Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “elevation models”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Geoscience Applications of Airborne and Spaceborne Lidar Altimetry

Recent advances in lidar altimetry technology have enabled new methods to describe the vertical structure of the Earth's surface with great accuracy. Application of these methods in several geoscience disciplines will be described. Airborne characterization of vegetation canopy structure will be illustrated, including a validation of lidar-derived Canopy Height Profiles for closed-canopy, broadleaf forests. Airborne detection of tectonic landforms beneath dense canopy will also be illustrated, with an application mapping active fault traces in the Puget Lowland of Washington state for earthquake hazard assessment purposes. Application of data from the first and second flights of the Shuttle Laser Altimeter will also be discussed in an assessment of global digital elevation model accuracy and error characteristics. Two upcoming space flight missions will be described, the Vegetation Canopy Lidar (VCL) and the Ice, Cloud and Land Elevation Mission (ICESat), which will provide comprehensive lidar altimeter observations of the Earth's topography and vegetation cover.

Harding David J.↗
NASA NTRS2002

Real Time Monitoring of Flooding from Microwave Satellite Observations

We have developed a new method for making high-resolution flood extent maps (e.g., at the 30-100 m scale of digital elevation models) in real-time from low-resolution (20-70 km) passive microwave observations. The method builds a "flood-potential" database from elevations and historic flood imagery and uses it to create a flood-extent map consistent with the observed open water fraction. Microwave radiometric measurements are useful for flood monitoring because they sense surface water in clear-or-cloudy conditions and can provide more timely data (e.g., compared to radars) from relatively wide swath widths and an increasing number of available platforms (DMSP, ADEOS-II, Terra, NPOESS, GPM). The chief disadvantages for flood mapping are the radiometers' low resolution and the need for local calibration of the relationship between radiances and open-water fraction. We present our method for transforming microwave sensor-scale open water fraction estimates into high-resolution flood extent maps and describe 30-day flood map sequences generated during a retrospective study of the 1993 Great Midwest Flood. We discuss the method's potential improvement through as yet unimplemented algorithm enhancements and expected advancements in microwave radiometry (e.g., improved resolution and atmospheric correction).

Galantowicz, John F.↗
NASA NTRS2007

SPOT-VEG Based Analysis of Siberian Silkmoth Outbreak

The spatial and temporal dynamics of an outbreak of the Siberian silkmoth were correlated with topographic features of the affected area using SPOT-VEG data and a high resolution digital elevation model (DEM). In 2002-2003 an outbreak affected approximately 20,000 ha in the South Siberian mountains of Russia. The outbreak began between the elevations of approximately 430- 480 m and on southwest slopes with steepness < 5 degrees. As the pest searched for food it moved up and down slope, resulting in an elevation distribution split within a range of approximately 390-540 m and slope steepness up to 15 degrees. In the final phase the azimuth distribution of damaged stands became even. The correlation between the initial phase and topographic features can be used to prioritize monitoring forest areas most vulnerable to destruction by pests.

Kharuk, Viatcheslav I.↗
DOE OSTI2020

High-resolution mapping of spatial heterogeneity in ice wedge polygon geomorphology near Prudhoe Bay, Alaska

It is well known that microtopography associated with ice wedge polygons drives pronounced, meter-scale spatial gradients in hydrologic and ecological processes on the tundra. However, highresolution maps of polygonal geomorphology are rarely available, due to the complexity and subtlety of ice wedge polygon relief at landscape scales. Here we present a sub-meter resolution map of >106 discrete ice wedge polygons across a ~1200 km2 landscape, delineated within a lidar-derived digital elevation model. The delineation procedure relies on a convolutional neural network paired with a set of common image processing operations and permits explicit measurement of relative elevation at the center of each ice wedge polygon. The resulting map visualizes meter- to kilometer-scale spatial gradients in polygonal geomorphology across an extensive landscape with unprecedented detail. This high-resolution inventory of polygonal geomorphology provides rich spatial context for extrapolating observations of environmental processes across the landscape. The map also represents an extensive baseline dataset for quantifying contemporary land surface deformation (i.e., thermokarst) at the survey area, through future topographic surveys.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

VandeVen, C.↗
NASA NTRS2007

Lunar South Pole Illumination: Review, Reassessment, and Power System Implications

This paper reviews past analyses and research related to lunar south pole illumination and presents results of independent illumination analyses using an analytical tool and a radar digital elevation model. The analysis tool enables assessment at most locations near the lunar poles for any time and any year. Average illumination fraction, energy storage duration, solar/horizon terrain elevation profiles and illumination fraction profiles are presented for various highly illuminated sites which have been identified for manned or unmanned operations. The format of the data can be used by power system designers to develop mass optimized solar and energy storage systems. Data are presented for the worse case lunar day (a critical power planning bottleneck) as well as three lunar days during lunar south pole winter. The main site under consideration by present lunar mission planners (on the Crater Shackleton rim) is shown to have, for the worse case lunar day, a 0.71 average illumination fraction and 73 to 117 hours required for energy storage (depending on power system type). Linking other sites and including towers at either site are shown to not completely eliminate the need for energy storage.

Fincannon, James↗
DOE OSTI2026

High-resolution mountain topography can inform global snow vulnerability estimates

Snow is changing globally. Computationally intensive snow reanalysis products and downscaled climate model projections allow for the estimation of historical and projected changes in snow over ∼4–10 km resolutions, but these resolutions are coarse relative to the scales needed for water supply and flood planning. Fine-scale digital elevation models (DEMs) are widely available but are underutilized to make first-order assessments of snow vulnerability. Here, we leverage DEMs at a 7.5 arc s (∼250 m) resolution, combining these with historical freezing level height estimates from ERA-5 to derive estimates of changes in the snow-receiving area (SRA) and its variability across global mountain ranges. Results show estimated SRA declines in 29% (1.9 million km2) of the global mountain area from 1982–2020; 66% of the mountainous areas had no change over the historical period. At +1.5 °C of warming relative to the pre-industrial control, global mountain SRA would decline by 9.5% (1.0 million km2) relative to recent conditions. This loss would be approximately doubled with +2 °C of warming. In a +4 °C warming scenario, an additional 34% (3.6 million km2) of SRA would be lost beyond the +2 °C case. Across individual mountain ranges, SRA losses can occur nonlinearly with warming, with some locations that have historically had relatively minor SRA losses at risk of substantially larger losses in warmer climates. Analysis using coarser-resolution DEMs can underestimate or overestimate SRA and its rate of loss, with the largest impacts in relatively warm, low-elevation mountain ranges. Results of this work provide estimates of projected loss in SRA at policy-relevant warming levels; inform the resolutions needed for process-based snow modeling; identify snow vulnerability hotspots; and provide a new integrated approach to snow vulnerability assessment that is achievable at global scales and highlights potential nonlinearities from recent trends to a variety of future warming scenarios.

climate, mountains↗
DOE OSTI2025

Applying Transfer Learning for Street-Scale Nuisance Flood Forecasting in Coastal-Urban Cities

An important challenge with Machine Learning (ML) is its transferability; that is, whether a ML model trained on one set of data can be applied to a second set of data without requiring a full re-training of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether a ML model trained on data collected for one set of streets can effectively forecast flooding for another set of streets in the same city using TL. The envisioned use case is a city deploying a new flood depth monitoring sensor on a street and using TL to apply a ML model, trained on sensor data from an existing flood depth sensor network, to this new street. Eventually, the new flood depth sensor will have a sufficient dataset for training its own ML model, but TL can be used to fill the gap in time while this new dataset is being generated. This method is explored using a Long Short-Term Memory (LSTM) model trained on data for the flood-prone streets of Norfolk City, Virginia. The data used for training includes environmental time series (rainfall, tide), topographic features (Digital Elevation Model (DEM), Topographic Wetness Index (TWI), Depth To Water (DTW)), and street-scale flood depth time series obtained from a high-fidelity physics-based model, acting as a synthetic street-scale stream depth sensor dataset since actual stream depth sensor data is generally unavailable for most cities. A set of 180 flood-prone streets was used to train a base model, while another set of 180 flood-prone streets was used to re-train that model using different TL strategies. The results show that full-weight re-training proved most effective and minimal re-training of only the output layer was insufficient. The advantage of TL was most pronounced when target data was limited, meaning data collected at the new water depth sensor location included generally less than 18 flood events. As target data increased beyond 18 flood events, the benefit of TL diminished relative to training a ML model directly on the local flood events. These findings can assist cities as they implement street-scale flood sensing systems to create accurate forecasts for new sensing locations that do not yet have sufficient data records to train a local ML model.

Roy, Binata [Univ. of Virginia, Charlottesville, V↗
NASA NTRS1980

Application of digital terrain data to quantify and reduce the topographic effect on LANDSAT data

Integration of LANDSAT multispectral scanner (MSS) data with 30 m U.S. Geological Survey (USGS) digital terrain data was undertaken to quantify and reduce the topographic effect on imagery of a forested mountain ridge test site in central Pennsylvania. High Sun angle imagery revealed variation of as much as 21 pixel values in data for slopes of different angles and aspects with uniform surface cover. Large topographic effects were apparent in MSS 4 and 5 was due to a combination of high absorption by the forest cover and the MSS quantization. Four methods for reducing the topographic effect were compared. Band ratioing of MSS 6/5 and MSS 7/5 did not eliminate the topographic effect because of the lack of variation in MSS 4 and 5 radiances. The three radiance models examined to reduce the topographic effect required integration of the digital terrain data. Two Lambertian models increased the variation in the LANDSAT radiances. The nonLambertian model considerably reduced (86 per cent) the topographic effect in the LANDSAT data. The study demonstrates that high quality digital terrain data, as provided by the USGS digital elevation model data, can be used to enhance the utility of multispectral satellite data.

Justice, C. O.↗
NASA NTRS1990

Flight mechanics applications for tethers in space: Cooperative Italian-US programs

Since the 1974 proposal by Giuseppe Colombo to fly a tethered subsatellite from the Shuttle Orbiter, the creative thinking of many scientists and engineers from Italy and U.S. has generated a broad range of potential tether applications in space. Many of these applications have promise for enabling innovative research and operational activities relating to flight mechanics in earth orbit and at suborbital altitudes. From a flight mechanics standpoint the most interesting of the currently proposed flight demonstrations are: the second Tethered Satellite System experiment which offers both the potential for aerothermodynamics and hypersonics research and for atmospheric science research; the Tethered Initiated Space Recovery System which would enable orbital deboost and recovery of a re-entry vehicle and waste removal from a space station; and the Tether Elevator/Crawler System which would provide a variable microgravity environment and space station center of mass management. The outer atmospheric and orbital flight mechanics characteristics of these proposed tether flight demonstrations are described. The second Tethered Satellite System mission will deploy the tethered satellite earthward and will bring it as low as 130 km from ground and thus into the transition region between the atmosphere (non-ionized) and the partially ionized ionosphere. The atmospheric flight mechanics of the tethered satellite is discussed and simulation results are presented. The Tether Initiated Space Recovery System experiment will demonstrate the ability of a simple tether system to deboost and recover a reentry vehicle. The main feature of this demonstration is the utilization of a Small Expendable Deployment System (SEDS) and the low-tension deployment assumed to separate the reentry vehicle from the Shuttle. This low-tension deployment maneuver is discussed and its criticalities are outlined. The Tether Elevator/Crawler System is a new space element able to move in a controlled way between the ends of a deployed tethered system. A Shuttle test of an Elevator model is planned to demonstrate the unique capability of this element as a microgravity facility and to test the transfer motion control. The basic dynamical features of the Elevator system are presented and a preliminary assessment of the Elevator-induced tether vibrations is discussed.

Bevilacqua, Franco↗
NASA NTRS2009

Elevation Change of Drangajokull, Iceland, from Cloud-Cleared ICESat Repeat Profiles and GPS Ground-Survey Data

Located on the Vestfirdir Northwest Fjords), DrangaJokull is the northernmost ice map in Iceland. Currently, the ice cap exceeds 900 m in elevation and covered an area of approx.l46 sq km in August 2004. It was about 204 sq km in area during 1913-1914 and so has lost mass during the 20th century. Drangajokull's size and accessibility for GPS surveys as well as the availability of repeat satellite altimetry profiles since late 2003 make it a good subject for change-detection analysis. The ice cap was surveyed by four GPS-equipped snowmobiles on 19-20 April 2005 and has been profiled in two places by Ice, Cloud. and land Elevation Satellite (ICESat) 'repeat tracks,' fifteen times from late to early 2009. In addition, traditional mass-balance measurements have been taken seasonally at a number of locations across the ice cap and they show positive net mass balances in 2004/2005 through 2006/2007. Mean elevation differences between the temporally-closest ICESat profiles and the GPS-derived digital-elevation model (DEM)(ICESat - DEM) are about 1.1 m but have standard deviations of 3 to 4 m. Differencing all ICESat repeats from the DEM shows that the overall elevation difference trend since 2003 is negative with losses of as much as 1.5 m/a from same season to same season (and similar elevation) data subsets. However, the mass balance assessments by traditional stake re-measurement methods suggest that the elevation changes where ICESat tracks 0046 and 0307 cross Drangajokull are not representative of the whole ice cap. Specifically, the area has experienced positive mass balance years during the time frame when ICESat data indicates substantial losses. This analysis suggests that ICESat-derived elevations may be used for multi-year change detection relative to other data but suggests that large uncertainties remain. These uncertainties may be due to geolocation uncertainty on steep slopes and continuing cloud cover that limits temporal and spatial coverage across the area.

Shuman, Christopher A.↗
NASA NTRS1991

Integration of SAR and DEM data: Geometrical considerations

General principles for integrating data from different sources are derived from the experience of registration of SAR images with digital elevation models (DEM) data. The integration consists of establishing geometrical relations between the data sets that allow us to accumulate information from both data sets for any given object point (e.g., elevation, slope, backscatter of ground cover, etc.). Since the geometries of the two data are completely different they cannot be compared on a pixel by pixel basis. The presented approach detects instances of higher level features in both data sets independently and performs the matching at the high level. Besides the efficiency of this general strategy it further allows the integration of additional knowledge sources: world knowledge and sensor characteristics are also useful sources of information. The SAR features layover and shadow can be detected easily in SAR images. An analytical method to find such regions also in a DEM needs in addition the parameters of the flight path of the SAR sensor and the range projection model. The generation of the SAR layover and shadow maps is summarized and new extensions to this method are proposed.

Kropatsch, Walter G.↗
NASA NTRS1992

The topographic distribution of annual incoming solar radiation in the Rio Grande River basin

We model the annual incoming solar radiation topoclimatology for the Rio Grande River basin in Colorado, U.S.A. Hourly pyranometer measurements are combined with satellite reflectance data and 30-m digital elevation models within a topographic solar radiation algorithm. Our results show that there is large spatial variability within the basin, even at an annual integration length, but the annual, basin-wide mean is close to that measured by the pyranometers. The variance within 16 sq km and 100 sq km regions is a linear function of the average slope in the region, suggesting a possible parameterization for sub-grid-cell variability.

Dubayah, R.↗
DOE OSTI2023

Reducing impacts of artificial ponding in modeling salt marshes using a conductivity-formulated subgrid model

The landforms of salt marsh systems are rather complex, with meandering channel networks cutting through low-lying, extensive marsh platforms. Some small-scale topographic details are critical to flooding and draining processes but cannot be reflected in the Digital Elevation Model (DEM) due to limited measurement resolution and vegetation bias. Numerical models need a grid with high enough resolution to capture the small-scale connectivity to correctly model the small-scale flow processes, making the model computationally unaffordable. Here, in this study, we derived a subgrid model, which couples two flow components, one is the regular subgrid model for simulating the subgrid-resolved flows, and the other is a conductivity-formulated porous flow model for modeling small-scale gut flows unresolved at the subgrid level. The model validation was performed using an idealized case with a narrow slot that was unresolved in the coupled flow model. Model results were compared with a slot-resolved regular subgrid model where only surface flows are solved and suggested that, with a proper model parameterization, the coupled flow model is capable of reproducing flooding and draining processes similar to the slot-resolved subgrid model of surface flow. The model was applied to simulating flooding and draining processes in a meso-tidal salt marsh. The model results demonstrate that the coupled subgrid model can be used to reduce the impacts of artificial ponding that usually occur in numerical simulations of salt marshes with numerous narrow gullies and creeks.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Elevation change (2000-2004) on the Malaspina Glacier, Alaska

The glaciers of the southeastern Alaska coastal region are the largest temperate glacier meltwater source on Earth and may contribute one third of the total glacier meltwater entering the global ocean. Since melt onset and refreeeze timing in this region show a tendency toward earlier onset and longer ablation seasons, accelerated glacier wastage may be occurring. In this study we focus on one of the largest temperate glacier systems on Earth, the Malaspina Glacier. This glacier, with a length of approximately 110 km and an area of approximately square 5,000 km, has the largest piedmont lobe of any temperate glacier. The entire lobe, which lies at elevations below 600 m, is within the ablation zone. We report and interpret ice elevation change between a digital elevation model (DEM) derived from the Shuttle Radar Topography Mission (SRTM C band) observations in Feb. 2000 and ICESat Laser 1-3 observations between Feb. 2003 and Nov. 2004. We use these elevation change results, along with earlier studies, to address the spatial and temporal variability in wastage of the piedmont lobe. Between 2000 and 2004 ice elevation changes of 10-30 meters occurred across the central Malaspina piedmont lobe. From 1972/73 (USGS DEM) to 1999 (SRTM corrected for estimated winter snow accumulation) Malaspina's (Agassiz, Seward Lobe, and Marvine) mean ice thinning was estimated at -47 m with maximum thinning on parts of the lobes to -160 m. The Malaspina's accumulation area is only slightly larger than its ablation area (2,575 km2 vs. 2,433 km2); unfortunately few glaciological observations are available from this source region. Snow accumulation rates have been largely inferred from low-altitude precipitation and temperature data. Comparing sequential ICESat observations in the Malaspina source region, we estimated short-term elevation increases of up to 5 meters during the winter of 2003/04.

Sauber, J.↗
NASA NTRS1985

A comparative study of spherical and flat-Earth geopotential modeling at satellite elevations

Flat-Earth and spherical-Earth geopotential modeling of crustal anomaly sources at satellite elevations are compared by computing gravity and scalar magnetic anomalies perpendicular to the strike of variably dimensioned rectangular prisms at altitudes of 150, 300, and 450 km. Results indicate that the error caused by the flat-Earth approximation is less than 10% in most geometric conditions. Generally, error increase with larger and wider anomaly sources at higher altitudes. For most crustal source modeling applications at conventional satellite altitudes, flat-Earth modeling can be justified and is numerically efficient.

Parrott, M. H.↗
NASA NTRS2022

Assessment of ICESat-2’s Horizontal Accuracy Using Precisely Surveyed Terrains in McMurdo Dry Valleys, Antarctica

This article presents an assessment of the horizontal accuracy and precision of the laser altimetry observations collected by NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission. We selected the terrain-matching method to determine the position of laser altimeter profiles within a precisely known surface, represented by a digital elevation model (DEM). We took this classical approach a step further, approximated the DEM by planar surfaces, and calculated the optimal position of the laser profile by minimizing the square sum of the elevation differences between reference DEMs and ICESat-2 profiles. We found the highly accurate DEMs of the McMurdo Dry Valleys (DV), Antarctica, ideal for this research because of their stable landscape and rugged topography. We computed the 3-D shift parameters of 379 different laser altimeter profiles along two reference ground tracks collected within the first two years of the mission. Analyzing these results revealed a total geolocation error (mean +1 σ ) of 4.93 m for version 3 and 4.66 m for version 4 data. These numbers are the averages of the six beams, expressed as mean +1 σ and lie well within the mission requirement of 6.5 m.

calibration↗
NASA NTRS2006

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm-surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm-surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm-surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and, most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite-element-based codes. It affords a capability for simulating tidal circulation and storm-surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm-surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

Valenti, Elizabeth↗