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At least 127 records · Page 7

Orthographic Stereo Correlator on the Terrain Model for Apollo Metric Images

A stereo correlation method on the object domain is proposed to generate the accurate and dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce high-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. Given camera parameters of an image pair from bundle adjustment in ASP, a correlation window is defined on the terrain with the predefined surface normal of a post rather than image domain. The squared error of back-projected images on the local terrain is minimized with respect to the post elevation. This single dimensional optimization is solved efficiently and improves the accuracy of the elevation estimate.

Terrain Model↗

Airborne Lidar-Based Estimates of Tropical Forest Structure in Complex Terrain: Opportunities and Trade-Offs for REDD+

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. Results: We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (approx. 20 returns/sq m) data was highly accurate (mean signed error of 0.19 +/-0.97 m), while those derived from reduced-density datasets (8/sq m, 4/sq m, 2/sq m and 1/sq m) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4/sq m, the bias in height estimates translated into errors of 80-125 Mg/ha in predicted aboveground biomass. Conclusions: Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Airborne lidar↗

Lunar Terrain Mapping Using 3D Software and Modeling Techniques for the Glenn Research Center Communication Analysis Suite

As NASA prepares to return humans to the Moon as part of upcoming Artemis missions, engineers must examine the surface features and safety of lunar terrain at various locations. The Glenn Research Center Communication Analysis Suite (GCAS) includes visualization tools developed to aid scientists in this quest to comprehend lunar terrain data, as well as spatial communication information. Visual information and understanding will be highly useful to engineers as they use the GCAS to compare the topography of regions of interest for the Artemis III and future space travel missions. Not only can three-dimensional (3D) visualization display the intricacies of the lunar terrain, but it can also demonstrate relationships such as the presence or absence of communication links between Earth ground stations, lunar crew members, and rovers, and the presence of shadows on the lunar surface. In the future, the GCAS has the potential to support the planning of other space exploration missions as well. The emerging possibility of incorporating more planetary bodies becomes especially important as NASA plans not only to return to the Moon but to press onward to Mars.

Visualization↗

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust, appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Vehicle Radiator↗

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust, appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Thermal Analysis↗

High Resolution Terrain Sensing Lidar for Precision Navigation and Safe Landing of Space and Aerial Vehicles

A 3-D imaging flash lidar sensor employing a resolution enhancement algorithm is being developed at NASA Langley Research Center for providing Terrain Relative Navigation and Hazard Avoidance capabilities onboard spacecraft landing on the Moon, Mars, and other planetary bodies. This lidar sensor, we refer to as Terrain Sensing Lidar (TSL), is a solution for future missions that require landing at pre-designated sites near high value resources or at areas of high scientific value, while avoiding hazardous terrain features, such as escarpments, craters, slopes, and rocks, or pre-deployed assets. TSL can also benefit terrestrial applications such as autonomous aerial vehicles without reliance on signals from Global Positioning System (GPS). The feasibility of the TSL concept has been shown through a series of drone, fixed-wing aircraft, and helicopter flight tests. A prototype version of the TSL has been recently assembled for conducting another set of flight tests to demonstrate its readiness for upcoming landing missions. This paper describes the TSL, provides its performance parameters, and explains its operational concepts for landing missions.

Precision Navigation↗

Editorial: Resolving atmospheric flow in complex environments: recent experiments in terrain and forest canopies

The characterization of atmospheric flows in complex environments, which may include steep terrain slopes and heterogeneous vegetation and/or forest cover, is a long-standing challenge in boundary-layer meteorology. Atmospheric observations are complicated by the presence of transient, terrain-induced flow features, forest-canopy-atmosphere interactions, and atmospheric stability effects, not to mention the logistical hurdles involved with instrument deployment, data analysis, and quality control. Furthermore, challenges in atmospheric modeling arise due to numerical errors associated with complex terrain flows, as well as reliance on simplified parameterizations for unresolved processes such as turbulent mixing and land-surface or forest-canopy-atmosphere interactions. These modeling challenges are exacerbated in the so-called “gray zone,” wherein features of interest have length scales that are similar to the model grid spacing, or when the principal flow layer is smaller than the grid spacing (e.g., slope flows).

54 ENVIRONMENTAL SCIENCES↗

Geologic terrain mapping from earth-satellite and ultra-high aerial photographs

A proposal is made for mapping from aerial photographs from the EROS program. Three kinds of maps (geomorphic or landform, soil, and surficial deposit) are being prepared at 1:250,000 scale for an 8000-square-mile area between Tucson and Ajo, Arizona. Nine cameras used on NASA mission 101 provided color, color infrared, and multispectral air photos from about 60,000 feet above the terrain and with photo scales ranging from 1:60,000 to 1:240,000. This area was selected because it provides a good sample of desert terrain and is suited for improving and testing the photointerpretive techniques for mapping geologic terrain features with small-scale photos.

Morrison, R. B.↗

Automatic Computer Mapping of Terrain

Computer processing of 17 wavelength bands of visible, reflective infrared, and thermal infrared scanner spectrometer data, and of three wavelength bands derived from color aerial film has resulted in successful automatic computer mapping of eight or more terrain classes in a Yellowstone National Park test site. The tests involved: (1) supervised and non-supervised computer programs; (2) special preprocessing of the scanner data to reduce computer processing time and cost, and improve the accuracy; and (3) studies of the effectiveness of the proposed Earth Resources Technology Satellite (ERTS) data channels in the automatic mapping of the same terrain, based on simulations, using the same set of scanner data. The following terrain classes have been mapped with greater than 80 percent accuracy in a 12-square-mile area with 1,800 feet of relief; (1) bedrock exposures, (2) vegetated rock rubble, (3) talus, (4) glacial kame meadow, (5) glacial till meadow, (6) forest, (7) bog, and (8) water. In addition, shadows of clouds and cliffs are depicted, but were greatly reduced by using preprocessing techniques.

Smedes, H. W.↗

Terrain classification maps of Yellowstone National Park

A cooperative ERTS-1 investigation involving U. S. Geological Survey, National Park Service, and Environmental Research Institure of Michigan (ERIM) personnel has as its goal the preparation of terrain classification maps for the entire Yellowstone National Park. Excellent coverage of the park was obtained on 6 August 1972 (frame 1015-17404). Preliminary terrain classification maps have been prepared at ERIM by applying multispectral pattern recognition techniques to ERTS-MSS digital taped data. The color coded terrain maps are presented and discussed. The discussion includes qualitative and quantitative accuracy estimates and discussion of processing techniques.

Thomson, F. J.↗

Parameter estimation for terrain modeling from gradient data

This paper developes a method for mathematically modeling terrain surfaces for use on an unmanned Martian vehicle. The data collected by the vehicle consists of terrain height and two directional slopes at each data point. The parameters for the mathematical terrain model are stochastically determined by using least square approximations.-

Shen, C. N.↗

Relationships between vegetation and terrain variables in southeastern Arizona

The author has identified the following significant results. Relationships were established between eight terrain variables and plant species and 31 vegetation types. Certain plant species are better than others for differentiating or discriminating groups of specified terrain variables. Certain terrain variables are better than others for differentiating or discriminating groups of vegetation types. Stepwise discriminant analysis was shown to be a useful tool in plant ecological studies.

Mouat, D. A.↗

A stochastic analysis of terrain evaluation variables for path selection

A stochastic analysis was performed on the variables associated with the characteristics of the terrain encountered by a roving system with an autonomous navigation system. A laser rangefinder is employed to detect terrain features at ranges up to 75 m. Analytic expressions and a numerical scheme were developed to calculate the variance of data on these four variables: (1) body clearance, (2) in-path slope, (3) tilt slope, and (4) wheel deviation. The variance is due to noise in the range data. It was found that the standard deviation of these terrain variables is large enough to warrant the use of a safety margin to aid the roving vehicle in avoiding high risk areas.

Donohue, J. G.↗

A study of GEOS-3 terrain data with emphasis on radar cross section

Radar cross sections (RCS) of terrain are studied using GEOS 3 radar altimeter data. Maps of RCS for portions of four east coast states (U.S.A.) are presented and used to draw curves of RCS versus inland distance as measured from the land/sea interface. The results show RCS to decay approximately exponentially with inland distance. The GEOS 3 data are also used to develop curves of RCS seasonal variation for the same regions. Observed variations correlate strongly with local potential evaporation. Results also show that farming operations in the state of North Carolina are observable in the RCS data. A restricted method for determining surface roughness features from saturated average return waveforms for some types of terrain is developed. Sensor bias induced by receiver saturation for certain terrain returns is briefly discussed.

Priester, R. W.↗

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.↗

Terrain profiling from Seasat altimetry

To determine their applicability for terrain profiling, Seasat altimeter measurements were analyzed for the following geographic areas: (1) Andean salars of southern Bolivia; (2) Alaska; (3) south-central Arizona; (4) imperial Valley of California; (5) Yuma Valley of Arizona; and (6) Great Salt Lake Desert. Analysis of the data over all of these geographic areas shows that the satellite altimeter servo did not respond quickly enough to changing terrain features. However, it is demonstrated that retracking of the archived surface return waveforms yields surface elevations over smooth terrain accurate to + or - 1 m when correlated with large scale maps. The retracking algorithm used and its verification over the salars of southern Bolivia are described. Results are presented for each of the six geographic areas.

Brooks, R. L.↗

Analysis of geologic terrain models for determination of optimum SAR sensor configuration and optimum information extraction for exploration of global non-renewable resources. Pilot study: Arkansas Remote Sensing Laboratory, part 1, part 2, and part 3

Computer-generated radar simulations and mathematical geologic terrain models were used to establish the optimum radar sensor operating parameters for geologic research. An initial set of mathematical geologic terrain models was created for three basic landforms and families of simulated radar images were prepared from these models for numerous interacting sensor, platform, and terrain variables. The tradeoffs between the various sensor parameters and the quantity and quality of the extractable geologic data were investigated as well as the development of automated techniques of digital SAR image analysis. Initial work on a texture analysis of SEASAT SAR imagery is reported. Computer-generated radar simulations are shown for combinations of two geologic models and three SAR angles of incidence.

Kaupp, V. H.↗

Automated basin delineation from digital terrain data

While digital terrain grids are now in wide use, accurate delineation of drainage basins from these data is difficult to efficiently automate. A recursive order N solution to this problem is presented. The algorithm is fast because no point in the basin is checked more than once, and no points outside the basin are considered. Two applications for terrain analysis and one for remote sensing are given to illustrate the method, on a basin with high relief in the Sierra Nevada. This technique for automated basin delineation will enhance the utility of digital terrain analysis for hydrologic modeling and remote sensing.

Marks, D.↗