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At least 127 records · Page 7

Planetary Geologic Mapping Handbook - 2009

Geologic maps present, in an historical context, fundamental syntheses of interpretations of the materials, landforms, structures, and processes that characterize planetary surfaces and shallow subsurfaces (e.g., Varnes, 1974). Such maps also provide a contextual framework for summarizing and evaluating thematic research for a given region or body. In planetary exploration, for example, geologic maps are used for specialized investigations such as targeting regions of interest for data collection and for characterizing sites for landed missions. Whereas most modern terrestrial geologic maps are constructed from regional views provided by remote sensing data and supplemented in detail by field-based observations and measurements, planetary maps have been largely based on analyses of orbital photography. For planetary bodies in particular, geologic maps commonly represent a snapshot of a surface, because they are based on available information at a time when new data are still being acquired. Thus the field of planetary geologic mapping has been evolving rapidly to embrace the use of new data and modern technology and to accommodate the growing needs of planetary exploration. Planetary geologic maps have been published by the U.S. Geological Survey (USGS) since 1962 (Hackman, 1962). Over this time, numerous maps of several planetary bodies have been prepared at a variety of scales and projections using the best available image and topographic bases. Early geologic map bases commonly consisted of hand-mosaicked photographs or airbrushed shaded-relief views and geologic linework was manually drafted using mylar bases and ink drafting pens. Map publishing required a tedious process of scribing, color peel-coat preparation, typesetting, and photo-laboratory work. Beginning in the 1990s, inexpensive computing, display capability and user-friendly illustration software allowed maps to be drawn using digital tools rather than pen and ink, and mylar bases became obsolete. Terrestrial geologic maps published by the USGS now are primarily digital products using geographic information system (GIS) software and file formats. GIS mapping tools permit easy spatial comparison, generation, importation, manipulation, and analysis of multiple raster image, gridded, and vector data sets. GIS software has also permitted the development of project-specific tools and the sharing of geospatial products among researchers. GIS approaches are now being used in planetary geologic mapping as well (e.g., Hare and others, 2009). Guidelines or handbooks on techniques in planetary geologic mapping have been developed periodically (e.g., Wilhelms, 1972, 1990; Tanaka and others, 1994). As records of the heritage of mapping methods and data, these remain extremely useful guides. However, many of the fundamental aspects of earlier mapping handbooks have evolved significantly, and a comprehensive review of currently accepted mapping methodologies is now warranted. As documented in this handbook, such a review incorporates additional guidelines developed in recent years for planetary geologic mapping by the NASA Planetary Geology and Geophysics (PGG) Program s Planetary Cartography and Geologic Mapping Working Group s (PCGMWG) Geologic Mapping Subcommittee (GEMS) on the selection and use of map bases as well as map preparation, review, publication, and distribution. In light of the current boom in planetary exploration and the ongoing rapid evolution of available data for planetary mapping, this handbook is especially timely.

Tanaka, K. L.↗

Planetary Geologic Mapping Handbook - 2010

Geologic maps present, in an historical context, fundamental syntheses of interpretations of the materials, landforms, structures, and processes that characterize planetary surfaces and shallow subsurfaces. Such maps also provide a contextual framework for summarizing and evaluating thematic research for a given region or body. In planetary exploration, for example, geologic maps are used for specialized investigations such as targeting regions of interest for data collection and for characterizing sites for landed missions. Whereas most modern terrestrial geologic maps are constructed from regional views provided by remote sensing data and supplemented in detail by field-based observations and measurements, planetary maps have been largely based on analyses of orbital photography. For planetary bodies in particular, geologic maps commonly represent a snapshot of a surface, because they are based on available information at a time when new data are still being acquired. Thus the field of planetary geologic mapping has been evolving rapidly to embrace the use of new data and modern technology and to accommodate the growing needs of planetary exploration. Planetary geologic maps have been published by the U.S. Geological Survey (USGS) since 1962. Over this time, numerous maps of several planetary bodies have been prepared at a variety of scales and projections using the best available image and topographic bases. Early geologic map bases commonly consisted of hand-mosaicked photographs or airbrushed shaded-relief views and geologic linework was manually drafted using mylar bases and ink drafting pens. Map publishing required a tedious process of scribing, color peel-coat preparation, typesetting, and photo-laboratory work. Beginning in the 1990s, inexpensive computing, display capability and user-friendly illustration software allowed maps to be drawn using digital tools rather than pen and ink, and mylar bases became obsolete. Terrestrial geologic maps published by the USGS now are primarily digital products using geographic information system (GIS) software and file formats. GIS mapping tools permit easy spatial comparison, generation, importation, manipulation, and analysis of multiple raster image, gridded, and vector data sets. GIS software has also permitted the development of projectspecific tools and the sharing of geospatial products among researchers. GIS approaches are now being used in planetary geologic mapping as well. Guidelines or handbooks on techniques in planetary geologic mapping have been developed periodically. As records of the heritage of mapping methods and data, these remain extremely useful guides. However, many of the fundamental aspects of earlier mapping handbooks have evolved significantly, and a comprehensive review of currently accepted mapping methodologies is now warranted. As documented in this handbook, such a review incorporates additional guidelines developed in recent years for planetary geologic mapping by the NASA Planetary Geology and Geophysics (PGG) Program's Planetary Cartography and Geologic Mapping Working Group's (PCGMWG) Geologic Mapping Subcommittee (GEMS) on the selection and use of map bases as well as map preparation, review, publication, and distribution. In light of the current boom in planetary exploration and the ongoing rapid evolution of available data for planetary mapping, this handbook is especially timely.

Tanaka, K. L.↗

Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development

With new motivation to increase the proportion of energy demands met by zero-carbon sources, there is a greater focus on efforts to assess and mitigate the impacts of renewable energy development on sensitive ecosystems and wildlife, of which birds are of particular interest. One challenge for researchers, due in part to a lack of appropriate tools, has been estimating the effects from such development on individual breeding populations of migratory birds. To help address this, we utilize a newly developed, high-resolution genetic tagging method to rapidly identify the breeding population of origin of carcasses recovered from renewable energy facilities and combine them with maps of genetic variation across geographic space (called ‘genoscapes’) for five species of migratory birds known to be exposed to energy development, to assess the extent of population-level effects on migratory birds. We demonstrate that most avian remains collected were from the largest populations of a given species. In contrast, those remains from smaller, declining populations made up a smaller percentage of the total number of birds assayed. Results suggest that application of this genetic tagging method can successfully define population-level exposure to renewable energy development and may be a powerful tool to inform future siting and mitigation activities associated with renewable energy programs.

14 SOLAR ENERGY↗

Model Data Archive Associated with Manuscript "Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon"

This data package supports the publication “Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon” by Li et al. (2026). The package contains processed model inputs, configuration files, restart files, simulation outputs, scripts, and visualization products used to evaluate post-fire dissolved organic carbon (DOC) dynamics in the Naches River Watershed, Washington, USA, following the 2021 Schneider Springs Fire. The modeling workflow couples ELM-BGC, the biogeochemistry-enabled Energy Exascale Earth System Model Land Model; ATS, the Advanced Terrestrial Simulator for integrated surface-subsurface hydrology; and PFLOTRAN, a reactive transport model for multicomponent aqueous geochemistry. Together, these models simulate how wildfire-induced changes in vegetation, litter, coarse woody debris, and soil organic matter influence DOC production, transport, and reaction from burned hillslopes to stream networks. The archive includes preprocessed meteorological, geospatial, hydrologic, and biogeochemical forcing data; ELM-BGC-derived DOC source terms; ATS mesh files; PFLOTRAN reactive-transport inputs; model configuration files; spin-up and transient restart files; watershed-scale diagnostic outputs; stream concentration time series; and figures or visualization files used to inspect and reproduce key results. File types include Hierarchical Data Format 5 (HDF5) files for gridded forcing and model-coupling data, model input and configuration files for ELM-BGC, ATS, and PFLOTRAN, restart and simulation-output files generated by the modeling workflow, tabular or time-series diagnostic outputs, scripts for post-processing and figure generation, and image or visualization products associated with the manuscript. Use of the package depends on the intended task. Re-running the simulations requires the relevant modeling software, including ELM-BGC, ATS, and PFLOTRAN as ATS's geochemical engine. Inspecting outputs and reproducing figures requires Python with scientific plotting libraries such as Matplotlib, and three-dimensional model outputs may be viewed with ParaView. Geographic information system files or maps may be inspected with ArcGIS Pro or comparable GIS software. The data package is intended to enable traceability, reuse, and partial reproduction of the coupled land-to-watershed hydro-biogeochemical modeling workflow used to test how wildfire disturbance affects terrestrial carbon pools and downstream DOC dynamics.

ATS↗

SolarSMART 2020 Georgia Survey

The SolarSMART 2020 Georgia Survey dataset provides results from a survey of 1,544 residents of the State of Georgia above the age of 18 on their perceptions of photovoltaic solar energy. The survey includes the following: demographic information for each respondent, their location in the state (by ZIP Code); the type of house they reside within; whether they have or have not adopted solar energy (and if so, how did they adopt solar energy); their personal views and perceptions of solar energy both for themselves and within their community; and their perceptions of who within Georgia and across the United States would or would not be inclined to adopt solar. Respondents were asked to provide their responses to questions addressing the following issues as they pertained to both themselves and their perceptions of others (Georgians and Americans writ large): (a) perception of how home type shape solar adoption; (b) perceptions of personal values (interpersonal, political, environmental); (c) the design of solar and the marketing of it; (d) financial dimensions of adopting solar energy; (d) and favorability towards new technologies. This data was collected via an online survey through a third-party distributor between June and September of 2020. Respondents were from 151 of the 159 counties of the State of Georgia, with representation of both urban and rural residents. In total, the dataset includes 171 variables, with one being an open-ended question coded by the research team. Variables include demographic characteristics (personal, housing, location), multiple-choice single answer, ranked-choice responses to different statements about solar, and a series of two digital map exercises where respondents highlighted geographic regions (states or parts of Georgia) based on whether the believe residents there do, do not, or they do not know if the respondents do or do not adopt solar.

14 SOLAR ENERGY↗

Earth Resources Technology Satellite: Non-US standard catalog No. N-13

To provide dissemination of information regarding the availability of Earth Resources Technology Satellite (ERTS) imagery, a Non-U.S. Standard Catalog is published on a monthly schedule. The catalogs identify imagery which has been processed and input to the data files during the preceding month. The Non-U.S. Standard Catalog includes imagery covering all areas except that of the United States, Hawaii, and Alaska. Imagery adjacent to the Continental U.S. and Alaska borders will normally appear in the U.S. Standard Catalog. As a supplement to these catalogs, an inventory of ERTS imagery on 16 millimeter microfilm is available. The catalogs consist of four parts: (1) annotated maps which graphically depict the geographic areas covered by the imagery listed in the current catalog, (2) a computer-generated listing organized by observation identification number (ID) with pertinent information for each image, (3) a computer listing of observations organized by longitude and latitude, and (4) observations which have had changes made in their catalog information since the original entry in the data base.

Source record↗

Earth Resources Technology Satellite: US standard catalog No. U-12

To provide dissemination of information regarding the availability of Earth Resources Technology Satellite (ERTS) imagery, a U.S. Standard Catalog is published on a monthly schedule. The catalogs identify imagery which has been processed and input to the data files during the preceding month. The U.S. Standard Catalog includes imagery covering the Continental United States, Alaska, and Hawaii. As a supplement to these catalogs, an inventory of ERTS imagery on 16 millimeter microfilm is available. The catalogs consist of four parts: (1) annotated maps which graphically depict the geographic areas covered by the imagery listed in the current catalog, (2) a computer-generated listing organized by observation identification number (D) with pertinent information on each image, (3) a computer listing of observations organized by longitude and latitude, and (4) observations which have had changes made in their catalog information since the original entry in the data base.

Source record↗

Information analysis of a spatial database for ecological land classification

An ecological land classification was developed for a complex region in southern California using geographic information system techniques of map overlay and contingency table analysis. Land classes were identified by mutual information analysis of vegetation pattern in relation to other mapped environmental variables. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless, the resulting land classification was ecologically reasonable and performed well when tested with higher quality data from the region.

Davis, Frank W.↗

Comparison of simulated cloud cover with satellite obsrvations over the Western United States

Satellite imagery datasets and regional climate model results are intercompared for evaluation of model accuracy in the simulation of cloud cover. Both monthly average individual simulation times are analyzed. To provide a consistent comparison, satellite data are first mapped into the model's geographic projection, grid domain, and resolution. It is found that September 1988 monthly average cloud fraction results from the modeled simulations correspond to observations, in both spatial pattern and magnitude, with bias less than +/- 20% cloud fraction over the entire inland West. Agreement in the pattern of cloud fraction also is evident for monthly average cloud fraction in July, but there is no negative bias of 10%-30% cloud fraction in the model diagnosis of cloud cover. Correlations between the spatial distributions of model-derived and observed cloud fractions are found to exceed 0.80 for certain geographic regions of the West, and these correlations are largest over mountainous areas during summer. Case studies of a series of daily cloud cover demonstrate the ability of the model to simulate the effects of frontal passage on cloud distribution. The ability of the RegCM1 to simulate daily cloud fraction and diurnal cloud evolution is somewhat weak for the summer convective season. It is anticipated that a more recent version of the regional climate model may improve the simulation of summer season cloud cover, through changes in cloud parameterization and improvements in model resolution.

Wetzel, Melanie A.↗

Regional Distribution Models with Lack of Proximate Predictors: Africanized Honeybees Expanding North

Species distribution models have often been hampered by poor local species data, reliance on coarse-scale climate predictors and the assumption that species-environment relationships, even with non-proximate predictors, are consistent across geographical space. Yet locally accurate maps of invasive species, such as the Africanized honeybee (AHB) in North America, are needed to support conservation efforts. Current AHB range maps are relatively coarse and are inconsistent with observed data. Our aim was to improve distribution maps using more proximate predictors (phenology) and using regional models rather than one across the entire range of interest to explore potential differences in drivers.

PRedictors↗

A Comparative Review of North American Tundra Delineations

Recent profound changes have been observed in the Arctic environment, including record low sea ice extents and high latitude greening. Studying the Arctic and how it is changing is an important element of climate change science. The Tundra, an ecoregion of the Arctic, is directly related to climate change due to its effects on the snow ice feedback mechanism and greenhouse gas cycling. Like all ecoregions, the Tundra border is shifting, yet studies and policies require clear delineation of boundaries. There are many options for ecoregion classification systems, as well as resources for creating custom maps. To help decision makers identify the best classification system possible, we present a review of North American Tundra ecoregion delineations and further explore the methodologies, purposes, limitations, and physical properties of five common ecoregion classification systems. We quantitatively compare the corresponding maps by area using a geographic information system.

Delineations↗

Method and system for routing based on a predicted connectivity quality

A system and method for routing based on a predicted connectivity quality is disclosed. The method includes receiving, by a controller, map information corresponding to a geographical area. The method also includes receiving, by the controller, wireless connectivity information corresponding to the geographical area. The method also includes generating output data of at least one route between a starting location and a destination location within the geographical area. The generating is based on the wireless connectivity information.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The location and scope of geographic remote sensing training in the United States

Maps displaying the distribution of graduate departments of geography in the United States and enrollments in remote sensing courses in all geography departments during the past two calendar years were compiled. It was anticipated that the two distributions would show a marked similarity since remote sensing is a relatively new geographic tool requiring specialized training to use as well as equipment not normally found in most geography departments. Thus only the larger graduate departments can afford to devote time and resources to this specialty. A broad correspondence does exist between the graduate departments of geography and the courses in remote ensing. However, the correlation is far from complete and the exceptions are frequent and large enough to cast doubt upon the accuracy of the original hypothesis. Whereas many large departments do offer courses in remote sensing, many smaller colleges and universities do also. A number of possible explanations can be offered for the discrepancies: (1) course titles, (2) the liberal arts orientation of geography departments in many universities, (3) job-oriented skills which many smaller departments have emphasized, and (4) in the tight job market many new graduates of even the larger departments have had to accept position in smaller departments and colleges.

Hawley, A. J.↗

Employing Geodatabases for Planetary Mapping Conduct - Requirements, Concepts and Solutions

Planetary geologic mapping has become complex in terms of merging and co-registering a variety of different datasets for analysis and mapping. But it has also become more convenient when it comes to conducting actual (geoscientific) mapping with the help of desktop Geographic Information Systems (GIS). The complexity and variety of data, however, are major issues that need to be taken care of in order to provide mappers with a consistent and easy-to-use mapping basis. Furthermore, a high degree of functionality and interoperability of various commercial and open-source GIS and remote sensing applications allow mappers to organize map data, map components and attribute data in a more sophisticated and intuitional way when compared to workflows 15 years ago. Integration of mapping results of different groups becomes an awkward task as each mapper follows his/her own style, especially if mapping conduct is not coordinated and organized programmatically. Problems of data homogenization start with various interpretations and implementations of planetary map projections and reference systems which form the core component of any mapping and analysis work. If the data basis is inconsistent, mapping results in terms of objects georeference become hard to integrate. Apart from data organization and referencing issues, which are important on the mapping as well as the data-processing side of every project, the organization of planetary geologic map units and attributes, as well as their representation within a common GIS environment, are key components that need to be taken care of in a consistent and persistent way.

vanGasselt, Stephan↗

Winter connectivity and leapfrog migration in a migratory passerine

Abstract Technological advances in migratory tracking tools have revealed a remarkable diversity in migratory patterns. One such pattern is leapfrog migration, where individuals that breed further north migrate to locations further south. Here, we analyzed migration patterns in the Painted Bunting ( Passerina ciris ) using a genetic‐based approach. We started by mapping patterns of genetic variation across geographic space (called a genoscape) using 386 individuals from 25 populations across the breeding range. We then genotyped an additional 230 samples from 31 migration stopover locations and 178 samples from 16 wintering locations to map patterns of migratory connectivity. Our analyses of genetic variation across the breeding range show the existence of four genetically distinct groups within the species: Eastern, Southwestern, Louisiana, and Central groups. Subsequent assignment of migrating and wintering birds to genetic groups illustrated that birds from the Central group migrated during the fall via western Mexico or southern Texas, spent the winter from northeastern Mexico to Panama, and migrated north via the Gulf Coast of Mexico. While Louisiana birds overlapped with Central birds on their spring migratory routes along the Gulf Coast, we found that Louisiana birds had a more restricted wintering distribution in the Yucatan Peninsula and Central America. Further estimation of the straight‐line distance from the predicted breeding location to the wintering location revealed that individuals sampled at lower winter latitudes traveled to greater distances (i.e., the predicted breeding area was further north; p > .001), confirming that these species exhibit a leapfrog migration pattern. Overall, these results demonstrate the utility of a genoscape‐based approach for identifying range‐wide patterns of migratory connectivity such as leapfrog migration with a high degree of clarity.

59 BASIC BIOLOGICAL SCIENCES↗

Initial scalar magnetic anomaly map from Magsat

Magsat data acquired during the November 1979-June 1980 mission was used to derive a scalar magnetic anomaly map covering +50 to -50 deg geographic latitude, and the separation of anomaly fields from core and external fields was accomplished by techniques developed for POGO satellite data. Except in the Atlantic and Pacific at latitudes south of -15 deg, comparison of the Magsat map with its POGO data-derived counterpart shows basic anomaly patterns to be reproducible, and higher resolution due to Magsat's lower measurement altitude. Color-coded scalar anomaly maps are presented for both satellites.

Langel, R. A.↗

Automated Classification of Vehicle Movements at Signalized Intersections Using Vehicle Trajectories

Accurate vehicle movement classification through signalized intersections is of paramount importance to the analysis of intersection performance and the optimization of traffic control strategies. Conventional techniques for tracking vehicle turning movements depend on infrastructure-based strategies like human counts, loop detectors, and video analytics, all of which are costly, prone to errors, and spatially constrained. High-frequency trajectory data can be utilized to determine vehicle movement patterns in a scalable and infrastructure-independent method due to the adoption of connected vehicles (CVs). In recent years, several studies have utilized connected vehicle data to generate performance measures. Most of the trajectory-based performance measures approaches, however, require map matching-i.e., extracting geospatial references from maps to identify the movements that individual vehicles make at a signalized intersection. These approaches are often time-consuming and hinder scalability since geographic features need to be provided for an analysis to be conducted. Map matching methods are prone to errors as different map versions change these geographic features. This research presents a novel automatic classification pipeline that uses CV trajectory data to classify vehicle movements at signalized crossings, specifically pass-through left-turn and right-turn maneuvers. The process starts by filtering trips that cross a spatial bounding box that has been defined at the target intersection. Approach and departure headings for each trajectory crossing the boundary are computed and are clustered together to identify dominant movements. The proposed algorithm is used to classify the movement of vehicles at 10 intersections in the state of California, and the results indicate that the algorithm can classify movements at these intersections with varying traffic volumes and road network configurations, all in a map-less framework with no need for conflation of vehicle trajectories to a digital base map.

24 POWER TRANSMISSION AND DISTRIBUTION↗