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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Martian particle size based on thermal inertia corrected for elevation-dependent atmospheric properties

Thermal inertia is commonly used to derive physical properties of the Martian surface. If the surface is composed of loosely consolidated grains, then the thermal conductivity derived from the inertia can theoretically be used to compute the particle size. However, one persistent difficulty associated with the interpretation of thermal inertia and the derivation of particle size from it has been the degree to which atmospheric properties affect both the radiation balance at the surface and the gas conductivity. These factors vary with atmospheric pressure so that derived thermal inertias and particle sizes are a function of elevation. By utilizing currently available thermal models and laboratory information, a fine component thermal inertia map was convolved with digital topography to produce particle size maps of the Martian surface corrected for these elevation-dependent effects. Such an approach is especially applicable for the highest elevations on Mars, where atmospheric back radiation and gas conductivity are low.

Bridges, N. T.↗
NASA NTRS2015

High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem

Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.

HRSI↗
NASA NTRS2007

Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences.

Adler, Robert↗
NASA NTRS2007

Application of Multi-Satellite Precipitation Analysis to Floods and Landslides

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences. However, difficulties in comparing landslide event information (mostly from news reports) with the satellite-based forecasts are analyzed.

Adler, Robert↗
NASA NTRS1991

Generation of topographic terrain models utilizing synthetic aperture radar and surface level data

Topographical terrain models are generated by digitally delineating the boundary of the region under investigation from the data obtained from an airborne synthetic aperture radar image and surface elevation data concurrently acquired either from an airborne instrument or at ground level. A set of coregistered boundary maps thus generated are then digitally combined in three dimensional space with the acquired surface elevation data by means of image processing software stored in a digital computer. The method is particularly applicable for generating terrain models of flooded regions covered entirely or in part by foliage.

Imhoff, Marc L.↗
NASA NTRS1979

Error detection and rectification in digital terrain models

Digital terrain models produced by computer correlation of stereo images are likely to contain occasional gross errors in terrain elevation. These errors typically result from having mismatched sub-areas of the two images, a problem which can occur for a variety of image- and terrain-related reasons. Such elevation errors produce undesirable effects when the models are further processed, and should be detected and corrected as early in the processing as possible. Algorithms have been developed to detect and correct errors in digital terrain models. These algorithms focus on the use of constraints on both the allowable slope and the allowable change in slope in local areas around each point. Relaxation-like techniques are employed in the iteration of the detection and correction phases to obtain best results.

Hannah, M. J.↗
NASA NTRS1998

Application of the Shuttle Laser Altimeter in an Accuracy Assessment of Global 1-Kilometer Digital Elevation Data

Shuttle Laser Altimeter (SLA) data have been used to evaluate the accuracy of GTOPO30, the first comprehensive, 1 km resolution, global topographic data set. GTOPO30 was developed by the USGS Eros Data Center (EDC), in part, to address NASA's needs for a global topographic model in support of remote sensing instruments aboard the Earth Observing System AM-1 spacecraft. SLA flew as a part of the STS-72 mission in January, 1996 observing the latitude band from +/- 28.5 deg, and on STS-85 in August, 1997 extending the observations to +/- 57 deg. Combining the SLA ranging data with shuttle position and pointing knowledge yields surface elevation data of very high vertical accuracy in an Earth-centered, absolute reference frame (2.8 m rms difference for SLA-01 with respect to ocean reference surface). Use of the well-determined mean sea surface reference for calibration allows propagation of high accuracy altimetry onto the continents. 436,635 SLA-01 land elevations were compared to the GTOPO30 grid after conversion to a mean sea level vertical datum using the Earth Geoid Model 96, jointly developed by Goddard and NIMA. The comparison reveals systematic elevation biases in southern Asia, Africa, Australia, and south America on the order 10's to 100 meters in the GTOPO30 compilation on spatial scales of 100's to 1000's of kilometers. These biases are likely due to vertical datum errors in the topographic source materials used to compile GTOPO30, which primarily consist of Defense Mapping Agency (DMA) digital elevation and topographic map products. These biases imply that elevation corrections applied to land gravity measurements using these DMA source materials will be biased, leading to errors in geoid models incorporating these land gravity data.

Harding, David J.↗
NASA NTRS1991

Monitoring global snow cover

A snow model that supports the daily, operational analysis of global snow depth and age has been developed. It provides improved spatial interpolation of surface reports by incorporating digital elevation data, and by the application of regionalized variables (kriging) through the use of a global snow depth climatology. Where surface observations are inadequate, the model applies satellite remote sensing. Techniques for extrapolation into data-void mountain areas and a procedure to compute snow melt are also contained in the model.

Armstrong, Richard↗
NASA NTRS2007

An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM, topography-derived hydrologic parameters such as flood direction. flow accumulation, basin, and river network etc.; 3) spatially distributed hydrological models to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay thc input data to the models and display the flood inundation results to the users and decision-makers. Early results appear reasonable in terms of location and frequency of events. Case studies of this experimental system are evaluated with surface runoff data and other river monitoring systems. such as Dartmouth Flood Observatory's "Surface Water Watch" array of river reaches that are measured daily via other satellite remote sensing data. A major outcome of this progress will be the availability of a global overview of flood alerts that should consequently improve the performance of Decision Support System. We expect these developments in utilization of satellite remote sensing technology to offer a practical solution to the challenge of building a cost-effective early warning system for data scarce and under-developed areas.

Adler, Robert↗
NASA NTRS1981

Analysis of GOES imagery and digitized data for the SEV-UPS period, August 1979

In support of the Southeastern Virginia Urban Plume Study (SEV-UPS), GOES satellite imagery was analyzed for the month of August 1979. The analyzed GOES images provide an additional source of meteorological input useful in the evaluation of air quality data collected during the month long period of the SEV-UPS experiment. In addition to the imagery analysis, GOES digitized data were analyzed for the period of August 6 to 11, during which a regional haze pattern was detectable in the imagery. The results of the study indicate that the observed haze patterns correspond closely with areas shown in surface based measurements to have reduced visibilities and elevated pollution levels. Moreover, the results of the analysis of digitized data indicate that digital reflectance counts can be directly related to haze intensity both over land and ocean. The model results agree closely with the observed GOES digital reflectance counts, providing further indication that satellite remote sensing can be a useful tool for monitoring regional elevated pollution episodes.

Bowley, C. J.↗
NASA NTRS2017

Crater Morphometry and Crater Degradation on Mercury: Mercury Laser Altimeter (MLA) Measurements and Comparison to Stereo-DTM Derived Results

Two types of measurements of Mercury's surface topography were obtained by the MESSENGER (MErcury Surface Space ENvironment, GEochemisty and Ranging) spacecraft: laser ranging data from Mercury Laser Altimeter (MLA) [1], and stereo imagery from the Mercury Dual Imaging System (MDIS) camera [e.g., 2, 3]. MLA data provide precise and accurate elevation meaurements, but with sparse spatial sampling except at the highest northern latitudes. Digital terrain models (DTMs) from MDIS have superior resolution but with less vertical accuracy, limited approximately to the pixel resolution of the original images (in the case of [3], 15-75 m). Last year [4], we reported topographic measurements of craters in the D=2.5 to 5 km diameter range from stereo images and suggested that craters on Mercury degrade more quickly than on the Moon (by a factor of up to approximately 10×). However, we listed several alternative explanations for this finding, including the hypothesis that the lower depth/diameter ratios we observe might be a result of the resolution and accuracy of the stereo DTMs. Thus, additional measurements were undertaken using MLA data to examine the morphometry of craters in this diameter range and assess whether the faster crater degradation rates proposed to occur on Mercury is robust.

morphometry↗
NASA NTRS1981

Application of HCMM data to regional geologic analysis for mineral and energy resource evaluation

The effects of topographic elevation and slope on thermal images were examined using representative field obstructions of the solar and sky radiation and a simple linearized thermal model. The forms are easily adapted for analysis of HCMM images using the DMA digital terrain data. From a representative set of field observations, it was found that flux variations with elevation can cause changes in the mean diurnal temperature gradient from -4 deg to -14 deg per km evaluated at 2000 m. Changes in the temperature difference gradient of 1 to 2 C per km are also produced which is equivalent to an effective thermal inertia gradient of 100 W s to the 1/2 power/sq m K/1 per km. Exposed bedrock on topographic ridges will appear to have a lower thermal inertia due to the additional effect.

Watson, K.↗
NASA NTRS2011

Large Terrain Modeling and Visualization for Planets

Physics-based simulations are actively used in the design, testing, and operations phases of surface and near-surface planetary space missions. One of the challenges in realtime simulations is the ability to handle large multi-resolution terrain data sets within models as well as for visualization. In this paper, we describe special techniques that we have developed for visualization, paging, and data storage for dealing with these large data sets. The visualization technique uses a real-time GPU-based continuous level-of-detail technique that delivers multiple frames a second performance even for planetary scale terrain model sizes.

digital elevation map↗
NASA NTRS1979

Remote sensing of snow and ice

This paper reviews remote sensing of snow and ice, techniques for improved monitoring, and incorporation of the new data into forecasting and management systems. The snowcover interpretation of visible and infrared data from satellites, automated digital methods, radiative transfer modeling to calculate the solar reflectance of snow, and models using snowcover input data and elevation zones for calculating snowmelt are discussed. The use of visible and near infrared techniques for inferring snow properties, microwave monitoring of snowpack characteristics, use of Landsat images for collecting glacier data, monitoring of river ice with visible imagery from NOAA satellites, use of sequential imagery for tracking ice flow movement, and microwave studies of sea ice are described. Applications of snow and ice research to commercial use are examined, and it is concluded that a major problem to be solved is characterization of snow and ice in nature, since assigning of the correct properties to a real system to be modeled has been difficult.

Rango, A.↗
NASA NTRS2019

Planetary Rover Simulation for Lunar Exploration Missions

When planning planetary rover missions it is useful to develop intuition and skills driving in, quite literally, alien environments before incurring the cost of reaching said locales. Simulators make it possible to operate in environments that have the physical characteristics of target locations without the expense and overhead of extensive physical tests. To that end, NASA Ames and Open Robotics collaborated on a Lunar rover driving simulator based on the open source Gazebo simulation platform and leveraging ROS (Robotic Operating System) components. The simulator was integrated with research and mission software for rover driving, system monitoring, and science instrument simulation to constitute an end-to-end Lunar mission simulation capability. Although we expect our simulator to be applicable to arbitrary Lunar regions, we designed to a reference mission of prospecting in polar regions. The harsh lighting and low illumination angles at the Lunar poles combine with the unique reflectance properties of Lunar regolith to present a challenging visual environment for both human and computer perception. Our simulator placed an emphasis on high fidelity visual simulation in order to produce synthetic imagery suitable for evaluating human rover drivers with navigation tasks, as well as providing test data for computer vision software development.In this paper, we describe the software used to construct the simulated Lunar environment and the components of the driving simulation. Our synthetic terrain generation software artificially increases the resolution of Lunar digital elevation maps by fractal synthesis and inserts craters and rocks based on Lunar size-frequency distribution models. We describe the necessary enhancements to import large scale, high resolution terrains into Gazebo, as well as our approach to modeling the visual environment of the Lunar surface. An overview of the mission software system is provided, along with how ROS was used to emulate flight software components that had not been developed yet. Finally, we discuss the effect of using the high-fidelity synthetic Lunar images for visual odometry. We also characterize the wheel slip model, and find some inconsistencies in the produced wheel slip behaviour.

Allan, Mark↗
NASA NTRS1988

The derivation of sub-canopy surface terrain models of coastal forests using synthetic aperture radar

Radar data acquired by the Shuttle Imaging Radar-B mission covering a portion of the Mouths of the Ganges forests were used to create a terrain model for use in determining tidal flow and eventual nutrient transport from the forest to the marine habitat. Results show that good digital topographic terrain models of wet coastal forests can be generated using multiple sets of L-band SAR and ancillary tide elevation data. The dominance of the interaction phenomenon in the radar backscatter of flooded forests can be used to create sub-canopy inundation maps which when merged with tide surface data can be used to generate reasonable topographic models. Ideally models could be improved by using multiple sets of data at a constant incidence angle over the total tide range. The optimal angle for the SAR depends upon the characteristics of the forest. The range of 46 to 57 deg seems applicable to the 12.5 m tall closed canopy in this example. Such models can be an extremely valuable tool for studying and mapping the mangal ecosystem.

Imhoff, M. L.↗
NASA NTRS1992

High-resolution terrain map from multiple sensor data

The authors present 3-D vision techniques for incrementally building an accurate 3-D representation of rugged terrain using multiple sensors. They have developed the locus method to model the rugged terrain. The locus method exploits sensor geometry to efficiently build a terrain representation from multiple sensor data. The locus method is used to estimate the vehicle position in the digital elevation map (DEM) by matching a sequence of range images with the DEM. Experimental results from large-scale real and synthetic terrains demonstrate the feasibility and power of the 3-D mapping techniques for rugged terrain. In real world experiments, a composite terrain map was built by merging 125 real range images. Using synthetic range images, a composite map of 150 m was produced from 159 images. With the proposed system, mobile robots operating in rugged environments can build accurate terrain models from multiple sensor data.

Kweon, In S.↗
NASA NTRS1987

Digital cartography of the planets - New methods, its status, and its future

A system has been developed that establishes a standardized cartographic database for each of the 19 planets and major satellites that have been explored to date. Compilation of the databases involves both traditional and newly developed digital image processing and mosaicking techniques, including radiometric and geometric corrections of the images. Each database, or digital image model (DIM), is a digital mosaic of spacecraft images that have been radiometrically and geometrically corrected and photometrically modeled. During compilation, ancillary data files such as radiometric calibrations and refined photometric values for all camera lens and filter combinations and refined camera-orientation matrices for all images used in the mapping are produced. The system is designed to aid in the following: access to and utilization of spatial data returned by planetary spacecraft; coregistration of cartographic image and topographic elevation models with geological, geophysical, and geochemical databases; and the design and preparation of both standard and custom map products. A major goal of the project is to publish the DIMs on compact computer-compatible media such as digital-optical (CD-ROM) disks.

Batson, R. M.↗