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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Integrating very-high-resolution imagery, Sentinel-2 time-series data, and machine learning to map shrub fractional abundance across arid and semi-arid ecosystems in China

Shrub fractional abundance (SFA), the proportion of shrub cover per unit area, serves as a critical indicator of environmental aridity and ecosystem health in arid and semi-arid regions, particularly across the Mongolian steppe. However, large-scale SFA mapping in Mongolian steppe ecosystems remains challenging due to the small crown size of shrubs, their sparse distribution, and spectral overlap with coexisting low vegetation (e.g., grasses and herbs), which hinders accurate detection using coarser-resolution satellite data or traditional field surveys. To address these challenges, we developed a two-step approach that integrates very-high-resolution (VHR) imagery, time-series Sentinel-2 data, and deep learning techniques. First, we generated high-accuracy benchmark maps of individual shrub crowns from 0.5 m VHR imagery by combining manual segmentation with a hybrid deep learning framework (Dino V2 and convolutional neural networks). Second, we used these shrub crown maps as training data to build an XGBoost model for predicting SFA from 20 m Sentinel-2 time-series data, leveraging phenological information to improve estimation. We validated our approach across 70 sites (1km 2 each) in the Inner Mongolia Autonomous Region, which is representative of Mongolian steppe ecosystems. From VHR imagery, we mapped 1.31 million shrub crowns with an accuracy of R 2 = 0.92. Scaling up with Sentinel-2 data yielded regional SFA maps with an R 2 = 0.60. Further SHAP (SHapley Additive exPlanations) analysis on the developed XGBoost model revealed that phenological metrics (particularly observations in early-May, mid-July, and late-September), which distinguish shrub phenology from that of other land cover types (e.g., grasses and bare soil), were the most influential predictors of SFA. Finally, our regional SFA maps uncovered unimodal relationships between shrub distribution and climate variables, peaking at mean annual minimum temperatures near 0 °C and annual precipitation around 200 mm. Collectively, these findings demonstrate how the integration of multi-source remote sensing and machine learning can overcome historical limitations in SFA mapping, enabling accurate, spatially continuous assessments across vast Inner-Mongolian steppe ecosystems. Our framework has the potential to be applied to other steppe ecosystems and dryland ecosystems across the Mongolian steppe and beyond, offering a foundation for improved monitoring and ecological impact assessments in the face of global climate changes.

Arid and semi-arid landscapes↗
DOE OSTI2020

Improvement of cryo-EM maps by density modification

A density-modification procedure for improving maps from single-particle electron cryogenic microscopy (cryo-EM) is presented here. The theoretical basis of the method is identical to that of maximum-likelihood density modification, previously used to improve maps from macromolecular X-ray crystallography. Key differences from applications in crystallography are that the errors in Fourier coefficients are largely in the phases in crystallography but in both phases and amplitudes in cryo-EM, and that half-maps with independent errors are available in cryo-EM. These differences lead to a distinct approach for combination of information from starting maps with information obtained in the density-modification process. The density-modification procedure was applied to a set of 104 datasets and improved map-model correlation and increased the visibility of details in many of the maps. The procedure requires two unmasked half-maps and a sequence file or other source of information on the volume of the macromolecule that has been imaged.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Planck 2015 results: XXII. A map of the thermal Sunyaev-Zeldovich effect

In this article, we have constructed all-sky Compton parameters maps, y-maps, of the thermal Sunyaev-Zeldovich (tSZ) effect by applying specifically tailored component separation algorithms to the 30 to 857 GHz frequency channel maps from the Planck satellite. These reconstructed y-maps are delivered as part of the Planck 2015 release. The y-maps are characterized in terms of noise properties and residual foreground contamination, mainly thermal dust emission at large angular scales, and cosmic infrared background and extragalactic point sources at small angular scales. Specific masks are defined to minimize foreground residuals and systematics. Using these masks, we compute the y-map angular power spectrum and higher order statistics. From these we conclude that the y-map is dominated by tSZ signal in the multipole range, 20 <ℓ< 600. Lastly, we compare the measured tSZ power spectrum and higher order statistics to various physically motivated models and discuss the implications of our results in terms of cluster physics and cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Making maps of cosmic microwave background polarization for B-mode studies: the POLARBEAR example

Analysis of cosmic microwave background (CMB) datasets typically requires some filtering of the raw time-ordered data. For instance, in the context of ground-based observations, filtering is frequently used to minimize the impact of low frequency noise, atmospheric contributions and/or scan synchronous signals on the resulting maps. In this paper, we have explicitly constructed a general filtering operator, which can unambiguously remove any set of unwanted modes in the data, and then amend the map-making procedure in order to incorporate and correct for it. We show that such an approach is mathematically equivalent to the solution of a problem in which the sky signal and unwanted modes are estimated simultaneously and the latter are marginalized over. We investigated the conditions under which this amended map-making procedure can render an unbiased estimate of the sky signal in realistic circumstances. We then discuss the potential implications of these observations on the choice of map-making and power spectrum estimation approaches in the context of B-mode polarization studies. Specifically, we have studied the effects of time-domain filtering on the noise correlation structure in the map domain, as well as impact it may haveon the performance of the popular pseudo-spectrum estimators. We conclude that although maps produced by the proposed estimators arguably provide the most faithful representation of the sky possible given the data, they may not straightforwardly lead to the best constraints on the power spectra of the underlying sky signal and special care may need to be taken to ensure this is the case. By contrast, simplified map-makers which do not explicitly correct for time-domain filtering, but leave it to subsequent steps in the data analysis, may perform equally well and be easier and faster to implement. We focused on polarization-sensitive measurements targeting the B-mode component of the CMB signal and apply the proposed methods to realistic simulations based on characteristics of an actual CMB polarization experiment, POLARBEAR. Finally, our analysis and conclusions are however more generally applicable.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Iterative map-making with two-level preconditioning for polarized cosmic microwave background data sets: A worked example for ground-based experiments

Context. An estimation of the sky signal from streams of time ordered data (TOD) acquired by the cosmic microwave background (CMB) experiments is one of the most important steps in the context of CMB data analysis referred to as the map-making problem. The continuously growing CMB data sets render the CMB map-making problem progressively more challenging in terms of computational cost and memory in particular in the context of ground-based experiments with their operational limitations as well as the presence of contaminants. Aims. We study a recently proposed, novel class of the Preconditioned Conjugate Gradient (PCG) solvers which invoke two-level preconditioners in the context of the ground-based CMB experiments. We compare them against the PCG solvers commonly used in the map-making context considering their precision and time-to-solution. Methods. We compare these new methods on realistic, simulated data sets reflecting the characteristics of current and forthcoming CMB ground-based experiments. We develop a divide-and-conquer implementation of the approach where each processor performs a sequential map-making for a subset of the TOD. Results. We find that considering the map level residuals, the new class of solvers permits us to achieve a tolerance that is better than the standard approach by up to three orders of magnitude, where the residual level often saturates before convergence is reached. This often corresponds to an important improvement in the precision of the recovered power spectra in particular on the largest angular scales. The new method also typically requires fewer iterations to reach a required precision and therefore shorter run times are required for a single map-making solution. However, the construction of an appropriate two-level preconditioner can be as costly as a single standard map-making run. Nevertheless, if the same problem needs to be solved multiple times, for example, as in Monte Carlo simulations, this cost is incurred only once, and the method should be competitive, not only as far as its precision is concerned but also its performance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Area-preserving maps models of gyroaveraged E×B chaotic transport

Discrete maps have been extensively used to model 2-dimensional chaotic transport in plasmas and fluids. Here we focus on area-preserving maps describing finite Larmor radius (FLR) effects on E × B chaotic transport in magnetized plasmas with zonal flows perturbed by electrostatic drift waves. FLR effects are included by gyro-averaging the Hamiltonians of the maps which, depending on the zonal flow profile, can have monotonic or non-monotonic frequencies. In the limit of zero Larmor radius, the monotonic frequency map reduces to the standard Chirikov-Taylor map, and in the case of non-monotonic frequency, the map reduces to the standard nontwist map. We show that in both cases FLR leads to chaos suppression, changes in the stability of fixed points, and robustness of transport barriers. FLR effects are also responsible for changes in the phase space topology and zonal flow bifurcations. Dynamical systems methods based on the counting of recurrences times are used to quantify the dependence on the Larmor radius of the threshold for the destruction of transport barriers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

COMPARING DENSE GALAXY CLUSTER REDSHIFT SURVEYS WITH WEAK-LENSING MAPS

We use dense redshift surveys of nine galaxy clusters at z ∼ 0.2 to compare the galaxy distribution in each system with the projected matter distribution from weak lensing. By combining 2087 new MMT/Hectospec redshifts and the data in the literature, we construct spectroscopic samples within the region of weak-lensing maps of high (70%-89%) and uniform completeness. With these dense redshift surveys, we construct galaxy number density maps using several galaxy subsamples. The shape of the main cluster concentration in the weak-lensing maps is similar to the global morphology of the number density maps based on cluster members alone, mainly dominated by red members. We cross-correlate the galaxy number density maps with the weak-lensing maps. The cross-correlation signal when we include foreground and background galaxies at 0.5z {sub cl} < z < 2z {sub cl} is 10%-23% larger than for cluster members alone at the cluster virial radius. The excess can be as high as 30% depending on the cluster. Cross-correlating the galaxy number density and weak-lensing maps suggests that superimposed structures close to the cluster in redshift space contribute more significantly to the excess cross-correlation signal than unrelated large-scale structure along the line of sight. Interestingly, the weak-lensing mass profiles are not well constrained for the clusters with the largest cross-correlation signal excesses (>20% for A383, A689, and A750). The fractional excess in the cross-correlation signal including foreground and background structures could be a useful proxy for assessing the reliability of weak-lensing cluster mass estimates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

THE ARIZONA RADIO OBSERVATORY CO MAPPING SURVEY OF GALACTIC MOLECULAR CLOUDS. IV. THE NGC 1333 CLOUD IN PERSEUS IN CO J = 2-1 AND {sup 13}CO J = 2-1

We mapped the NGC 1333 section of the Perseus Molecular Cloud in the J = 2-1 emission lines of {sup 12}CO and {sup 13}CO over a 50' × 60' region (3.4 × 4.1 pc at the cloud distance of 235 pc), using the Arizona Radio Observatory Heinrich Hertz Submillimeter Telescope. The angular resolution is 38'' (0.04 pc) and velocity resolution is 0.3 km s{sup –1}. We compare our velocity moment maps with known positions of young stellar objects (YSOs) and (sub)millimeter dust continuum emission. The CO emission is brightest at the center of the cluster of YSOs, but is detected over the full extent of the mapped region at ≥10 × rms. The morphology of the CO channel maps shows a kinematically complex structure, with many elongated features extending from the YSO cluster outward by ∼1 pc. One notable feature appears as a narrow serpentine structure that curves and doubles back, with a total length of ∼3 pc. The {sup 13}CO velocity channel maps show evidence for many low-density cavities surrounded by partial shell-like structures, consistent with previous studies. Maps of the velocity moments show localized effects of bipolar outflows from embedded YSOs, as well as a large-scale velocity gradient around the central core of YSOs, suggestive of large-scale turbulent cloud motions determining the location of current star formation. The CO/{sup 13}CO intensity ratios show the distribution of the CO opacity, which exhibits a complex kinematic structure. Identified YSOs are located mainly at the positions of greatest CO opacity. The maps are available for download as FITS files.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Protocluster discovery in tomographic Ly α forest flux maps

Here, we present a new method of finding protoclusters using tomographic maps of Ly α forest flux. We review our method of creating tomographic flux maps and discuss our new highperformance implementation, which makes large reconstructions computationally feasible. Using a large N-body simulation, we illustrate how protoclusters create large-scale flux decrements, roughly 10 h -1 Mpc across, and how we can use this signal to find them in flux maps. We test the performance of our protocluster finding method by running it on the ideal, noiseless map and tomographic reconstructions from mock surveys, and comparing to the halo catalogue. Using the noiseless map, we find protocluster candidates with about 90 per cent purity, and recover about 75 per cent of the protoclusters that form massive clusters (>3 × 10 14 h -1 M ⊙ ). We construct mock surveys similar to the ongoing COSMOS Lyman-Alpha Mapping And Tomography Observations survey. While the existing data have an average sightline separation of 2.3 h -1 Mpc, we test separations of 2-6 h -1 Mpc to see what can be tolerated for our application. Using reconstructed maps from small separation mock surveys, the protocluster candidate purity and completeness are very close to what was found in the noiseless case. As the sightline separation increases, the purity and completeness decrease, although they remain much higher than we initially expected. We extended our test cases to mock surveys with an average separation of 15 h -1 Mpc, meant to reproduce high source density areas of the Baryon Oscillation Spectroscopic Survey. Finally, we find that even with such a large sightline separation, the method can still be used to find some of the largest protoclusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Convolutional Neural Network Approach for Mapping Arctic Vegetation Using Multi-Sensor Remote Sensing Fusion

Accurate and high-resolution maps of vegetation are critical for projects seeking to understand the terrestrial ecosystem processes and land-atmosphere interactions in Arctic ecosystems, such as U.S. Department of Energy's Next Generation Ecosystem Experiment (NGEE) Arctic. However, most existing Arctic vegetation maps are at a coarse resolution and with a varying degree of detail and accuracy. Remote sensing-based approaches for mapping vegetation, while promising, are challenging in high latitude environments due to frequent cloud cover, polar darkness, and limited availability of high-resolution remote sensing datasets (e.g., ~ 5 m). This study proposes a new remote sensing based multi-sensor data fusion approach for developing high-resolution maps of vegetation in the Seward Peninsula, Alaska. We focus detailed analysis and validation study around the Kougarok river, located in the central Seward Peninsula of Alaska. We seek to evaluate the integration of hyper-spectral, multi-spectral, radar, and terrain datasets using unsupervised and supervised classification techniques over a ~343.72 km 2 area for generating vegetation classifications at a variety of resolutions (5 m and 12.5 m). We fist applied a quantitative goodness-of-fit method, called Mapcurves, that shows the degree of spatial concordance between the public coarse resolution maps and k-means clustering values and relabels the k values based on the best overlap. We develop a convolutional neural network (CNN) approach for developing high resolution vegetation maps for our study region in Arctic. We compare two CNN approaches: (1) breaking up the images into small patches (e.g., 6 × 6) and predict the vegetation class for entire patch and (2) semantic segmentation and predict the vegetation class for every pixel. We also perform accuracy assessments of the developed data products and evaluate varying CNN architectures. The fusion of hyperspectral and optical datasets performed the best, with accuracy values increased from 0.64 to 0.96-0.97 when using a training map produced by unsupervised clustering and Mapcurves labeling for both CNN models.

Langford, Zach↗
DOE OSTI2014

Sci—Thur AM: YIS - 08: Constructing an Attenuation map for a PET/MR Breast coil

In 2013, around 23000 Canadian women and 200 Canadian men were diagnosed with breast cancer. An estimated 5100 women and 55 men died from the disease. Using the sensitivity of MRI with the selectivity of PET, PET/MRI combines anatomical and functional information within the same scan and could help with early detection in high-risk patients. MRI requires radiofrequency coils for transmitting energy and receiving signal but the breast coil attenuates PET signal. To correct for this PET attenuation, a 3-dimensional map of linear attenuation coefficients (μ-map) of the breast coil must be created and incorporated into the PET reconstruction process. Several approaches have been proposed for building hardware μ-maps, some of which include the use of conventional kVCT and Dual energy CT. These methods can produce high resolution images based on the electron densities of materials that can be converted into μ-maps. However, imaging hardware containing metal components with photons in the kV range is susceptible to metal artifacts. These artifacts can compromise the accuracy of the resulting μ-map and PET reconstruction; therefore high-Z components should be removed. We propose a method for calculating μ-maps without removing coil components, based on megavoltage (MV) imaging with a linear accelerator that has been detuned for imaging at 1.0MeV. Containers of known geometry with F18 were placed in the breast coil for imaging. A comparison between reconstructions based on the different μ-map construction methods was made. PET reconstructions with our method show a maximum of 6% difference over the existing kVCT-based reconstructions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-233: Effect of Brachytherapy Seed Artifacts in T2 and Proton Density Maps in MR Images

Purpose: This study aims at investigating the influence of brachytherapy seeds on T2 and proton density (PD) maps generated from MR images. Proton density maps can be used to extract water content. Since dose absorbed in tissue surrounding low energy brachytherapy seeds are highly influenced by tissue composition, knowing the water content is a first step towards implementing a heterogeneity correction algorithm using MR images. Methods: An LDR brachytherapy (IsoAid Advantage Pd-103) seed was placed in the middle of an agar-based gel phantom and imaged using a 3T Philips MR scanner with a 168-channel head coil. A multiple echo sequence with TE=20, 40, 60, 80, 100 (ms) with large repetition time (TR=6259ms) was used to extract T2 and PD maps. Results: Seed artifacts were considerably reduced on T2 maps compared to PD maps. The variation of PD around the mean was obtained as −97% to 125% (±1%) while for T2 it was recorded as −71% to 24% (±1%). Conclusion: PD maps which are required for heterogeneity corrections are susceptible to artifacts from seeds. Seed artifacts on T2 maps, however, are significantly reduced due to not being sensitive to B0 field variation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Impact Mapping for Geospatial Reasoning and Decision Making

Objective The reported study evaluated a novel approach to aiding geospatial reasoning and decision making. Background Impact mapping aims to alleviate the cognitive demands of geospatial tasks in part by externalizing data in the form of an integrated decision surface. This is achieved by aggregating data across multiple sources of information and visualizing their combined utility rather than objective measurements or individual utility. Previous research has shown that geospatial decisions improve when aided in this manner, but it remains unknown if dynamic decision making, often plagued by fatigue and anchoring bias, would benefit similarly. Method The experiment implemented a systematic manipulation of the presence of a composite impact map and the number of attributes present in a two-stage disaster relief, resource allocation task to investigate when and how impact mapping is beneficial or deleterious to decision makers. Results The presence of the composite impact map increased the utility of selected sites, increased re-planning decisions, reduced information display views, and reduced workload. Generally, the effect of the composite impact map was greater when participants were asked to evaluate more attributes. Conclusion Composite impact maps appear to improve repeated geospatial reasoning and minimize anchoring bias because they alleviate the cognitive demands otherwise necessary to interpret and maintain information from multiple attributes. Application Data visualization techniques, such as impact mapping, can improve repeated geospatial decision making in environments that include high cognitive demand.

Illingworth, David A.↗
NASA NTRS1973

Evaluation of ERTS-1 imagery for mapping Quaternary deposits and landforms in the Great Plains and Midwest

The author has identified the following significant results. The main landform associations and larger landforms are readily identifiable on the better images and commonly the gross associations of surficial Quaternary deposits also can be differentiated, primarily by information on landforms and soils. Maps showing the Quaternary geologic-terrain units that can be differentiated from the ERTS-1 images are being prepared for study areas in Illinois, Iowa, Missouri, Kansas, Nebraska, and South Dakota. Preliminary maps at 1:1 million scale are given of two of the study areas, the Peoria and Decatur, Illinois, 1 deg x 2 quadrangles. These maps exemplify the first phase of investigations, which consists of identifying and mapping landform and land use characteristics and geologic-surficial materials directly from ERTS-1 images alone, without input of additional data. These maps shown that commonly the boundaries of geologic-terrain units can be identified more accurately on ERTS-1 images than on topographic maps of 1:250,000 scale. From analysis of drainage patterns, stream-divide relations, and tone and textural variations on the ERTS-1 images, the trends of numerous moraines of Wisconsinan and possibly some of Illinoian age were mapped. In the Peoria study area the trend of a buried valley of the Mississippi River is revealed.

Morrison, R. B.↗
NASA NTRS1973

Evaluation of ERTS-1 imagery for mapping Quaternary deposits and landforms in the Great Plains and Midwest

The author has identified the following significant results. Maps of 1:1 million scale exemplifying the first phase of investigation were prepared for ten study areas (mostly 1 deg x 2 deg in area): 2 in Kansas, 1 in Missouri-Kansas, 2 in Nebraska, 1 in South Dakota, 3 in Illinois, and 1 in Iowa-Illinois (a total of 13 such maps, covering about 97,000 sq. mi., since the start of the project). Collection of all pertinent published geologic-terrain data also has been completed for all the study areas for which these first-phase maps have been made. The ground truth data are being used in combination with additional interpretation of the repetitive ERTS-1 images of most of these study areas to prepare enhanced information maps at 1:500,000. For areas that have not been mapped at 1:500,000 or larger scales, the maps will provide the first moderately detailed information on landform features and surficial materials. Much of the information mapped is significant for exploration and development of ground water (and locally petroleum) and for applications in engineering and environmental geology, and land use patterns as indicated by tone and texture on the images. Numerous moraines have been identified; also, the trends of parts of ancient filled valleys have been identified. Valley alinement appears controlled by faults or other structural lineaments.

Morrison, R. B.↗
NASA NTRS1973

Reconnaissance geologic mapping in the Dry Valleys of Antarctica using the Earth Resources Technology Satellite

The author has identified the following significant results. Reconnaissance geologic mapping can be done with 60-70% accuracy in the Dry Valleys of Antarctica using ERTS-1 imagery. Bedrock geology can be mapped much better than unconsolidated deposits of Quaternary age. Mapping of bedrock geology is facilitated by lack of vegetation, whereas mapping of Quaternary deposits is hindered by lack of vegetation. Antarctic images show remarkable clarity and under certain conditions (moderate relief, selection of the optimum band for specific rock types, stereo-viewing) irregular contacts can be mapped in local areas that are amazing like those mapped at a scale of 1:25,000, but, of course, lack details due to resolution limitations. ERTS-1 images should be a valuable aid to Antarctic geologists who have some limited ground truth and wish to extend boundaries of geologic mapping from known areas.

Houston, R. S.↗
NASA NTRS1973

Remote sensing aids geologic mapping.

Remote sensing techniques have been applied to general geologic mapping along the Rio Grande rift zone in central Colorado. A geologic map of about 1,100 square miles was prepared utilizing (1) prior published and unpublished maps, (2) detailed and reconnaissance field maps made for this study, and (3) remote sensor data interpretations. The map is to be used for interpretation of the complex Cenozoic tectonic and geomorphic histories of the area. Regional and local geologic mapping can be aided by the proper application of remote sensing techniques. Conventional color and color infrared photos contain a large amount of easily-extractable general geologic information and are easily used by geologists untrained in the field of remote sensing. Other kinds of sensor data used in this study, with the exception of SLAR imagery, were generally found to be impractical or unappropriate for broad-scale general geologic mapping.

Knepper, D. H., Jr.↗
NASA NTRS1974

Snow-extent mapping and lake ice studies using ERTS-1 MSS together with NOAA-2 VHRR

Five snow extent maps of the 5,601 sq km American River Basin were prepared using a Zoom Transfer Scope from ERTS-1 MSS band 4 imagery. The maps were generally completed within one hour. A snowmelt curve based on ERTS-1 imagery was used as a calibration standard or comparison for maps prepared from NOAA-2 VHRR imagery in the same manner. Cost comparisons with U-2 derived imagery indicate that ERTS-1 snow mapping of the basins is six times faster. Conservative estimates of comparable aircraft snow survey flights yields a cost figure 200 times that of the ERTS-1 snow map. Snow mapping attempts in the Lake Ontario Basin demonstrated that ERTS-1 is not well suited to large basins. Optimum size of basins for ERTS studies is believed to range from about 250 sq km to 30,000 sq km. The value of the ERTS-1 MSS for Great Lake ice evaluation was proved during the past winter on Lake Erie. Not only were ice features and types of ice identified, but melting ice was detected through the combined use of band 5 and band 7. Ice movement (direction and speed) was mapped by examining imagery from two successive days.

Wiesnet, D. R.↗