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NASA NTRS2023

Shape from spectra

We introduce a new unified atmospheric–topographic correction approach that estimates surface geometry directly from the radiance measurement. Surface topography influences the at-sensor radiance measurement, making precise topography modeling critical in applications like vegetation or snow studies in mountainous terrain. Currently, elevation maps are used to derive topographic variables such as the slope and sky-view factor. This process is error-prone since static global digital elevation models do not generally achieve the accuracy required, and even minor mismatches in spatial resolution can introduce significant artifacts in downstream processing. Here we demonstrate that it is possible to estimate topographic parameters directly from spectral data, ensuring perfect physical consistency, temporal coincidence, and spatial alignment. We present experiments estimating topographic slope in two scenes in Southern California, with data from NASA’s Next Generation Airborne Visible/Near Infrared Imaging Spectrometer (AVIRIS-NG). We compared our radiance-based estimates against high-resolution lidar datasets. Our initial validation result showed a correlation of R 2 = 0.864 (n = 160) over the homogeneous surface of Beckman Auditorium’s cone-shaped roof on the Caltech campus in Pasadena, California. We then validate the model over a larger study site near Santa Clarita, California, finding R 2 = 0.923 (n = 40,000) in a 350 x 350m area. The accuracy of our model estimates, combined with its systematic advantages over the alternative, show the potential of the approach for use in both airborne campaigns and orbital missions.

Nimrod Carmon↗

NASA NTRS2009

Lunar Pole Illumination and Communications Maps Computed from GSSR Elevation Data

A Digital Elevation Model of the lunar south pole was produced using Goldstone Solar System RADAR (GSSR) data obtained in 2006.12 This model has 40-meter horizontal resolution and about 5-meter relative vertical accuracy. This Digital Elevation Model was used to compute average solar illumination and Earth visibility with 100 kilometers of the lunar south pole. The elevation data were converted into local terrain horizon masks, then converted into lunar-centric latitude and longitude coordinates. The horizon masks were compared to latitude, longitude regions bounding the maximum Sun and Earth motions relative to the moon. Estimates of Earth visibility were computed by integrating the area of the region bounding the Earth's motion that was below the horizon mask. Solar illumination and other metrics were computed similarly. Proposed lunar south pole base sites were examined in detail, with the best site showing yearly solar power availability of 92 percent and Direct-To-Earth (DTE) communication availability of about 50 percent. Similar analysis of the lunar south pole used an older GSSR Digital Elevation Model with 600-meter horizontal resolution. The paper also explores using a heliostat to reduce the photovoltaic power system mass and complexity.

lunar base↗

NASA NTRS1990

Geocoding and stereo display of tropical forest multisensor datasets

Concern about the future of tropical forests has led to a demand for geocoded multisensor databases that can be used to assess forest structure, deforestation, thermal response, evapotranspiration, and other parameters linked to climate change. In response to studies being conducted at the Braulino Carrillo National Park, Costa Rica, digital satellite and aircraft images recorded by Landsat TM, SPOT HRV, Thermal Infrared Multispectral Scanner, and Calibrated Airborne Multispectral Scanner sensors were placed in register using the Landsat TM image as the reference map. Despite problems caused by relief, multitemporal datasets, and geometric distortions in the aircraft images, registration was accomplished to within + or - 20 m (+ or - 1 data pixel). A digital elevation model constructed from a multisensor Landsat TM/SPOT stereopair proved useful for generating perspective views of the rugged, forested terrain.

Welch, R.↗

NASA NTRS1979

Forest Classification and Inventory System using Landsat, digital terrain, and ground sample data

Accurate timber inventory data for cost-effective forest management is the primary goal of a Forest Classification and Inventory System (FOCIS) designed to provide estimates of timber volume by species aggregated by compartments, townships, or other spatial management units. FOCIS uses Landsat spectral data, including a synthesized texture channel, and Forest Service ground sample data to produce timber volume-homogeneous classes through a two-step unsupervised clustering process. Registered digital terrain data, including derived slope angle and slope aspect channels, are used to predict species proportions through a trend surface model, again using ground sample data for model calibration. In the final stage of FOCIS, volume estimates and predicted species proportions are merged and aggregated to yield timber volumes by species within management areas.

Strahler, A. H.↗

NASA NTRS1984

Atmospheric model development

Spectral albedo measurements from the LANDSAT-4/5 thematic mappers require that spacecraft upwelling radiances be corrected for atmospheric absorption and scattering and for local surface illumination. A two-stream model is developed, with a lower boundary condition that varies with incidence angle. The TM data must be registered to digital terrain data. Reflectance from points in shadows can be used to estimate optical depth. The primary application is determination of the spectral albedo of snow. The TM is better-suited for this purpose than the MSS because of its larger dynamic range.

Source record↗

NASA NTRS2010

Robust Mosaicking of Stereo Digital Elevation Models from the Ames Stereo Pipeline

Robust estimation method is proposed to combine multiple observations and create consistent, accurate, dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce higher-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data than is currently possible. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. However, the DEMs currently produced by the ASP often contain errors and inconsistencies due to image noise, shadows, etc. The proposed method addresses this problem by making use of multiple observations and by considering their goodness of fit to improve both the accuracy and robustness of the estimate. The stepwise regression method is applied to estimate the relaxed weight of each observation.

Kim, Tae Min↗

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 NTRS1982

Forest management applications of Landsat data in a geographic information system

The utility of land-cover data resulting from Landsat MSS classification can be greatly enhanced by use in combination with ancillary data. A demonstration forest management applications data base was constructed for Santa Cruz County, California, to demonstrate geographic information system applications of classified Landsat data. The data base contained detailed soils, digital terrain, land ownership, jurisdictional boundaries, fire events, and generalized land-use data, all registered to a UTM grid base. Applications models were developed from problems typical of fire management and reforestation planning.

Maw, K. D.↗

NASA NTRS2022

Integrated Topographic Corrections Improve Forest Mapping Using Landsat Imagery

In mountainous environments, topography strongly affects the reflectance due to illumination effects and cast shadows, which introduce errors in land cover classifications. However, topographic correction is not routinely implemented in standard data pre-processing chains (e.g., Landsat Analysis Ready Data), and there is a lack of consensus whether topographic correction is necessary, and if so, how to conduct it. Furthermore, methods that correct simultaneously for atmospheric and topographic effects are becoming available, but they have not been compared directly. Our objects were to investigate (1) the effectiveness of two topographic correction approaches that integrate atmospheric and topographic correction, (2) improvements in classification accuracy when analyzing topographically corrected single-date imagery (14 July 2016 and 2 October 2016), versus a full Landsat time series from 2014 to 2016, and 3) improvements in classification accuracy when including additional terrain information (i.e., topographic slope, elevation, and aspect). We developed a physical based model and compared it with an enhanced C-correction, both of which integrate atmospheric and topographic correction. We compared classification accuracies with and without topographic correction using combinations of single-date imagery, image composites and spectral-temporal metrics generated from the full Landsat time series, and additional terrain information in the Caucasus Mountains. We found that both the enhanced C-correction and the physical model performed very well and largely eliminated the correlation (Pearson’s correlation coefficient r ranges from 0.06 to 0.24) between surface reflectance and illumination condition, but the physical model performed best (r ranges from 0.05 to 0.11). Both image composites, and spectral-temporal metrics generated from corrected imagery, resulted in significantly (p ≤ 0.05) higher classification accuracies and better forest classifications, especially for the mixed forests. Adding terrain information reduced classification error significantly, but not as much as topographic correction. In summary, topographic correction remains necessary, even when analyzing a full Landsat time series and including a digital elevation model in the classification. We recommend that topographic correction should be applied when analyzing Landsat satellite imagery in mountainous region for forest cover classification.

Atmospheric correction↗

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 NTRS1982

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.↗

NASA NTRS2011

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting system, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction System), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using Adams dynamic modeling software. The external library was built in Fortran and called by Adams to model the wheel-soil interactions include the rut-formation effect of deformable soils, lateral and longitudinal forces, bull-dozing effects, and applied wheel torque. The paper presents the details and implementation of the system. To validate the developed system, one study case is presented from a realistic drive on Mars of the Opportunity rover. The simulation results match well from the measurement of on-board telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.

rover↗

NASA NTRS1977

Full color hybrid display for aircraft simulators

A full spectrum color monitor, connected to the camera and lens system of a television camera supported by a gantry frame over a terrain model simulating an aircraft landing zone, projects the monitor image onto a lens or screen visually accessible to a trainee in the simulator. A digital computer produces a pattern corresponding to the lights associated with the landing strip onto a monochromatic display, and an optical system projects the calligraphic image onto the same lens so that it is superposed on the video representation of the landing field. The optical system includes a four-color wheel which is rotated between the calligraphic display and the lens, and an apparatus for synchronizing the generation of a calligraphic pattern with the color segments on the color wheel. A servo feedback system responsive to the servo motors on the gantry frame produces an input to the computer so that the calligraphically generated signal corresponds in shape, size and location to the video signal.

Chase, W. D.↗

NASA NTRS1983

Geometric rectification of radar imagery using digital elevation models

Geologic analysis of radar imagery requires accurate spatial rectification to allow rock type discrimination and meaningful exploitation of multisensor data files. A procedure is described which removes distortions produced by most sources including the heretofore elusive problem of terrain induced effects. Rectified imagery is presented which displays geologic features not apparent in the distorted data.

Naraghi, M.↗

NASA NTRS2010

Quantitative Measures of Immersion in Cloud and the Biogeography of Cloud Forests

Sites described as tropical montane cloud forests differ greatly, in part because observers tend to differ in their opinion as to what constitutes frequent and prolonged immersion in cloud. This definitional difficulty interferes with hydrologic analyses, assessments of environmental impacts on ecosystems, and biogeographical analyses of cloud forest communities and species. Quantitative measurements of cloud immersion can be obtained on site, but the observations are necessarily spatially limited, although well-placed observers can examine 10 50 km of a mountain range under rainless conditions. Regional analyses, however, require observations at a broader scale. This chapter discusses remote sensing and modeling approaches that can provide quantitative measures of the spatiotemporal patterns of cloud cover and cloud immersion in tropical mountain ranges. These approaches integrate remote sensing tools of various spatial resolutions and frequencies of observation, digital elevation models, regional atmospheric models, and ground-based observations to provide measures of cloud cover, cloud base height, and the intersection of cloud and terrain. This combined approach was applied to the Monteverde region of northern Costa Rica to illustrate how the proportion of time the forest is immersed in cloud may vary spatially and temporally. The observed spatial variation was largely due to patterns of airflow over the mountains. The temporal variation reflected the diurnal rise and fall of the orographic cloud base, which was influenced in turn by synoptic weather conditions, the seasonal movement of the Intertropical Convergence Zone and the north-easterly trade winds. Knowledge of the proportion of the time that sites are immersed in clouds should facilitate ecological comparisons and biogeographical analyses, as well as land use planning and hydrologic assessments in areas where intensive on-site work is not feasible.

Lawton, R. O.↗

NASA NTRS1981

Rain, fog, and clouds for aircraft simulators

Environmental chamber creates realistic fog and rain effects in aircraft simulator. It reproduces clouds, homogeneous fog, patches of fog, rain and fog, and rain only. It is used with real time digital computer, color computer generated image display that simulates airport lights, or color television camera that produces moving display of airport runway as depicted on model terrain board.

Chase, W. D.↗

NASA NTRS2013

Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS

The Mars Exploration Rovers (MERs), Spirit and Opportunity, far exceeded their original drive distance expectations and have traveled, at the time of this reporting, a combined 29 kilometers across the surface of Mars. The Rover Sequencing and Visualization Program (RSVP), the current program used to plan drives for MERs, is only a kinematic simulator of rover movement. Therefore, rover response to various terrains and soil types cannot be modeled. Although sandbox experiments attempt to model rover-terrain interaction, these experiments are time-intensive and costly, and they cannot be used within the tactical timeline of rover driving. Imaging techniques and hazard avoidance features on MER help to prevent the rover from traveling over dangerous terrains, but mobility issues have shown that these methods are not always sufficient. ARTEMIS, a dynamic modeling tool for MER, allows planned drives to be simulated before commands are sent to the rover. The deformable soils component of this model allows rover-terrain interactions to be simulated to determine if a particular drive path would take the rover over terrain that would induce hazardous levels of slip or sink. When used in the rover drive planning process, dynamic modeling reduces the likelihood of future mobility issues because high-risk areas could be identified before drive commands are sent to the rover, and drives planned over these areas could be rerouted. The ARTEMIS software consists of several components. These include a preprocessor, Digital Elevation Models (DEMs), Adams rover model, wheel and soil parameter files, MSC Adams GUI (commercial), MSC Adams dynamics solver (commercial), terramechanics subroutines (FORTRAN), a contact detection engine, a soil modification engine, and output DEMs of deformed soil. The preprocessor is used to define the terrain (from a DEM) and define the soil parameters for the terrain file. The Adams rover model is placed in this terrain. Wheel and soil parameter files can be altered in the respective text files. The rover model and terrain are viewed in Adams View, the GUI for ARTEMIS. The Adams dynamics solver calls terramechanics subroutines in FORTRAN containing the Bekker-Wong equations.

Trease, Brian P.↗

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↗