potential sampling issues that may impact model performance would need further attention.

cloud detection↗
NASA NTRS2011

Developing and Evaluating RGB Composite MODIS Imagery for Applications in National Weather Service Forecast Offices

Satellite remote sensing has gained widespread use in the field of operational meteorology. Although raw satellite imagery is useful, several techniques exist which can convey multiple types of data in a more efficient way. One of these techniques is multispectral compositing. The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed two multispectral satellite imagery products which utilize data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites, based upon products currently generated and used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The nighttime microphysics product allows users to identify clouds occurring at different altitudes, but emphasizes fog and low cloud detection. This product improves upon current spectral difference and single channel infrared techniques. Each of the current products has its own set of advantages for nocturnal fog detection, but each also has limiting drawbacks which can hamper the analysis process. The multispectral product combines each current product with a third channel difference. Since the final image is enhanced with color, it simplifies the fog identification process. Analysis has shown that the nighttime microphysics imagery product represents a substantial improvement to conventional fog detection techniques, as well as provides a preview of future satellite capabilities to forecasters.

Oswald, Hayden↗
NASA NTRS1971

Geophysical aspects of remote sensing

Results obtained through the NASA Earth Resources Aircraft Program at Mill Creek, Oklahoma, provide a case history example of the application of remote sensing to the identification of geologic rock units. Thermal infrared images are interpreted by means of a sequence of models of increasing complexity. The roles of various parameters are examined: rock properties (thermal inertia, albedo, emissivity), site location (latitude), season (sun's declination), atmospheric effects (cloud cover, transmission, air temperature), and topographic orientation (slope, azimuth). The results obtained at this site also illustrate the development of an important application of remote sensing in geologic identification. Relatively pure limestones and dolomites of the Mill Creek test area can be differentiated in nighttime infrared images, and facies changes between them can be detected along and across strike. The predominance on the earth's surface of sedimentary rocks, of which limestone and dolomite are major members, indicates the importance of this discrimination.

Watson, K.↗
NASA NTRS2000

Passive Night Vision Sensor Comparison for Unmanned Ground Vehicle Stereo Vision Navigation

One goal of the "Demo III" unmanned ground vehicle program is to enable autonomous nighttime navigation at speeds of up to 10 m.p.h. To perform obstacle detection at night with stereo vision will require night vision cameras that produce adequate image quality for the driving speeds, vehicle dynamics, obstacle sizes, and scene conditions that will be encountered. This paper analyzes the suitability of four classes of night vision cameras (3-5 micrometer cooled FLIR, 8-12 micrometer cooled FLIR, 8-12 micrometer uncooled FLIR, and image intensifiers) for night stereo vision, using criteria based on stereo matching quality, image signal to noise ratio, motion blur and synchronization capability. We find that only cooled FLIRs will enable stereo vision performance that meets the goals of the Demo III program for nighttime autonomous mobility.

Owens, Ken↗
NASA NTRS2016

Improvements to Lunar BRDF-Corrected Nighttime Satellite Imagery: Uses and Applications

Observations made by the VIIRS day/night band (DNB) provide daily, nighttime measurements to monitor Earth surface processes.However, these observations are impacted by variations in reflected solar radiation on the moon's surface. As the moon transitions from new to full phase, increasing radiance is reflected to the Earth's surface and contributes additional reflected moonlight from clouds and land surface, in addition to emissions from other light sources observed by the DNB. The introduction of a bi-directional reflectance distribution function (BRDF) algorithm serves to remove these lunar variations and normalize observed radiances. Provided by the Terrestrial Information Systems Laboratory at Goddard Space Flight Center, a 1 km gridded lunar BRDF-corrected DNB product and VIIRS cloud mask can be used for a multitude of nighttime applications without influence from the moon. Such applications include the detection of power outages following severe weather events using pre-and post-event DNB imagery, as well as the identification of boat features to curtail illegal fishing practices. This presentation will provide context on the importance of the lunar BRDF correction algorithm and explore the aforementioned uses of this improved DNB product for applied science applications.

NWS↗
NASA NTRS2023

SNPP and N20 VIIRS Day/Night Band (DNB) Calibration and Performance

The first two Visible Infrared Imaging Radiometer Suite (VIIRS) instruments, on-board the Suomi National Polar-orbiting Partnership (SNPP) and the NOAA-20 (N20) satellites, have been operating for over 11 and 5 years since their launches on28 October 2011 and 18 November 2017 respectively. The day-night band (DNB) onboard VIIRS is a panchromatic visible/near-infrared (Vis/NIR) channel designed to detect radiance from the brightest daytime scenes down to very dim nighttime scenes illuminated by a quarter moon. In this paper, we present the SNPP and N20 VIIRS DNB calibration results performed by the NASA VIIRS Characterization Support Team (VCST) to generate the calibration coefficient look up tables (LUTs) for the latest NASA Level 1B Collection 2 products. The differing DNB straylight contamination between VIIRS instruments is discussed along with the correction methodology and performance.

Junqiang Sun↗
NASA NTRS1989

Options for daytime monitoring of atmospheric visibility in optical communications

Techniques for daytime detection of atmospheric transmission and cloud cover to determine the capabilities of future deep-space optical communications links are considered. A modification of the planned nighttime photometry program will provide the best data while minimizing the need for further equipment. Greater degrees of modification will provide increased detection capabilities. Future testing of the equipment will better define the improvement offered by each level of modification. Daytime photometry is favored at certain wavelengths because of higher transmission and lower background noise, thus giving an increased signal-to-noise ratio. A literature search has provided a list of stars brighter than second magnitude at these wavelengths.

Erickson, D.↗
NASA NTRS2000

Confirmation of NLDN Long Range Strike Locations with LIS Observations

This study compares the lightning locations reported by the National Lightning Detection Network (NLDN) with the lightning locations determined by the Lightning Imaging Sensor (LIS). The NLDN system identifies the rf signature of cloud-to-ground lightning. The LIS data is the top level of a hierarchy of optical data objects. The centroid and timing of each LIS lightning activity center are compared with each flash in a subset of the NLDN long range lightning location data in a portion of the Atlantic Ocean and the Caribbean Sea consisting of those locations more than 625 km from any sensor. This subset is produced by analyzing each reported NLDN location to determine if that location is within the LIS field of view at the time of the reported flash. The Tropical Rainfall Measuring Mission Satellite (TRMM) orbit limits the cross-sensor comparison to tropical and sub-tropical regions. Because the rf-detection system depends on ionospheric propagation conditions, a separate analysis was made for daylight conditions at both source and sensor as well as nighttime at both places. A full year of data is compared to provide an adequate sample of each data set. Confirmation of lightning in the general location of the NLDN report is established when LIS detected one or more centers of lightning activity within a 2 degree radius from the NLDN location.

Boeck, William↗
DOE OSTI2022

Comparison of scattering ratio profiles retrieved from ALADIN/Aeolus and CALIOP/CALIPSO observations and preliminary estimates of cloud fraction profiles

The space-borne active sounders have been contributing invaluable vertically resolved information of atmospheric optical properties since the launch of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) in 2006. To build long-term records from space-borne lidars useful for climate studies, one has to understand the differences between successive space lidars operating at different wavelengths, flying on different orbits, and using different viewing geometries, receiving paths, and detectors. In this article, we compare the results of Atmospheric Laser Doppler INstrument (ALADIN) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidars for the period from 28 June to 31 December 2019. First, we build a dataset of ALADIN–CALIOP collocated profiles (Δdist<1°; Δtime<6 h). Then we convert ALADIN's 355 nm particulate backscatter and extinction profiles into the scattering ratio vertical profiles SR(z) at 532 nm using molecular density profiles from Goddard Earth Observing System Data Assimilation System, version 5 (GEOS-5 DAS). And finally, we build the CALIOP and ALADIN globally gridded cloud fraction profiles CF(z) by applying the same cloud detection threshold to the SR(z) profiles of both lidars at the same spatial resolution. Before comparing the SR(z) and CF(z) profiles retrieved from the two analyzed lidar missions, we performed a numerical experiment to estimate the best achievable cloud detection agreement CDA norm (z) considering the differences between the instruments. We define CDA norm (z) in each latitude–altitude bin as the occurrence frequency of cloud layers detected by both lidars, divided by a cloud fraction value for the same latitude–altitude bin. We simulated the SR(z) and CF(z) profiles that would be observed by these two lidars if they were flying over the same atmosphere predicted by a global model. By analyzing these simulations, we show that the theoretical limit for CDA$_{norm}^{theor}$(z) for a combination of ALADIN and CALIOP instruments is equal to 0.81±0.07 at all altitudes. In other words, 19 % of the clouds cannot be detected simultaneously by two instruments due to said differences. The analyses of the actual observed CALIOP–ALADIN collocated dataset containing ~78 000 pairs of nighttime SR(z) profiles revealed the following points: (a) the values of SR(z) agree well up to ~3 km height. (b) The CF(z) profiles show agreement below ~3 km, where ~80 % of the clouds detected by CALIOP are detected by ALADIN as expected from the numerical experiment. (c) Above this height, the CDA$_{norm}^{obs}$(z) reduces to ~50 %. (d) On average, better sensitivity to lower clouds skews ALADIN's cloud peak height in pairs of ALADIN–CALIOP profiles by ~0.5±0.6 km downwards, but this effect does not alter the heights of polar stratospheric clouds and high tropical clouds thanks to their strong backscatter signals. (e) The temporal evolution of the observed CDA$_{norm}^{obs}$(z) does not reveal any statistically significant change during the considered period. This indicates that the instrument-related issues in ALADIN L0/L1 have been mitigated, at least down to the uncertainties of the following CDA$_{norm}^{obs}$(z) values: 68±12 %, 55±14 %, 34±14 %, 39±13 %, and 42±14 % estimated at 0.75, 2.25, 6.75, 8.75, and 10.25 km, respectively.

54 ENVIRONMENTAL SCIENCES↗