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At least 91 records · Page 5

Development and implementation of a low cost micro computer system for LANDSAT analysis and geographic data base applications

Since the implementation of the GRID and IMGRID computer programs for multivariate spatial analysis in the early 1970's, geographic data analysis subsequently moved from large computers to minicomputers and now to microcomputers with radical reduction in the costs associated with planning analyses. Programs designed to process LANDSAT data to be used as one element in a geographic data base were used once NIMGRID (new IMGRID), a raster oriented geographic information system, was implemented on the microcomputer. Programs for training field selection, supervised and unsupervised classification, and image enhancement were added. Enhancements to the color graphics capabilities of the microsystem allow display of three channels of LANDSAT data in color infrared format. The basic microcomputer hardware needed to perform NIMGRID and most LANDSAT analyses is listed as well as the software available for LANDSAT processing.

Faust, N.

Monte Carlo models and analysis of galactic disk gamma-ray burst distributions

Gamma-ray bursts are transient astronomical phenomena which have no quiescent counterparts in any region of the electromagnetic spectrum. Although temporal and spectral properties indicate that these events are likely energetic, their unknown spatial distribution complicates astrophysical interpretation. Monte Carlo samples of gamma-ray burst sources are created which belong to Galactic disk populations. Spatial analysis techniques are used to compare these samples to the observed distribution. From this, both quantitative and qualitative conclusions are drawn concerning allowed luminosity and spatial distributions of the actual sample. Although the Burst and Transient Source Experiment (BATSE) experiment on Gamma Ray Observatory (GRO) will significantly improve knowledge of the gamma-ray burst source spatial characteristics within only a few months of launch, the analysis techniques described herein will not be superceded. Rather, they may be used with BATSE results to obtain detailed information about both the luminosity and spatial distributions of the sources.

Hakkila, Jon

Delineating the Impact of Transition‐Metal Crossover on Solid‐Electrolyte Interphase Formation with Ion Mass Spectrometry

Abstract Lithium‐metal batteries (LMB) employing cobalt‐free layered‐oxide cathodes are a sustainable path forward to achieving high energy densities, but these cathodes exhibit substantial transition‐metal dissolution during high‐voltage cycling. While transition‐metal crossover is recognized to disrupt solid‐electrolyte interphase (SEI) formation on graphite anodes, experimental evidence is necessary to demonstrate this for lithium‐metal anodes. In this work, advanced high‐resolution 3D chemical analysis is conducted with time‐of‐flight secondary‐ion mass spectrometry (TOF‐SIMS) to establish spatial correlations between the transition metals and electrolyte decomposition products found on cycled lithium‐metal anodes. Insights into the localization of various chemistries linked to crucial processes that define LMB performance, such as lithium deposition, SEI growth, and transition‐metal deposition are deduced from a precise elemental and spatial analysis of the SEI. Heterogenous transition‐metal deposition is found to perpetuate both heterogeneous SEI growth and lithium deposition on lithium‐metal anodes. These correlations are confirmed across various lithium‐metal anodes that are cycled with different cobalt‐free cathodes and electrolytes. An advanced electrolyte that is stable to higher voltages is shown to minimize transition‐metal crossover and its effects on lithium‐metal anodes. Overall, these results highlight the importance of maintaining uniform SEI coverage on lithium‐metal anodes, which is disrupted by transition‐metal crossover during operation at high voltages.

Chemistry

ROSAT data analysis with EXSAS

For the x-ray observatory ROSAT, data from survey and pointed mission phases taken with different focal plane instruments and according to a complex mission timeline have to be handled. Data analysis therefore puts high demands on appropriate software tools. With EXSAS - the Extended Scientific Analysis System developed with an effort of 20 man years by the German ROSAT Scientific Data Center - a comfortable system for the reduction of data from the ROSAT x-ray and XUV instruments has been made available. EXSAS comprises a large collection of application modules as typically required in analyzing data of this wavelength regime and runs as a specific context in the wide-spread ESO-MIDAS environment. EXSAS, completely written in FORTRAN 77, takes full advantage of all the standards used in MIDAS and therefore, reflects the same portability (different UNIX installations and VMS). If required, the FORTRAN code also enables users to adapt the software in an easy way to their specific needs. To maintain independence from the specifics of different operating systems also on the data input side, all ROSAT data redistributed in the widely accepted FITS format. Although EXSAS has been developed specifically for data analysis of the ROSAT instruments, its structural design is sufficiently general to serve equally well also data from other X-ray and XUV instruments. EXSAS analysis modules are grouped into 4 application packages dealing with Data Preparation and Instrument Correction, Spatial Analysis, Spectral Analysis and Timing Analysis. A special EXSAS header, read and updated by each application, maintains the general information transfer on the origin, the history and the parameter space of the data stored in tables and images. About 100 genuine commands (most of which offer several additional options) allow to interactively explore the functionality of the system. Up to now 40 institutes all over the world have requested the EXSAS software. Maintenance and regular updates of the software and the comprehensive documentation are provided by the ROSAT Scientific Data Center at Garching.

Zimmermann, H. U.

Integration of Landsat data into the Saginaw River Basin geographic information system

One of the objectives of the Saginaw River Basin study is related to the development of a computer model to predict flood damages. The computer model is to be operational in June 1985. In order to achieve this objective, the input of land-use data into a data base consisting of 198,000 grid cells will be required. A planning technique using Spatial Analysis Methodology (SAM) was developed by the Corps of Engineers Hydrologic Engineering Center (HEC) to systematically handle these data. The HEC-SAM system uses the spatially oriented map data in a series of data management and analysis software programs for input to the Corps hydrologic and environmental models. Attention is given to data base development, Landsat digital data, the placement of the Landsat data into the grid cell data base, and the development of the land cover classification. The Landsat-2 MSS scene covering 85 percent of the Saginaw River Basin was geometrically corrected to a UTM coordinate system.

Mckim, H. L.

Measuring forest landscape patterns in the Cascade Range of Oregon, USA

This paper describes the use of a set of spatial statistics to quantify the landscape pattern caused by the patchwork of clearcuts made over a 15-year period in the western Cascades of Oregon. Fifteen areas were selected at random to represent a diversity of landscape fragmentation patterns. Managed forest stands (patches) were digitized and analyzed to produce both tabular and mapped information describing patch size, shape, abundance and spacing, and matrix characteristics of a given area. In addition, a GIS fragmentation index was developed which was found to be sensitive to patch abundance and to the spatial distribution of patches. Use of the GIS-derived index provides an automated method of determining the level of forest fragmentation and can be used to facilitate spatial analysis of the landscape for later coordination with field and remotely sensed data. A comparison of the spatial statistics calculated for the two years indicates an increase in forest fragmentation as characterized by an increase in mean patch abundance and a decrease in interpatch distance, amount of interior natural forest habitat, and the GIS fragmentation index. Such statistics capable of quantifying patch shape and spatial distribution may prove important in the evaluation of the changing character of interior and edge habitats for wildlife.

Ripple, William J.

Bryan Mound Collar Compression Study

This report presents a study of collar compression for the wells at the Bryan Mound site. The study includes a comprehensive review of all available Multi-Arm Caliper (MAC) logs from the site, which has been used to identify specific wells that are experiencing casing restrictions at collar joints. Additional site-wide analysis of Bryan Mound well temperature data, proximity to sulphur wells, pulsed eddy current (PEC) logs, and a general spatial analysis has been included.

02 PETROLEUM

Impact of Spatial Sampling on Continuity of MODIS-VIIRS Land Surface Reflectance Products: A Simulation Approach

With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard the National Aeronautics and Space Administrations Terra and Aqua satellites. In this paper, we aim at quantifying the consistency of Aqua MODIS and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Reflectance (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional reflectance distribution function, the MODIS and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface reflectance at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and MODIS footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for product intercomparisons, spatial aggregations may be used. It was found that if per-grid-cell differences on the order of 10(in LSR or NDVI) are tolerated, the product intercomparisons are expected to be immune from differences in spatial sampling.

VIIRS

Family Life Cycle and Deforestation in Amazonia: Combining Remotely Sensed Information with Primary Data

This paper examines the relationships between the socio-demographic characteristics of small settlers in the Brazilian Amazon and the life cycle hypothesis in the process of deforestation. The analysis was conducted combining remote sensing and geographic data with primary data of 153 small settlers along the TransAmazon Highway. Regression analyses and spatial autocorrelation tests were conducted. The results from the empirical model indicate that socio-demographic characteristics of households as well as institutional and market factors, affect the land use decision. Although remotely sensed information is not very popular among Brazilian social scientists, these results confirm that they can be very useful for this kind of study. Furthermore, the research presented by this paper strongly indicates that family and socio-demographic data, as well as market data, may result in misspecification problems. The same applies to models that do not incorporate spatial analysis.

Caldas, M.

Environmental Assessment and Monitoring with ICAMS (Image Characterization and Modeling System) Using Multiscale Remote-Sensing Data

With the rapid increase in spatial data, especially in the NASA-EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called Image Characterization and Modeling System (ICAMS) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph-MGE and Arc/info UNIX and Windows-NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this paper, we demonstrate the main applications of ICAMS on the Intergraph-MGE platform using Landsat Thematic Mapper images from the city of Lake Charles, Louisiana. While the utilities of ICAMS' spatial measurement methods (e.g., fractal indices) in assessing environmental conditions remain to be researched, making the software available to a wider scientific community can permit the techniques in ICAMS to be evaluated and used for a diversity of applications. The findings from these various studies should lead to improved algorithms and more reliable models for environmental assessment and monitoring.

Lam, N.

Lunar and Planetary Science XXXV: Mars

The session "Mars" included the following reports:Tentative Theories for the Long-Term Geological and Hydrological Evolution of Mars; Stratigraphy of Special Layers Transient Ones on Permeable Ones: Examples from Earth and Mars; Spatial Analysis of Rootless Cone Groups on Iceland and Mars; Summer Season Variability of the North Residual Cap of Mars from MGS-TES; Spectral and Geochemical Characteristics of Lake Superior Type Banded Iron Formation: Analog to the Martian Hematite Outcrops; Martian Wave Structures and Their Relation to Mars; Shape, Highland-Lowland Chemical Dichotomy and Undulating Atmosphere Causing Serious Problems to Landing Spacecrafts; Shear Deformation in the Graben Systems of Sirenum Fosssae, Mars: Preliminary Results; Components of Martian Dust Finding on Terrestrial Sedimentary Deposits with Use of Infrared Spectra; Morphologic and Morphometric Analyses of Fluvial Systems in the Southern Highlands of Mars; Light Pattern and Intensity Analysis of Gray Spots Surrounding Polar Dunes on Mars; The Volume of Possible Ancient Oceanic Basins in the Northern Plains of Mars MARSES: Possibilities of Long-Term Monitoring Spatial and Temporal Variations and Changes of Subsurface Geoelectrical Section on the Base; Results of the Geophysical Survey Salt/Water Interface and Groundwater Mapping on the Marina Di Ragusa, Sicily and Shalter Island, USA ;A Miniature UV-VIS Spectrometer for the Surface of Mars; Automatic Recognition of Aeolian Ripples on Mars; Absolute Dune Ages and Implications for the Time of Formation of Gullies in Nirgal Vallis, Mars; Diurnal Dust Devil Behaviour for the Viking 1 Landing Site: Sols 1 to 30; Topography Based Surface Age Computations for Mars: A Step Toward the Formal Proof of Martian Ocean Recession, Timing and Probability; Gravitational Effects of Flooding and Filling of Impact Basins on Mars; Viking 2 Landing Site in MGS/MOC Images South Polar Residual Cap of Mars: Features, Stratigraphy, and Changes.

Source record

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Al-Hamdan, Mohammad Z.

Lapse-Rate Feeback: The Key to Reconciling TOA and Surface Attributions of Surface Warming

The impact of climate feedbacks on surface warming is conventionally evaluated using a decomposition of the top-of-atmosphere (TOA) energy budget. Alternatively, the climate feedback analysis can also be carried out using the surface energy budget. However, the two perspectives do not provide the same interpretation of process contributions to surface warming, particularly when executing a spatial analysis. The TOA energy budget is equal to the sum of the surface and atmospheric energy budgets. Using the CMIP5 RCP 8.5 model projections, we show that the major discrepancies between the surface and TOA climate feedback attributions of surface warming are due to non-negligible changes in the atmospheric energy budget that differ from their counterparts at the surface. Individual radiative and non-radiative processes cause vertically non-uniform energy flux perturbations, in response to an external forcing, that naturally lead to a vertically non-uniform temperature change. The TOA lapse-rate feedback is the manifestation of these multiple processes that produce a vertically non-uniform warming response such that it accounts for the asymmetry between the changes in the atmospheric and surface energy budgets. Using the climate feedback-response analysis method, we can decompose the lapse-rate feedback into contributions by individual processes. The negative lapse-rate feedback in the tropics is due to greater moist convection and condensational heating along with ocean heat storage. On the other hand, the positive lapse-rate feedback in polar regions is primarily due to the surface albedo and water vapor feedbacks. Combining the process contributions that are hidden within the lapse-rate feedback with their respective direct impacts on the TOA energy budget allows for a very consistent picture of process contributions to surface warming and its inter-model spread as that given by the surface energy budget approach. With the modified approach, both perspectives indicate water vapor feedback is the largest contributor in the tropics, while surface albedo feedback is the greatest contributor in polar regions. Dynamics and ocean heat storage are the main suppressors of surface warming, except over Antarctica. Both perspectives show there is large inter-model uncertainty in the contributions of water vapor, clouds, albedo, and dynamics plus ocean heat storage.

Sergio A Sejas

Siting Lab [SWR-24-95]

Siting Lab contains a collection of user-friendly tutorials and guides for working with the Siting Lab (https://data.openei.org/siting_lab) data within the context of the reV model. The python code examples demonstrate the creation and transformation of Siting Lab data into reV compliant format as well as working with the reV model inputs and outputs. Specifically, Siting Lab provides a collection of Jupyter Notebooks that serve as guides for working with data from NREL's spatial analysis portfolio. These notebooks teach users how to create and interact with reV data in order to facilitate external use of the model. The guides in this repository reference NREL's Supply Curve data as well as Siting Lab spatial data available on OEDI.

Lopez, Anthony

The Application of Remote Sensing using NASA Earth Observations paired with Sociodemographic Indicators to Identify Communities Most Susceptible to Urban Heat Exposure in Austin, Texas

In recent years, Austin, Texas has experienced an increase in population and urban development. Additionally, the City’s climate—already characterized by periods of extreme heat and drought—continues to change. As temperatures and demand for utilities and cooling resources rise, the number of heat-related deaths and illnesses in socially vulnerable populations (e.g., older, lower-income populations) is expected to increase. The City of Austin, The University of Texas at Austin (UT Austin), and The University of Texas Health Science Center at Houston (UT Health) partnered with NASA DEVELOP to examine the distribution of urban heat throughout the City. This project used land surface temperature, greenness, plant water content, and urban surface material analysis parameters derived from NASA Earth observations from Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), and Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The project team produced three different indices to create a spatial analysis for the study area including a social vulnerability index (SoVI), heat exposure index (HEI), and an overall heat priority index (HPI) score. This overall score was determined with a weighted analysis of heat-related environmental variables from NASA Earth observations and socioeconomic data from the 2019 American Community Survey. Based on the HPI score, the project team identified 121 census block groups out of 605 total that are designated as being most at risk of adverse impacts from extreme heat events. To test the sensitivity of the HPI, the team used a Monte Carlo analysis using different approaches for geographic scale, variable inclusion, census uncertainty, and index aggregation. Based on the sensitivity analysis, the resulting HPI score showed the metric was consistent with the baseline HPI. This provided increased confidence the score can be used as a tool to make informed infrastructure improvement plans in targeted areas (e.g., siting of cooling centers) and ensure equitable sustainable development.

Ryan Hammock

Geospatial analysis of preterm and small-for-gestational age births in Washington D.C.

Background: This study is based on the recognition that adverse pregnancy outcomes significantly affect maternal and infant health, leading to increased morbidity and mortality. These outcomes are shaped by a complex interplay of individual-level factors—like maternal age and education—and community-level influences, including socio-economic status and access to healthcare. Understanding these determinants is crucial for developing effective public health strategies, especially for marginalized populations, by identifying high-risk areas and informing targeted interventions that address both individual and structural barriers. Methods: We utilized geospatial analysis to explore the association between individual- and community-level factors and adverse pregnancy outcomes, specifically preterm birth (PTB) and small-for-gestational-age (SGA) birthweight in Washington, D.C. We used Empirical Bayes smoothing methods to calculate rates of adverse birth outcomes from 2010 to 2018 at the U.S. Census tract–level. Spatial scan statistics were used to investigate if adverse birth outcomes clustered in specific areas. ANOVA tests were conducted for individual- and community-level factors within identified clusters. Results: Spatial analysis identified significant high-risk clusters for PTB and SGA infants primarily in southeastern Washington, D.C., particularly in Wards 7 and 8. Individuals residing within these clusters experienced a 47% increased risk of PTB (RR = 1.467) and a 56% increased risk of SGA (RR = 1.560) compared to those outside clusters. Space–time analysis revealed temporal variation, with PTB clusters persisting from 2011 to 2014 and SGA clusters extending through 2017. Compared to low-risk clusters, high-risk clusters had younger birthing individuals (mean age ~26.5 vs. ~33 years), lower maternal college degree attainment (~20% vs. ~80%), higher rates of late or no prenatal care (~16% vs. 11%), and increased prevalence of smoking and hypertension (all P < 0.001). Community-level indicators showed lower median household incomes ($\$40,000$ vs. ~$\$105,000$), greater poverty (~16% vs. ~7% below $\$10,000$/year), higher public assistance use (~32% vs. ~5%), and reduced healthcare access (greater distances to emergency and specialty care) in high-risk areas (all P < 0.001). Neighborhood deprivation indices were significantly elevated, commutes were longer, and population density was lower in these clusters. These findings highlight that adverse birth outcomes cluster in neighborhoods with pronounced socioeconomic and health disparities. Conclusion: High-risk birth clusters highlight intertwined factors: individual, socio-economic, and geographic. Addressing these requires comprehensive interventions focusing on social and structural determinants of health.

Birth outcomes

Army technology development. IBIS query. Software to support the Image Based Information System (IBIS) expansion for mapping, charting and geodesy

The Image Based Information System (IBIS) has been under development at the Jet Propulsion Laboratory (JPL) since 1975. It is a collection of more than 90 programs that enable processing of image, graphical, tabular data for spatial analysis. IBIS can be utilized to create comprehensive geographic data bases. From these data, an analyst can study various attributes describing characteristics of a given study area. Even complex combinations of disparate data types can be synthesized to obtain a new perspective on spatial phenomena. In 1984, new query software was developed enabling direct Boolean queries of IBIS data bases through the submission of easily understood expressions. An improved syntax methodology, a data dictionary, and display software simplified the analysts' tasks associated with building, executing, and subsequently displaying the results of a query. The primary purpose of this report is to describe the features and capabilities of the new query software. A secondary purpose of this report is to compare this new query software to the query software developed previously (Friedman, 1982). With respect to this topic, the relative merits and drawbacks of both approaches are covered.

Friedman, S. Z.

Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analyses

This presentation demonstrates a spatial analysis workflow to assess data availability for the many components of geologic carbon storage technical viability. The workflow relies upon a knowledge-data framework that links the different components of GCS technical viability to the data types needed for evaluation. Using this contextual information, a combination of data science methods (e.g., natural language processing) and spatial analyses are applied to identify areas where sufficient data exists for a given component. The results are aggregated into maps illustrating data density and spatial gaps across all technical viability factors and data categories, as well as the individual component and category level for a more nuanced understanding. Presented at the FECM NETL Carbon Management Program Review Meeting 2024.

Creason, Christopher