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At least 109 records · Page 6

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↗

Mars rover concept development

A structured study effort to develop an extensive, innovative set of mobility and navigation concepts for a planetary exploration vehicle along with the concomitant value system and evaluation tools is presented. A further objective is to submit these concepts to a rigorous, structured evaluation process to derive the most promising candidate systems. To support the evaluation process, a three-layer computer model of the Martian surface was developed, based on the 1/64 deg Digital Elevation Model (DEM) of Mars. Local surface roughness based on measured Martian slope distribution and power spectral density was superimposed on the DEM, and rocks based on Moore's distribution model were added. To assess performance, selected concepts were modeled using DADS, and simulations were run with the vehicle traversing the Martian surface model, including one-meter-high vertical steps and one-meter-wide crevasses. The design details of three promising candidate systems are presented, along with the discussion of their evolution with some recommendations.

Mctamaney, Louis S.↗

Western Rainier Seismic Zone Airborne Laser Swath Mapping

Airborne laser swath mapping (ALSM) of the Puget Lowland conducted by TerraPoint LLC for the Purget Sound Lidar Concortium (PSLC), has been successful in revealing Holocene fault scarps and lendsliders hidden beneath the dense, temperate rain forest cover and in quantifying shoreline terrace uplift. Expanding the PSLC efforts, NASA-USGS collaboration is now focusing on topographic mapping of seismogenic zones adjacent to volcanois in the western Cascades range in order to assess the presence of active faulting and tectonic deformation, better define the extend of lahars and understand their flow processes, and characterize landslide occurrence. Mapping of the western Rainier zone (WRZ) was conducted by TerraPoint in late 2002, after leaf fall and before snow accumulation. The WRZ is a NNW-trending, approx. 30 km-long zone of seismicity west of Mount Rainier National Park. The Puget Lowland ALSM methods were modified to accommodate challenges posed by the steep, high relief terrian. The laser data, acquired with a density of approx. 2 pulses /sq m, was filtered to identify returns from the ground from which a bare Earth digital elevation model (DEM) was produced with a grid size of 1.8 m. The RMS elevation accuracy of the DEM in flat, unvegetated areas is approx. 10cm based on consistency between overlapping flight swaths and comparisons to ground control points. The resulting DEM substantially improves upon Shuttle Radar Topography Mission and USGS photogrammetric mapping. For example, the DEM defines the size and spatial distribution of flood erratics left by the Electron lahar and of megaclasts within the Round Pass lahar, important for characterizing the lahar hydraulics. A previously unknown lateral levee on the Round Pass lahar is also revealed. In addition, to illustrating geomorfic feature within the WRZ, future plans for laser mapping of the Saint Helens and Darrington seismic zones will be described.

Harding, David J.↗

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↗

Ground-Level Digital Terrain Model (DTM) Construction from Tandem-X InSAR Data and Worldview Stereo-Photogrammetric Images

The ground-level digital elevation model (DEM) or digital terrain model (DTM) information are invaluable for environmental modeling, such as water dynamics in forests, canopy height, forest biomass, carbon estimation, etc. We propose to extract the DTM over forested areas from the combination of interferometric complex coherence from single-pass TanDEM-X (TDX) data at HH polarization and Digital Surface Model (DSM) derived from high-resolution WorldView (WV) image pair by means of random volume over ground (RVoG) model. The RVoG model is a widely and successfully used model for polarimetric SAR interferometry (Pol-InSAR) technique for vertical forest structure parameter retrieval [1][2][3][4]. The ground-level DEM have been obtained by complex volume decorrelation in the RVoG model with the DSM using stereo-photogrammetric technique. Finally, the airborne lidar data were used to validate the ground-level DEM and forest canopy height results.

Lee, Seung-Kuk↗

NASA's Earth Science Use of Commercially Availiable Remote Sensing Datasets: Cover Image

The cover image incorporates high resolution stereo pairs acquired from the DigitalGlobe(R) QuickBird sensor. It shows a digital elevation model of Meteor Crater, Arizona at approximately 1.3 meter point-spacing. Image analysts used the Leica Photogrammetry Suite to produce the DEM. The outside portion was computed from two QuickBird panchromatic scenes acquired October 2006, while an Optech laser scan dataset was used for the crater s interior elevations. The crater s terrain model and image drape were created in a NASA Constellation Program project focused on simulating lunar surface environments for prototyping and testing lunar surface mission analysis and planning tools. This work exemplifies NASA s Scientific Data Purchase legacy and commercial high resolution imagery applications, as scientists use commercial high resolution data to examine lunar analog Earth landscapes for advanced planning and trade studies for future lunar surface activities. Other applications include landscape dynamics related to volcanism, hydrologic events, climate change, and ice movement.

Underwood, Lauren W.↗

Assessment of Required Accuracy of Digital Elevation Data for Hydrologic Modeling

The effect of vertical accuracy of Digital Elevation Models (DEMs) on hydrologic models is evaluated by comparing three DEMs and resulting hydrologic model predictions applied to a 7.2 sq km USDA - ARS watershed at Mahantango Creek, PA. The high resolution (5 m) DEM was resempled to a 30 m resolution using method that constrained the spatial structure of the elevations to be comparable with the USGS and SIR-C DEMs. This resulting 30 m DEM was used as the reference product for subsequent comparisons. Spatial fields of directly derived quantities, such as elevation differences, slope, and contributing area, were compared to the reference product, as were hydrologic model output fields derived using each of the three DEMs at the common 30 m spatial resolution.

HYDROLOGIC MODELS↗

Topographic mapping using radar interferometry - Processing techniques

In the summer of 1991 the NASA DC-8 airborne synthetic aperture radar (SAR) system acquired data with the radar configured in a C-band across-track interferometer mode. The data were processed to generate rectified topographic maps. A new processing scheme was developed featuring motion compensation, absolute phase retrieval, and three-dimensional 1ocation. The new processor has been tested using data which were acquired with extreme aircraft motion so that performance could be evaluated under adverse conditions. The topographic maps generated by the radar were compared to Digital Elevation Models (DEM's) derived using conventional optical stereo techniques. In one region we measured rms elevation deviations which were less than the specified DEM accuracy, and in the region covered by the more accurate DEM we found errors varying from 2.2 m rms in relatively flat terrain up to 5.0 m in mountainous areas. The rms difference between radar and DEM elevations over the 6.5 km by 22 km area covered by the more accurate DEM was 3.6 m.

Madsen, Soren N.↗

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob↗

Utilizing Satellite Based Observations and Physical Hydrological Modeling for Freshwater Ecosystem Health in the Lower Mekong River Basin

Freshwater availability is necessary to promote economic growth through agriculture, fisheries, transport, environmental health, and social equity.The National Aeronautics and Space Administration (NASA) and the Conservation International (CI) are partnering to use remote sensing Earth observations to improve regional efforts that assess natural resources for conservation and sustainable management. (Vollmer et al.,2018) have presented the social-ecological framework named the Freshwater Health Index (FHI), which takes account of the interplay between governance, stakeholders, freshwater ecosystems and the ecosystem services they provide.In this work, we develop decision support and making tools for natural resources conservation in the Lower Mekong by leveraging the FHI framework, multiple data products, and hydrological modeling capabilities (Mohammed et al., 2018). Modeling capabilities enable the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil characteristics, and land cover and land use information to simulate water flux framework.

Mohammed, Ibrahim N.↗

Analysis of Daily, Seasonal, and Interannual Changes in Hofsjokull Ice Cap, Iceland, using Satellite Data

Analysis of a time series of European Remote Sensing Satellite (ERS)-1 and -2, RADARSAT ScanSAR synthetic aperture radar (SAR) and Landsat images from 1973 to 1998, shows daily to interannual changes in Hofsjokull, a 923 sq km ice cap in central Iceland. A digital elevation model of Hofsjokull was constructed using interferometry, and then SAR backscatter coefficient (d) was plotted with elevation, and air temperature along a transect across the ice cap. Most of the a' changes measured along the transect are caused by a change in the state (frozen or thawed) of the surficial snow or ice when air temperature rises above or below about -5 to O C. Seasonal (sigma)deg patterns are identified in a 4-year time series of 57 ERS-1 and -2 images. In addition, June 1997 ScanSAR images display rapid changes in brightness that are tied closely to daily meteorological events. SAR and Landsat data were also used to measure changes in the areal extent of Hofsjokull, from 1973 to 1997, and to locate (sigma)deg and reflectance boundaries that relate to the glacier facies. Late-summer 1997 (sigma)deg and reflectance boundaries agree and are coincident with the approximate location of the fim line, and the January 1998 position of the equilibrium line as determined from ERS-2 data.

Hall, D. K.↗

Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery

Thermal heterogeneity of rivers is essential to support freshwater biodiversity. Salmon behaviorally thermoregulate by moving from patches of warm water to cold water. When implementing river restoration projects, it is essential to monitor changes in temperature and thermal heterogeneity through time to assess the impacts to a river’s thermal regime. Lightweight sensors that record both thermal infrared (TIR) and multispectral data carried via unoccupied aircraft systems (UASs) present an opportunity to monitor temperature variations at high spatial (<0.5 m) and temporal resolution, facilitating the detection of the small patches of varying temperatures salmon require. Here, we present methods to classify and filter visible wetted area, including a novel procedure to measure canopy cover, and extract and correct radiant surface water temperature to evaluate changes in the variability of stream temperature pre- and post-restoration followed by a high-intensity fire in a section of the river corridor of the South Fork McKenzie River, Oregon. We used a simple linear model to correct the TIR data by imaging a water bath where the temperature increased from 9.5 to 33.4 °C. The resulting model reduced the mean absolute error from 1.62 to 0.35 °C. We applied this correction to TIR-measured temperatures of wetted cells classified using NDWI imagery acquired in the field. We found warmer conditions (+2.6 °C) after restoration (p < 0.001) and median absolute deviation for pre-restoration (0.30) to be less than both that of post-restoration (0.85) and post-fire (0.79) orthomosaics. In addition, there was statistically significant evidence to support the hypothesis of shifts in temperature distributions pre- and post-restoration (KS test 2009 vs. 2019, p < 0.001, D = 0.99; KS test 2019 vs. 2021, p < 0.001, D = 0.10). Moreover, we used a Generalized Additive Model (GAM) that included spatial and environmental predictors (i.e., canopy cover calculated from multispectral NDVI and photogrammetrically derived digital elevation model) to model TIR temperature from a transect along the main river channel. This model explained 89% of the deviance, and the predictor variables showed statistical significance. Collectively, our study underscored the potential of a multispectral/TIR sensor to assess thermal heterogeneity in large and complex river systems.

Barker, Matthew I. (ORCID:0000000252864930)↗

The length-scaling properties of topography

The scaling properties of synthetic topographic surfaces and digital elevation models (DEMs) of topography are examined by analyzing their 'structure functions,' i.e., the qth order powers of the absolute elevation differences: delta h(sub q) (l) = E((absolute value of h(x + l) - h(x))(exp q)). We find that the relation delta h(sub 1 l) approximately equal cl(exp H) describes well the scaling behavior of natural topographic surfaces, as represented by DEMs gridded at 3 arc sec. Average values of the scaling exponent H between approximately 0.5 and 0.7 characterize DEMs from Ethiopia, Saudi Arabia, and Somalia over 3 orders of magnitude range in length scale l (approximately 0.1-150 km). Differences in appparent topographic roughness among the three areas most likely reflect differences in the amplitude factor c. Separate determination of scaling properties in the x and y coordinate directions allows us to assess whether scaling exponents are azimuthally dependent (anisotropic) or whether they are isotropic while the surface itself is anisotropic over a restricted range of length scale. We explore ways to determine whether topographic surfaces are characterized by simple or multiscaling properties.

Weissel, Jeffrey K.↗

A Terrestrial Validation of ICESat Elevation Measurements and Implications for Global Reanalyses

The primary goal of NASA's Ice, Cloud, and land Elevation Satellite (ICESat) mission was to detect centimeter-level changes in global ice sheet elevations at the spatial scale of individual ice streams. Confidence in detecting these small signals requires careful validation over time to characterize the uncertainty and stability of measured elevations. A common validation approach compares altimeter elevations to an independently characterized and stable reference surface. Using a digital elevation model (DEM) from geodetic surveys of one such surface, the salar de Uyuni in Bolivia, we show that ICESat elevations at this location have a 0.0-centimeter bias relative to the WGS84 ellipsoid, 4.0-centimeter (1-sigma) uncertainty overall, and 1.8-centimeter uncertainty under ideal conditions over short (50 kilometer) profiles. We observe no elevation bias between ascending and descending orbits, but we do find that elevations measured immediately after transitions from low to high surface albedo may be negatively biased. Previous studies have reported intercampaign biases (ICBs) between various ICESat observation campaigns, but we find no statistically significant ICBs or ICB trends in our data. We do find a previously unreported 3.1-centimeter bias between ICESat's Laser 2 and Laser 3, and we find even larger interlaser biases in reanalyzed data from other studies. For an altimeter with an exact repeat orbit like ICESat, we also demonstrate that validation results with respect to averaged elevation profiles along a single ground track are comparable to results obtained using reference elevations from an in situ survey.

Laser Ranging↗

Program Merges SAR Data on Terrain and Vegetation Heights

X/P Merge is a computer program that estimates ground-surface elevations and vegetation heights from multiple sets of data acquired by the GeoSAR instrument [a terrain-mapping synthetic-aperture radar (SAR) system that operates in the X and bands]. X/P Merge software combines data from X- and P-band digital elevation models, SAR backscatter magnitudes, and interferometric correlation magnitudes into a simplified set of output topographical maps of ground-surface elevation and tree height.

Siqueira, Paul↗

Evaluation of the Global Multi-Resolution Terrain Elevation Data 2010 (GMTED2010) Using ICESat Geodetic Control

Supported by NASA's Earth Surface and Interior (ESI) Program, we are producing a global set of Ground Control Points (GCPs) derived from the Ice, Cloud and land Elevation Satellite (ICESat) altimetry data. From February of 2003, to October of 2009, ICESat obtained nearly global measurements of land topography (+/- 86deg latitudes) with unprecedented accuracy, sampling the Earth's surface at discrete approx.50 m diameter laser footprints spaced 170 m along the altimetry profiles. We apply stringent editing to select the highest quality elevations, and use these GCPs to characterize and quantify spatially varying elevation biases in Digital Elevation Models (DEMs). In this paper, we present an evaluation of the soon to be released Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010). Elevation biases and error statistics have been analyzed as a function of land cover and relief. The GMTED2010 products are a large improvement over previous sources of elevation data at comparable resolutions. RMSEs for all products and terrain conditions are below 7 m and typically are about 4 m. The GMTED2010 products are biased upward with respect to the ICESat GCPs on average by approximately 3 m.

Carabajal, Claudia C.↗

Peru Water Resources: Integrating NASA Earth Observations into Water Resource Planning and Management in Perus La Libertad Region

Developing countries often struggle with providing water security and sanitation services to their populations. An important aspect of improving security and sanitation is developing a comprehensive understanding of the country's water budget. Water For People, a non-profit organization dedicated to providing clean drinking water, is working with the Peruvian government to develop a water budget for the La Libertad region of Peru which includes the creation of an extensive watershed management plan. Currently, the data archive of the necessary variables to create the water management plan is extremely limited. Implementing NASA Earth observations has bolstered the dataset being used by Water For People, and the METRIC (Mapping EvapoTranspiration at High Resolution and Internalized Calibration) model has allowed for the estimation of the evapotranspiration values for the region. Landsat 8 imagery and the DEM (Digital Elevation Model) from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor onboard Terra were used to derive the land cover information, and were used in conjunction with local weather data of Cascas from Peru's National Meteorological and Hydrological Service (SENAMHI). Python was used to combine input variables and METRIC model calculations to approximate the evapotranspiration values for the Ochape sub-basin of the Chicama River watershed. Once calculated, the evapotranspiration values and methodology were shared Water For People to help supplement their decision support tools in the La Libertad region of Peru and potentially apply the methodology in other areas of need.

Padgett-Vasquez, Steve↗

Applications of ArcticDEM for measuring volcanic dynamics, landslides, retrogressive thaw slumps, snowdrifts, and vegetation heights

Topographical changes are of fundamental interest to a wide range of Arctic science disciplines faced with the need to anticipate, monitor, and respond to the effects of climate change, including geohazard management, glaciology, hydrology, permafrost, and ecology. This study demonstrates several geomorphological, cryospheric, and biophysical applications of ArcticDEM – a large collection of publicly available, time-dependent digital elevation models (DEMs) of the Arctic. Our study illustrates ArcticDEM's applicability across different disciplines and five orders of magnitude of elevation derivatives, including measuring volcanic lava flows, ice cauldrons, post-failure landslides, retrogressive thaw slumps, snowdrifts, and tundra vegetation heights. We quantified surface elevation changes in different geological settings and conditions using the time series of ArcticDEM. Following the 2014–2015 Bárðarbunga eruption in Iceland, ArcticDEM analysis mapped the lava flow field, and revealed the post-eruptive ice flows and ice cauldron dynamics. The total dense-rock equivalent (DRE) volume of lava flows is estimated to be (1431 ± 2) million m 3 . Then, we present the aftermath of a landslide in Kinnikinnick, Alaska, yielding a total landslide volume of (400 ± 8) × 103 m 3 and a total area of 0.025 km 2 . ArcticDEM is further proven useful for studying retrogressive thaw slumps (RTS). The ArcticDEM-mapped RTS profile is validated by ICESat-2 and drone photogrammetry resulting in a standard deviation of 0.5 m. Volume estimates for lake-side and hillslope RTSs range between 40,000 ± 9000 m 3 and 1,160,000 ± 85,000 m 3 , highlighting applicability across a range of RTS magnitudes. A case study for mapping tundra snow demonstrates ArcticDEM's potential for identifying high-accumulation, late-lying snow areas. The approach proves effective in quantifying relative snow accumulation rather than absolute values (standard deviation of 0.25 m, bias of −0.41 m, and a correlation coefficient of 0.69 with snow depth estimated by unmanned aerial systems photogrammetry). Furthermore, ArcticDEM data show its feasibility for estimating tundra vegetation heights with a standard deviation of 0.3 m (no bias) and a correlation up to 0.8 compared to the light detection and ranging (LiDAR). The demonstrated capabilities of ArcticDEM will pave the way for the broad and pan-Arctic use of this new data source for many disciplines, especially when combined with other imagery products. The wide range of signals embedded in ArcticDEM underscores the potential challenges in deciphering signals in regions affected by various geological processes and environmental influences.

Chunli Dai↗