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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Building a Real-Time Flood Prediction Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the local government of Howard County, Maryland, to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a statistical model capable of hindcasting the two severe flash flood events that devastated Ellicott City and transitioned to a ‘Long Short-Term Memory’ based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using Nash-Sutcliffe Efficiency. The final product, the Sequentially Trained Real-time EstimAted Model (STREAM) predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

NASA DEVELOP↗
NASA NTRSDate not supplied

Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the Howard County government in Maryland to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a prediction model capable of hindcasting the two severe flash flood events that devastated Ellicott City, and transitioned to an Long Short-Term Memory (LSTM) based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using the Nash-Sutcliffe Efficiency (NSE). The final product, called the Sequentially Trained Real-time EstimAted Model (STREAM), predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh (HRRR) model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate the OEM’s emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

Ryan Hammock↗
NASA NTRS1987

SIR-B ocean-wave enhancement with fast Fourier transform techniques

Shuttle Imaging Radar (SIR-B) imagery is Fourier filtered to remove the estimated system-transfer function, reduce speckle noise, and produce ocean scenes with a gray scale that is proportional to wave height. The SIR-B system response to speckled scenes of uniform surfaces yields an estimate of the stationary wavenumber response of the imaging radar, modeled by the 15 even terms of an eighth-order two-dimensional polynomial. Speckle can also be used to estimate the dynamic wavenumber response of the system due to surface motion during the aperture synthesis period, modeled with a single adaptive parameter describing an exponential correlation along track. A Fourier filter can then be devised to correct for the wavenumber response of the remote sensor and scene correlation, with subsequent subtraction of an estimate of the speckle noise component. A linearized velocity bunching model, combined with a surface tilt and hydrodynamic model, is incorporated in the Fourier filter to derive estimates of wave height from the radar intensities corresponding to individual picture elements.

Tilley, David G.↗
NASA NTRS1986

Description of data on the Nimbus 7 LIMS map archive tape: Temperature and geopotential height

The process by which the analysis of the Limb Infared Monitor of the Stratosphere (LIMS) experiment data were used to produce estimates of synoptic maps of temperature and geopotential height is described. In addition to a detailed description of the analysis procedure, several interesting features in the data are discussed and these features are used to demonstrate how the analysis procedure produced the final maps and how one can estimate the uncertainties in the maps. In addition, features in the analysis are noted that would influence how one might use, or interpret, the results. These include subjects such as smoothing and the interpretation of wave components. While some suggestions are made for an improved analysis of the data, it is shown that, in general, the maps are an excellent estimation of the synoptic fields.

Haggard, K. V.↗
NASA NTRS1977

Phugoid characteristics of a YF-12 airplane with variable-geometry inlets obtained in flight tests at a Mach number of 2.9

Flight tests were conducted with the YF-12 airplane to examine the airplane's longitudinal characteristics at a Mach number of approximately 2.9. Phugoid oscillations as well as short period pulses were analyzed with the variable geometry engine inlets in the fixed and the automatic configurations. Stability and control derivatives for the velocity and altitude degrees of freedom and the standard short period derivatives were obtained. Inlet bypass door position was successfully used to represent the total inlet system, and the effect of the inlets on the velocity and altitude derivatives was determined. The phugoid mode of the basic airplane (fixed inlet configuration) had neutral damping, and the height mode was stable. With the addition of the inlets in the automatic configuration, the phugoid mode was slightly divergent and the height mode was divergent with a time to double amplitude of about 114 seconds. The results of the derivative estimation indicated that the change in the height mode characteristics was primarily the result of the change in the longitudinal force derivative with respect to velocity.

Powers, B. G.↗
NASA NTRS1993

Postprocessing of satellite altimetry return signals for improved sea surface topography accuracy

Retracked southern ocean data from the first 34 repeat cycles of the Geosat Exact Repeat Mission are analyzed. The difference between the surface heights calculated from the retracked data and the original on-board estimate is less than 10 cm for significant wave heights (SWH) lower than 10 m but increases to about 1.0 m at an SWH of 18 m. The electromagnetic (EM) bias coefficient calculated using the retracked data is generally slightly less than that using the unretracked data and does not decrease as much with SWH as to the EM bias coefficients calculated from the unretracked data. A map of the sea surface height variability of the southern ocean created using the retracked data shows differences from variability maps created using the unretracked data in regions of high wave heights. This study shows that retracking will improve altimeter precision.

Brenner, A. C.↗
NASA NTRS1995

Topography of closed depressions, scarps, and grabens in the north Tharsis region of Mars: Implications for shallow crustal discontinuities and Graben formation

Using Viking Orbiter images, detailed photoclinometric profiles were obtained across 10 irregular depressions, 32 fretted fractures, 40 troughs and pits, 124 solitary scarps, and 370 simple grabens in the north Tharsis region of Mars. These data allow inferences to be made on the shallow crustal structure of this region. The frequency modes of measured scarp heights correspond with previous general thickness estimates of the heavily cratered and rigded plains units. The depths of the flat-floored irregular depressions (55-175 m), fretted fractures (85-890 m), and troughs and pits (60-1620 m) are also similar to scarp heights (thicknesses) of the geologic units in which these depressions occur, which suggests that the depths of these flat-floored features were controlled by erosional base levels created by lithologic contacts. Although the features have a similar age, both their depths and their observed local structural control increase in the order listed above, which suggests that the more advanced stages of associated fracturing facilitated the development of these depressions by increasing permeability. If a ground-ice zone is a factor in development of these features, as has been suggested, our observation that the depths of these features decrease with increasing latitude suggests that either the thickness of the ground-ice zone does not increase poleward or the depths of the depressions were controlled by the top of the ground-ice zone whose depth may decrease with latitude.

Davis, P. A.↗
NASA NTRSDate not supplied

Vegetation Heights for Landsat Land Cover Classes in the Interior Boreal Forest Region of Alaska

Accurate determination and mapping of vegetation height is a prerequisite for regional estimations of above ground biomass, carbon pool dynamics, and improved modeling of future climate-vegetation-soil interactions. This study combined land cover class maps (at 30-m pixel resolution) derived from Landsat image bands with canopy vegetation heights detected at 1-m resolution from NASA G-LiHT Lidar flights, both from the year 2014 for the Middle Tanana Valley near Fairbanks, Alaska. The statistical distributions and structural attributes from Lidar plant heights were derived and refined for all Landsat vegetation classes. Results showed that the tallest cover classes in this region were deciduous forests (dominated by birch and aspen), followed by evergreen spruce and wooded wetlands. Open shrubland and herbaceous cover areas were determined to be 2 - 5 m shorter, on average, than these boreal forest stands. Tall shrubland cover areas were slightly shorter than most spruce-dominated evergreen forest areas. Nearly 60% of all low shrubland and herbaceous wetland pixels were detected with at least one tree crown greater than 10 m tall. This was in contrast to evergreen and deciduous forest classes that showed 88% of stands with at least one tree crown greater than 10 m tall.

Vegetation↗
NASA NTRS2002

Estimating the Ocean Flow Field from Combined Sea Surface Temperature and Sea Surface Height Data

This project was part of a previous grant at MIT that was moved over to the Scripps Institution of Oceanography (SIO) together with the principal investigator. The final report provided here is concerned only with the work performed at SIO since January 2000. The primary focus of this project was the study of the three-dimensional, absolute and time-evolving general circulation of the global ocean from a combined analysis of remotely sensed fields of sea surface temperature (SST) and sea surface height (SSH). The synthesis of those two fields was performed with other relevant physical data, and appropriate dynamical ocean models with emphasis on constraining ocean general circulation models by a combination of both SST and SSH data. The central goal of the project was to improve our understanding and modeling of the relationship between the SST and its variability to internal ocean dynamics, and the overlying atmosphere, and to explore the relative roles of air-sea fluxes and internal ocean dynamics in establishing anomalies in SST on annual and longer time scales. An understanding of those problems will feed into the general discussion on how SST anomalies vary with time and the extend to which they interact with the atmosphere.

Stammer, Detlef↗
NASA NTRS1994

The Martian atmospheric planetary boundary layer stability, fluxes, spectra, and similarity

This is the first analysis of the high frequency data from the Viking lander and spectra of wind, in the Martian atmospheric surface layer, along with the diurnal variation of the height of the mixed surface layer, are calculated for the first time for Mars. Heat and momentum fluxes, stability, and z(sub O) are estimated for early spring, from a surface temperature model and from Viking Lander 2 temperatures and winds at 44 deg N, using Monin-Obukhov similarity theory. The afternoon maximum height of the mixed layer for these seasons and conditions is estimated to lie between 3.6 and 9.2 km. Estimations of this height is of primary importance to all models of the boundary layer and Martian General Circulation Models (GCM's). Model spectra for two measuring heights and three surface roughnesses are calculated using the depth of the mixed layer, and the surface layer parameters and flow distortion by the lander is also taken into account. These experiments indicate that z(sub O), probably lies between 1.0 and 3.0 cm, and most likely is closer to 1.0 cm. The spectra are adjusted to simulate aliasing and high frequency rolloff, the latter caused both by the sensor response and the large Kolmogorov length on Mars. Since the spectral models depend on the surface parameters, including the estimated surface temperature, their agreement with the calculated spectra indicates that the surface layer estimates are self consistent. This agreement is especially noteworthy in that the inertial subrange is virtually absent in the Martian atmosphere at this height, due to the large Kolmogorov length scale. These analyses extend the range of applicability of terrestrial results and demonstrate that it is possible to estimate the effects of severe aliasing of wind measurements, to produce a models which agree well with the measured spectra. The results show that similarity theory developed for Earth applies to Mars, and that the spectral models are universal.

Tillman, James E.↗
NASA NTRS2021

Estimating Bare Earth in Sparse Boreal Forests With WorldView Stereo Imagery

Circumboreal forests are currently experiencing rapid climate warming which is altering their structure, productivity, and status as a carbon sink. Very-high resolution (VHR, <2 m) stereo derived digital surface models are available to monitor these forests, but, a similar resolution digital terrain model (DTM) is required to extract information about tree height, which is often used to estimate carbon content. To our knowledge, no openly available VHR DTM currently exists. To address this need, we developed approaches to extract DTMs by filtering VHR stereo point clouds (PCs) in sparse canopies of Alaska. Our evaluation consisted of two stereo processing methods with three PC search radii, at six different tree canopy cover (TCC) intervals. We found VHR DTMs were robust for estimating bare ground at TCC intervals less than 40% with vertical errors <1.6 m using airborne small footprint light detection and ranging (LiDAR) as reference.

Christopher S R Neigh↗
NASA NTRS2021

Estimating Bare Earth in Sparse Boreal Forests With WorldView Stereo Imagery

Circumboreal forests are currently experiencing rapid climate warming which is altering their structure, productivity, and status as a carbon sink. Very-high resolution (VHR, <2 m) stereo derived digital surface models are available to monitor these forests, but, a similar resolution digital terrain model (DTM) is required to extract information about tree height, which is often used to estimate carbon content. To our knowledge, no openly available VHR DTM currently exists. To address this need, we developed approaches to extract DTMs by filtering VHR stereo point clouds (PCs) in sparse canopies of Alaska. Our evaluation consisted of two stereo processing methods with three PC search radii, at six different tree canopy cover (TCC) intervals. We found VHR DTMs were robust for estimating bare ground at TCC intervals less than 40% with vertical errors <1.6 m using airborne small footprint light detection and ranging (LiDAR) as reference.

Christopher S. R. Neigh↗
NASA NTRS1992

Geopotential models of the Earth from satellite tracking, altimeter and surface gravity observations: GEM-T3 and GEM-T3S

Improved models of the Earth's gravitational field have been developed from conventional tracking data and from a combination of satellite tracking, satellite altimeter and surface gravimetric data. This combination model represents a significant improvement in the modeling of the gravity field at half-wavelengths of 300 km and longer. Both models are complete to degree and order 50. The Goddard Earth Model-T3 (GEM-T3) provides more accurate computation of satellite orbital effects as well as giving superior geoidal representation from that achieved in any previous GEM. A description of the models, their development and an assessment of their accuracy is presented. The GEM-T3 model used altimeter data from previous satellite missions in estimating the orbits, geoid, and dynamic height fields. Other satellite tracking data are largely the same as was used to develop GEM-T2, but contain certain important improvements in data treatment and expanded laser tracking coverage. Over 1300 arcs of tracking data from 31 different satellites have been used in the solution. Reliable estimates of the model uncertainties via error calibration and optimal data weighting techniques are discussed.

Lerch, F. J.↗
NASA NTRS2016

Combining Stereo SECCHI COR2 and HI1 Images for Automatic CME Front Edge Tracking

COR2 coronagraph images are the most commonly used data for coronal mass ejection (CME) analysis among the various types of data provided by the STEREO (Solar Terrestrial Relations Observatory) SECCHI (Sun-Earth Connection Coronal and Heliospheric Investigation) suite of instruments. The field of view (FOV) in COR2 images covers 215 solar radii (Rs) that allow for tracking the front edge of a CME in its initial stage to forecast the lead-time of a CME and its chances of reaching the Earth. However, estimating the lead-time of a CME using COR2 images gives a larger lead-time, which may be associated with greater uncertainty. To reduce this uncertainty, CME front edge tracking should be continued beyond the FOV of COR2 images. Therefore, heliospheric imager (HI1) data that covers 1590 Rs FOV must be included. In this paper, we propose a novel automatic method that takes both COR2 and HI1 images into account and combine the results to track the front edges of a CME continuously. The method consists of two modules: pre-processing and tracking. The pre-processing module produces a set of segmented images, which contain the signature of a CME, for both COR2 and HI1 separately. In addition, the HI1 images are resized and padded, so that the center of the Sun is the central coordinate of the resized HI1 images. The resulting COR2 andHI1 image set is then fed into the tracking module to estimate the position angle (PA) and track the front edge of a CME. The detected front edge is then used to produce a height-time profile that is used to estimate the speed of a CME. The method was validated using 15 CME events observed in the period from January 1, 2008 to August 31, 2009. The results demonstrate that the proposed method is effective for CME front edge tracking in both COR2 and HI1 images. Using this method, the CME front edge can now be tracked automatically and continuously in a much larger range, i.e., from 2 to 90 Rs, for the first time. These improvement scan greatly help in making the quantitative CME analysis more accurate and have the potential to assist in space weather forecasting.

Kirnosov, Vladimir↗
NASA NTRS1973

Coordinated observations of chemical releases from the ground and from aircraft at high latitudes

The ground observations of the Na-Li trail released from a Nike-Apache rocket obtained by the Geophysical Institute are discussed. By using the nominal trajectory for a 60 pound payload and the particular rocket, a best fit trajectory was determined based on the Ester Dome photographic data, launch time and earth-sun geometrical shadow height. From these calculations, the height of obvious features along the trail were determined and their velocity estimated. A clockwise rotation of the velocity vector with increasing height was observed. Velocities deduced at various altitudes were then compared to meter radar data also obtained during this period. The comparisons of these two neutral wind measurements techniques are satisfactory.

Romick, G. J.↗
NASA NTRS2019

Boreal canopy surfaces from spaceborne stereogrammetry

Surface elevation estimates from high resolution spaceborne image (HRSI) stereogrammetry are used to examine fine-scaled structure of boreal forest canopies. These data can depict detailed spatial patterns of vertical forest structure at remote sites across the circumpolar domain where these estimates would otherwise be unavailable. This work examines where these estimates are most effective at describing vertical forest structure to explain which canopy surfaces they represent. We evaluated the variation in canopy surface estimates captured from four general types of HRSI digital surface models (DSMs) across the full range of boreal canopy cover. These DSMs, classified into 4 types by grouping them according to the acquisition's (1) sun elevation angle (low or high) and (2) seasonality-driven ground surface condition (snow presence/absence), vary with acquisition characteristics and the details of this variation continues to be studied. We explored some of this variation by comparing the distributions of differences in boreal canopy percentile heights derived from reference small footprint lidar in Tanana Valley, Alaska with canopy surface elevations derived from these 4 types of HRSI DSMs. We examined how canopy surface estimates from HRSI DSMs differ according to acquisition characteristics and canopy cover, and ultimately which canopy surfaces are represented in these DSMs. Our results help clarify which boreal canopy surfaces are representative of those captured with HRSI DSMs. They show that in the Tanana Valley (1) DSMs grouped by sun elevation angle and ground surface condition provide different surface estimates of boreal canopies; (2) the two DSM types that appear to most differently capture boreal forest canopy surfaces are DSMs from snow-free images acquired at sun elevation angles <30° (Low sun elev. & snow-free) and those with snow-cover at sun elevation angles ≥30° (High sun elev. & snow-free); (3) DSMs with snow most often do not capture upper canopy surfaces; (4) the “Low sun elev. & snow-free” DSMs resolve surfaces that are most representative of upper canopy surfaces (dense forests >60% cover, 70th–80th percentile heights); and (5) in the most dense forests (>80% cover) where canopy gaps are least likely to bias downward the average surface estimates, the snow-free DSM types are representative of 70th - 80th percentile heights (“Low sun elev. & snow-free”) and 60th–70th percentile heights (“High sun elev. & snow-free”). The combination of horizontal structure (canopy cover) and acquisition characteristics affect the boreal vertical structure (canopy surface height) estimates from spaceborne stereogrammetry. These effects should be considered when analyzing products derived from HRSI DSMs, and as part of a comprehensive approach to spaceborne remote sensing of circumpolar boreal forests.

forest structure↗
NASA NTRS2018

MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds

Global wind observations are fundamental for studying weather and climate dynamics and for operational forecasting. Most wind measurements come from atmospheric motion vectors (AMVs) by tracking the displacement of cloud or water vapor features. These AMVs generally rely on thermal infrared (IR) techniques for their height assignments, which are subject to large uncertainties in the presence of weak or reversed vertical temperature gradients near the planetary boundary layer (PBL)and tropopause folds. Stereo imaging can overcome the height assignment problem using geometric parallax for feature height determination. In this study we develop a stereo 3D-Wind algorithm to simultaneously retrieve AMV and height from geostationary (GEO) and low Earth orbit (LEO) satellite imagery and apply it to collocated Geostationary Operational Environmental Satellite (GOES)and Multi-angle Imaging SpectroRadiometer (MISR) imagery. The new algorithm improves AMV and height relative to products from GOES or MISR alone, with an estimated accuracy of <0.5 m/s in AMV and <200 m in height with 2.2 km sampling. The algorithm can be generalized to other LEO-GEO or LEO-LEO combinations for greater spatiotemporal coverage. The technique demonstrated with MISR and GOES has important implications for future high-quality AMV observations, for which a low-cost constellation of CubeSats can play a vital role.

MISR↗
NASA NTRS1992

Aircraft- and tower-based fluxes of carbon dioxide, latent, and sensible heat

Fluxes of carbon dioxide, water vapor, and sensible heat obtained over a grassland ecosystem, during the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), using an aircraft- and two tower-based systems are compared for several days in 1987 and in 1989. The tower-based cospectral estimates of CO2, sensible heat, water vapor, and momentum, expressed as a function of wavenumber K times sampling height z, are relatively similar to the aircraft-based estimates for K x z greater than 0.1. A measurable contribution to the fluxes is observed by tower-based systems at K x z less than 0.01 but not by the aircraft-based system operating at an altitude of approximately 100 m over a 15 x 15 km area. Using all available simultaneous aircraft and tower data, flux estimates by both systems were shown to be highly correlated. As expected from the spatial variations of the greenness index, surface extrapolation of airborne flux estimates tended to lie between those of the two tower sites. The average fluxes obtained, on July 11, 1987, and August 4, 1989, by flying a grid pattern over the FIFE site agreed with the two tower data sets for CO2, but sensible and latent heat were smaller than those obtained by the tower-based systems. However, in general, except for a small underestimation due to the long wavelength contributions and due to flux divergence with height, the differences between the aircraft- and tower-based surface estimates of fluxes appear to be mainly attributable to differences in footprint, that is, differences in the area contributing to the surface flux estimates.

Desjardins, R. L.↗