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NASA NTRSDate not supplied

Improvements to GNSS Positioning in Challenging Environments by 3DMA Lidar Informed Selective Satellites Usage

The use of global navigation satellite systems (GNSS) for position estimation tends to yield poor results when operating inside of an urban canyon due to large obstructions (e.g., buildings) that disrupt signals as they travel from a satellite to a receiver resulting in a position estimate that may significantly fluctuate in magnitude and direction. Identifying and removing signals that are non-line-of-sight (NLOS) to the receiver and only using signals that are line-of-sight (LOS) can improve the estimated position. However, quickly and accurately determining the LOS status of each measurement can be challenging without additional information about the operating environment. Use of publicly available lidar data can be used to incorporate techniques, such as 3D-mapping-aided (3DMA), to estimate the LOS status of satellites and augment the position solution accordingly. To complicate the issue, the error on the GNSS position estimate in an urban canyon is often so large that is it not sufficient to use as an approximate location for LOS prediction. That is, at times the calculated GNSS solution is not representative of the true location and cannot be used to accurately predict which satellites are within LOS due to the difference in the physical geometry associated with the two locations. This paper explores the use of a GNSS/inertial fused position solution as the initial position estimate for predicting which satellites are within LOS in an urban environment and the impact that removal of predicted NLOS satellites has on the GNSS position solution.

GPS↗

NASA NTRS2015

Real-time Terrain Relative Navigation Test Results from a Relevant Environment for Mars Landing

Terrain Relative Navigation (TRN) is an on-board GN&C function that generates a position estimate of a spacecraft relative to a map of a planetary surface. When coupled with a divert, the position estimate enables access to more challenging landing sites through pin-point landing or large hazard avoidance. The Lander Vision System (LVS) is a smart sensor system that performs terrain relative navigation by matching descent camera imagery to a map of the landing site and then fusing this with inertial measurements to obtain high rate map relative position, velocity and attitude estimates. A prototype of the LVS was recently tested in a helicopter field test over Mars analog terrain at altitudes representative of Mars Entry Descent and Landing conditions. TRN ran in real-time on the LVS during the flights without human intervention or tuning. The system was able to compute estimates accurate to 40m (3 sigma) in 10 seconds on a flight like processing system. This paper describes the Mars operational test space definition, how the field test was designed to cover that operational envelope, the resulting TRN performance across the envelope and an assessment of test space coverage.

Pin-point Landing↗

DOE OSTI2024

Chromosome-level genome assemblies and genetic maps reveal heterochiasmy and macrosynteny in endangered Atlantic Acropora

Abstract Background Over their evolutionary history, corals have adapted to sea level rise and increasing ocean temperatures, however, it is unclear how quickly they may respond to rapid change. Genome structure and genetic diversity contained within may highlight their adaptive potential. Results We present chromosome-scale genome assemblies and linkage maps of the critically endangered Atlantic acroporids,Acropora palmataandA. cervicornis. Both assemblies and linkage maps were resolved into 14 chromosomes with their gene content and colinearity. Repeats and chromosome arrangements were largely preserved between the species. The family Acroporidae and the genusAcroporaexhibited many phylogenetically significant gene family expansions. Macrosynteny decreased with phylogenetic distance. Nevertheless, scleractinians shared six of the 21 cnidarian ancestral linkage groups as well as numerous fission and fusion events compared to other distantly related cnidarians. Genetic linkage maps were constructed from oneA. palmatafamily and 16A. cervicornisfamilies using a genotyping array. The consensus maps span 1,013.42 cM and 927.36 cM forA. palmataandA. cervicornis, respectively. Both species exhibited high genome-wide recombination rates (3.04 to 3.53 cM/Mb) and pronounced sex-based differences, known as heterochiasmy, with 2 to 2.5X higher recombination rates estimated in the female maps. Conclusions Together, the chromosome-scale assemblies and genetic maps we present here are the first detailed look at the genomic landscapes of the critically endangered Atlantic acroporids. These data sets revealed that adaptive capacity of Atlantic acroporids is not limited by their recombination rates. The sister species maintain macrosynteny with few genes with high sequence divergence that may act as reproductive barriers between them. In the AtlanticAcropora, hybridization between the two sister species yields an F1 hybrid with limited fertility despite the high levels of macrosynteny and gene colinearity of their genomes. Together, these resources now enable genome-wide association studies and discovery of quantitative trait loci, two tools that can aid in the conservation of these species.

Biotechnology & Applied Microbiology↗

NASA NTRS1993

Geology and radiophysical properties of the Venera and Vega landing sites

Geologic maps for all seven Venera and Vega landing sites have been produced. Because the radius of error for each landing site is 150 km, the entire landing circle has been mapped centered about the estimated landing point. Correlations were found between the Magellan imagery and the lander TV panoramas and geochemical measurements made at the landing site. Radiophysical properties, including backscatter cross-sections, altimetry, emissivity, and rms slopes, were determined for each landing circle. After mapping the geology of the landing circles, the regional geology of the seven sites was mapped and the geologic history of theses large regions was determined.

Weitz, C. M.↗

NASA NTRS1991

Remote sensing of potential lunar resources. I - Near-side compositional properties

Using telescopic CCD multispectral images of the lunar near side and the results of 330-870 nm spectroscopy of selected regions, the compositional differences relevant to the locations of potential lunar resources (such as ilmenite, FeTiO3, and solar-wind-implanted He-3 and H) are estimated. The 400/560 nm CCD ratio images were converted to weight percent TiO2, and the values were used to construct a new TiO2 abundance map which can be used to estimate the areas potentially rich in ilmenite. A 950/560 nm CCD ratio mosaic of the full moon provides estimates of relative surface maturity. Since high He-3 concentrations correlate with mature ilmenite-rich soils, a combination of relative surface maturity maps and the TiO2 abundance maps can be used to estimate distributions of He-3 (and possibly H) on local scales.

Johnson, Jeffrey R.↗

NASA NTRS1983

Classification and area estimation of land covers in Kansas using ground-gathered and LANDSAT digital data

Ground-gathered data and LANDSAT multispectral scanner (MSS) digital data from 1981 were analyzed to produce a classification of Kansas land areas into specific types called land covers. The land covers included rangeland, forest, residential, commercial/industrial, and various types of water. The analysis produced two outputs: acreage estimates with measures of precision, and map-type or photo products of the classification which can be overlaid on maps at specific scales. State-level acreage estimates were obtained and substate-level land cover classification overlays and estimates were generated for selected geographical areas. These products were found to be of potential use in managing land and water resources.

May, G. A.↗

NASA NTRS2003

First Year Wilkinson Microwave Anisotropy Probe(WMAP)Observations: The Angular Power Spectrum

We present the angular power spectrum derived from the first-year Wilkinson Microwave Anisotropy Probe (WMAP) sky maps. We study a variety of power spectrum estimation methods and data combinations and demonstrate that the results are robust. The data are modestly contaminated by diffuse Galactic foreground emission, but we show that a simple Galactic template model is sufficient to remove the signal. Point sources produce a modest contamination in the low frequency data. After masking approximately 700 known bright sources from the maps, we estimate residual sources contribute approximately 3500 mu sq Kappa at 41 GHz, and approximately 130 mu sq Kappa at 94 GHz, to the power spectrum [iota(iota + 1)C(sub iota)/2pi] at iota = 1000. Systematic errors are negligible compared to the (modest) level of foreground emission. Our best estimate of the power spectrum is derived from 28 cross-power spectra of statistically independent channels. The final spectrum is essentially independent of the noise properties of an individual radiometer. The resulting spectrum provides a definitive measurement of the CMB power spectrum, with uncertainties limited by cosmic variance, up to iota approximately 350. The spectrum clearly exhibits a first acoustic peak at iota = 220 and a second acoustic peak at iota approximately 540, and it provides strong support for adiabatic initial conditions. Researchers have analyzed the CT(sup Epsilon) power spectrum, and present evidence for a relatively high optical depth, and an early period of cosmic reionization. Among other things, this implies that the temperature power spectrum has been suppressed by approximately 30% on degree angular scales, due to secondary scattering.

Hinshaw, G.↗

DOE OSTI2026

Polynomial-time preparation of low-temperature Gibbs states for two-dimensional toric code

In this work, we propose a polynomial-time algorithm for preparing the Gibbs state of the two-dimensional toric code Hamiltonian at any temperature, starting from any initial state, significantly improving upon prior estimates that suggested exponential scaling with inverse temperature. We prove that fast mixing at low temperature for the two-dimensional toric code can be achieved by augmenting local jump operators with simple global jump operators, which enable efficient transitions between logical sectors. To establish tight lower bounds on the spectral gap, we introduce a new reduction method that eventually maps the problem to estimating the spectral gap of a perturbed graph Laplacian on a stair graph. Our proof also shows that the Lindblad dynamics with a digitally implemented low-temperature local Davies generator is able to efficiently drive the quantum state toward the ground state manifold.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1987

4-D display of satellite cloud images

A technique has been developed to display GOES satellite cloud images in perspective over a topographical map. Cloud heights are estimated using temperatures from an infrared (IR) satellite image, surface temperature observations, and a climatological model of vertical temperature profiles. Cloud levels are discriminated from each other and from the ground using a pattern recognition algorithm based on the brightness variance technique of Coakley and Bretherton. The cloud regions found by the pattern recognizer are rendered in three-dimensional perspective over a topographical map by an efficient remap of the visible image. The visible shades are mixed with an artificial shade based on the geometry of the cloud-top surface, in order to enhance the texture of the cloud top.

Hibbard, William L.↗

DOE OSTI2025

NLR HPC Kestrel Jobs Data

Overview: Anonymized job-level records from the Kestrel HPC system at the National Laboratory of the Rockies (NLR). Each record represents a Slurm batch job with scheduling metadata, resource requests, utilization, energy estimates, and efficiency metrics. Sensitive fields (user, account, job name, submit line, working directory, submit script, and job type) are replaced with 7-character cryptographic hashes. System & Timeframe: Kestrel is located at the NLR campus. Standard compute nodes have 104 cores and 256 GB RAM; bigmem nodes have 2,000 GB. GPU nodes (gpu-h100 partition) use NVIDIA H100 GPUs. Data covers jobs submitted August 2023 through December 2025. Funding provided by the U.S. Department of Energy, EERE. Files: esif.hpc.kestrel.job-anon.zip — Anonymized job records (Hive-partitioned Parquet) datacard.md — Full dataset documentation ~11 million rows, 50 variables. Readable with PyArrow, pandas, DuckDB, Apache Spark, or any Parquet-compatible tool. Data Collection: Jobs collected via sacct with timezone-aware export (SLURM_TIME_FORMAT="%Y-%m-%dT%H:%M:%S%z"), loaded into PostgreSQL. Calculated columns updated via database triggers and batch functions. All timestamps use timestamptz and correctly handle DST transitions. Preprocessing: Anonymization of name, user, account, submit_line, work_dir, submit_script, and job_type via 7-char hex hashes Derived columns: queue_wait, cpu_eff, max/min/avg_mem_eff, energy estimates Simplified job state mapping (e.g., "CANCELLED by 132357" → "CANCELLED") Boolean flags: python_job, reframe_job Temporal decomposition: year, month, day, day_of_week, hour, minute from submit_time Shared node tracking: shared_job_count, nodes_shared, jobs_shared Key Variables: Scheduling: job_id, partition, state_simple, submit_time, start_time, end_time, queue_wait Resources: nodes_req/used, processors_req/used, memory_req, wallclock_req/used, gpus_requested Efficiency: cpu_eff, max/min/avg_mem_eff Energy: cpu_energy_tdp_estimated_max/used_watt_hours, consumed_energy_raw_joules, consumed_energy_raw_watt_hours Sharing: shared_job_count, nodes_shared, jobs_shared Partitions: short, standard, debug, gpu-h100 Job States: CANCELLED, COMPLETED, FAILED, PENDING, RUNNING QoS Levels: normal, high Important Notes: Timestamps include timezone offsets; DST transitions are handled correctly, though adding intervals across DST boundaries requires offset adjustment shared_job_count reflects physical node co-residency, not use of the shared partition Job step records and raw Slurm JSONB fields are excluded Do not attempt to re-identify individuals from hashed fields

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1998

A Modeling Approach to Global Land Surface Monitoring with Low Resolution Satellite Imaging

The effects of changing land use/land cover on global climate and ecosystems due to greenhouse gas emissions and changing energy and nutrient exchange rates are being addressed by federal programs such as NASA's Mission to Planet Earth (MTPE) and by international efforts such as the International Geosphere-Biosphere Program (IGBP). The quantification of these effects depends on accurate estimates of the global extent of critical land cover types such as fire scars in tropical savannas and ponds in Arctic tundra. To address the requirement for accurate areal estimates, methods for producing regional to global maps with satellite imagery are being developed. The only practical way to produce maps over large regions of the globe is with data of coarse spatial resolution, such as Advanced Very High Resolution Radiometer (AVHRR) weather satellite imagery at 1.1 km resolution or European Remote-Sensing Satellite (ERS) radar imagery at 100 m resolution. The accuracy of pixel counts as areal estimates is in doubt, especially for highly fragmented cover types such as fire scars and ponds. Efforts to improve areal estimates from coarse resolution maps have involved regression of apparent area from coarse data versus that from fine resolution in sample areas, but it has proven difficult to acquire sufficient fine scale data to develop the regression. A method for computing accurate estimates from coarse resolution maps using little or no fine data is therefore needed.

Hlavka, Christine A.↗

NASA NTRS1995

Evaluating the Type and State of Alaska Taiga Forests with Imaging Radar for Use in Ecosystem Models

Changes in the seasonal CO2 flux of the boreal forests may result from increased atmospheric CO2 concentrations and associated global warming patterns. To monitor this potential change, a combination of information derived from remote sensing data, including forest type and growing season length, and ecophysiological models which predict the CO2 flux and its seasonal amplitude based on meteorological data, are required. In this paper we address the use of synthetic aperture radar (SAR) to map fores type and monitor canopy and soil freeze/thaw, which define the growing season for conifers, and leaf on/off, which defines the growing season for deciduous species. Aircraft SAR (AIRSAR) data collected in March 1988 during a freeze/thaw event are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off transitions and soil freeze/thaw. Finally, a CO2 flux algorithm is presented which utilizes SAR data and an ecophysiological model to estimate CO2 flux. CO2 flux maps are generated, from which areal estimates of CO2 flux are derived.

Alaska↗

NASA NTRS2004

MIT Haystack Observatory Analysis Center Report

The data from twenty years of the NCEP numerical weather model have been used to calculate the IMF hydrostatic mapping function for several sites distributed in latitude from -66 degrees to +78 degrees. Comparison of heights estimated with the NMF hydrostatic mapping function demonstrates that using NMFh results in height errors at annual and semi-annual periods with amplitudes as large as approximately 8 mm and 4 mm, respectively, when data down to 5 degrees are included. The errors are smallest at the equator and increase towards the poles.

Niell, Arthur↗

NASA NTRS2018

Autonomous Small Body Mapping and Spacecraft Navigation

Current methods for pose and shape estimation of small bodies, such as comets and asteroids, rely on extensive ground support and signiﬁcant use of radiometric measurements using the Deep Space Network. The Stereo-Photoclinometry (SPC) technique is currently used to provide detailed topological information about a small body as well as its absolute orientation and position. While this technique has produced very accurate estimates, the core algorithm cannot be run in real-time and requires a team of scientists on the ground who must communicate with the spacecraft in order to oversee SPC operations. Autonomous onboard navigation addresses these limitations by eliminating the need for human oversight. In this paper, we present an optimization-based estimation algorithm for navigation that allows the spacecraft to autonomously approach and maneuver around an unknown small body by mapping its geometric shape, estimating its orientation, and simultaneously determining the trajectory of the center of mass of the small body. We show the eﬀectiveness of the proposed algorithm using simulated data from a previous ﬂight mission to Comet 67P.

Bhaskaran, Shyamkumar↗

NASA NTRS2016

Top-of-the-Atmosphere Shortwave Flux Estimation from Satellite Observations: An Empirical Neural Network Approach Applied with Data from the A-Train Constellation

Estimates of top-of-the-atmosphere (TOA) radiative flux are essential for the understanding of Earth's energy budget and climate system. Clouds, aerosols, water vapor, and ozone (O3) are among the most important atmospheric agents impacting the Earth's shortwave (SW) radiation budget. There are several sensors in orbit that provide independent information related to these parameters. Having coincident information from these sensors is important for understanding their potential contributions. The A-train constellation of satellites provides a unique opportunity to analyze data from several of these sensors. In this paper, retrievals of cloud/aerosol parameters and total column ozone (TCO) from the Aura Ozone Monitoring Instrument (OMI) have been collocated with the Aqua Clouds and Earth's Radiant Energy System (CERES) estimates of total reflected TOA outgoing SW flux (SWF). We use these data to develop a variety of neural networks that estimate TOA SWF globally over ocean and land using only OMI data and other ancillary information as inputs and CERES TOA SWF as the output for training purposes. OMI-estimated TOA SWF from the trained neural networks reproduces independent CERES data with high fidelity. The global mean daily TOA SWF calculated from OMI is consistently within 1% of CERES throughout the year 2007. Application of our neural network method to other sensors that provide similar retrieved parameters, both past and future, can produce similar estimates TOA SWF. For example, the well-calibrated Total Ozone Mapping Spectrometer (TOMS) series could provide estimates of TOA SWF dating back to late 1978.

CERES data with high fidelity↗

NASA NTRSDate not supplied

Generation of Continental Scale Percent Tree Cover Product Using Deep-learning and Multi-scale Remote Sensing Data

Spatially explicit percent tree cover (TC) estimation is critical for mapping forest aboveground biomass and its dynamics. While various TC products have been developed, there has not been a generalized framework that can be applied to diverse terrestrial ecosystems due to underlain extreme complexities. Deep learning algorithms can learn a spatial pattern and radiometric characteristics of tree canopy as a robust approximation of physical or empirical models, and thus have emerged as promising and efficient tools for large-scale TC mapping. In this study, we synergistically use very high-resolution aerial imageries (National Agriculture Imagery Program, NAIP) and medium resolution Landsat data to map continental-scale TC (CONUS and Mexico) through a hierarchical deep learning approach (Convolutional Neural Network), i.e., NAIP TC generated from a NAIP model is utilized to train a Landsat model. The produced TC product (hereafter, NEX-TC) is able to capture the spatial pattern of TC distribution and its changes driven by natural disturbance and human land management. We further explore and analyze the reliability and potential uncertainty of the NEX-TC by comparing it to lidar- (lidar-TC), National Land Cover Database (NLCD-TC), and MODIS Vegetation Continuous Field (MODIS-TC). This evaluation practice reveals that TC products based on passive optical sensors tend to underestimate TC across all land cover types while Landsat-based TCs (i.e., NEX-TC & NLCD-TC) perform better than the coarser MODIS TC estimate. Our results show that the NEX-TC is generally comparable to NLCD-TC but it particularly outperforms NLCD-TC and MODIS-TC over the dense forests where lidar-TC indicates >80% TC. These results indicate that our hierarchical deep learning approach and TC product will be effective and useful for characterizing large-scale tree cover and possibly associated carbon dynamics.

Landsat↗

DOE OSTI2024

New Probe of the High- z Baryon Acoustic Oscillation Scale: BAO Tomography with CMB × LIM -Nulling Convergence

Standard rulers such as the baryon acoustic oscillation (BAO) scale serve as workhorses for precision tests of cosmology, enabling distance measurements that probe the geometry and expansion history of our Universe. Aside from BAO measurements from the cosmic microwave background (CMB), most standard ruler techniques operate at relatively low redshifts and depend on biased tracers of the matter density field. In a companion paper, we explored the scientific reach of nulling estimators, where CMB lensing convergence maps are cross-correlated with linear combinations of similar maps from line intensity mapping (LIM) to precisely null out the low-redshift contributions to CMB lensing. We showed that nulling estimators can be used to constrain the high redshift matter power spectrum and showed that this spectrum exhibits discernible BAO features. Here we propose using these features as a standard ruler at high redshifts that does not rely on biased tracers. Forecasting such a measurement at z ~ 5, we find that next-generation instruments will be able to constrain the BAO scale to 7.2% precision, while our futuristic observing scenario can constrain the BAO scale to 4% precision. In conclusion, this constitutes a fundamentally new kind of BAO measurement during early epochs in our cosmic history.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1983

Mapping land use changes in the carboniferous region of Santa Catarina, report 2

The techniques applied to MSS-LANDSAT data in the land-use mapping of Criciuma region (Santa Catarina state, Brazil) are presented along with the results of a classification accuracy estimate tested on the resulting map. The MSS-LANDSAT data digital processing involves noise suppression, features selection and a hybrid classifier. The accuracy test is made through comparisons with aerial photographs of sampled points. The utilization of digital processing to map the classes agricultural lands, forest lands and urban areas is recommended, while the coal refuse areas should be mapped visually.

Valeriano, D. D.↗