Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Space Technology”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8Linked to original sources
USGS1997

Landsat Data

In the mid-1960's, the National Aeronautics and Space Administration (NASA) embarked on an initiative to develop and launch the first Earth monitoring satellite to meet the needs of resource managers and earth scientists. The U.S. Geological Survey (USGS) entered into a partnership with NASA in the early 1970?s to assume responsibility for archiving data and distributing data products. On July 23, 1972, NASA launched the first in a series of satellites designed to provide repetitive global coverage of the Earth?s land masses. Designated initially as the "Earth Resources Technology Satellite-A" ("ERTS-A"), it used a Nimbus-type platform that was modified to carry sensor systems and data relay equipment. When operational orbit was achieved, it was designated "ERTS-1." The satellite continued to function beyond its designed life expectancy of 1 year and finally ceased to operate on January 6, 1978, more than 5 years after its launch date. The second in this series of Earth resources satellites (designated ?ERTS-B?) was launched January 22, 1975. It was renamed "Landsat 2" by NASA, which also renamed "ERTS-1" as "Landsat 1." Three additional Landsats were launched in 1978, 1982, and 1984 (Landsats 3, 4, and 5 ). (See table 1). NASA was responsible for operating the program through the early 1980?s. In January 1983, operation of the Landsat system was transferred to the National Oceanic and Atmospheric Administration (NOAA). In October 1985, the Landsat system was commercialized and the Earth Observation Satellite Company, now Space Imaging EOSAT, assumed responsibility for its operation under contract to NOAA. Throughout these changes, the USGS EROS Data Center (EDC) retained primary responsibility as the Government archive of Landsat data. The Land Remote Sensing Policy Act of 1992 (Public Law 102-5555) officially authorized the National Satellite Land Remote Sensing Data Archive and assigned responsibility to the Department of the Interior. In addition to its Landsat data management responsibility, the EDC investigates new methods of characterizing and studying changes on the land surface with Landsat data.

Fact Sheet↗
USGS2009

Converting nonstandard fish sampling data to standardized data

Fishery biologists spend considerable effort over multiple years collecting data on fish population and community status using a particular sampling method or set of methods. However, new (and often more effective) sampling methods and technologies are continuously being developed. To incorporate these new sampling techniques, fishery biologists need a means for converting sample data collected using old methods so they can be compared with data collected using new methods. Similarly, fishery biologists often need a means to compare fish sample data collected using the same method over time (e.g., from year to year) and space (e.g., between sample sites). If fish abundance, species presence, or richness are estimated using an unbiased statistical estimator, the estimates can be validly compared, even if the fish sample data were collected with different methods. However, if unbiased statistical estimators were not used, biologists need methods for adjusting fish sampling data collected using different methods or using the same method collected under different sampling conditions. In this chapter, we describe and provide examples of statistical techniques for converting nonstandard fish sampling data to standardized data and for making comparisons of fish sampling data collected at different times or at different locations. We define standard fish sampling data as data collected using the standardized fish sampling methods described throughout this book. Any other sampling methods and associated data are thus defined as nonstandard. Before delving into the details of the statistical modeling techniques, we describe the nature of fish sample data, their uses, and their limitations. Catch-effort measures, such as relative abundance and catch per unit effort (CPUE), are more formally described as indices. Here, we define an index as any measure or count of a species or community (e.g., species richness) based on direct observation without an estimate of the ability to count individuals or species. Indices have some very desirable characteristics for use in fisheries research and management. In general (but not always), indices require less effort to collect and are usually more precise than unbiased population estimators (e.g., CPUE versus capture–recapture estimates of abundance). The proper use of indices for assessment of fish populations or communities, however, requires that the relationship between an index and the true value (e.g., fish density, species richness) is relatively constant (1) across the observable range of true values, (2) through time when evaluating trends at a single location, and (3) across space when making comparisons among locations.

Book chapter↗
USGS2015

Is there a single best estimator? selection of home range estimators using area- under- the-curve

Background Global positioning system (GPS) technology for monitoring home range and movements of wildlife has resulted in prohibitively large sample sizes of locations for traditional estimators of home range. We used area-under-the-curve to explore the fit of 8 estimators of home range to data collected with both GPS and concurrent very high frequency (VHF) technology on a terrestrial mammal, the Florida panther Puma concolor coryi , to evaluate recently developed and traditional estimators. Results Area-under-the-curve was the highest for Florida panthers equipped with Global Positioning System (GPS) technology compared to VHF technology. For our study animal, estimators of home range that incorporated a temporal component to estimation performed better than traditional first- and second-generation estimators. Conclusions Comparisons of fit of home range contours with locations collected would suggest that use of VHF technology is not as accurate as GPS technology to estimate size of home range for large mammals. Estimators of home range collected with GPS technology performed better than those estimated with VHF technology regardless of estimator used. Furthermore, estimators that incorporate a temporal component (third-generation estimators) appeared to be the most reliable regardless of whether kernel-based or Brownian bridge-based algorithms were used and in comparison to first- and second-generation estimators. We defined third-generation estimators of home range as any estimator that incorporates time, space, animal-specific parameters, and habitat. Such estimators would include movement-based kernel density, Brownian bridge movement models, and dynamic Brownian bridge movement models among others that have yet to be evaluated.

Florida↗
USGS2025

The impact of the May 1921 superstorm on American telecommunication systems

A compilation is presented of impacts (interference and damage) realized on long-line telegraph and telephone systems across North America during the 13-16 May 1921 magnetic storm. Impacts occurred primarily during local nighttime, after the third of four sudden commencements, and during the storm’s most-prominent main phase. Impacts are attributed to rapid and high-amplitude geomagnetic field variation generated by substorms. This induced potential di erences and between the grounding points of communication networks that were su cient to cause system interference and damage. In the United States, impacts were concentrated in the Midwest and in the East, regions characterized by high electromagnetic surface impedance. Given technological changes, modern telecommunication systems are less exposed to storms like that of May 1921, while power-grid systems are now more exposed to them.

Space Weather↗
USGS2019

Monitoring live vegetation in semiarid and arid rangeland environments with satellite remote sensing in northern Kenya

As part of the U.S. Department of the Interior’s (DOI) commitment to provide technical assistance to the Kenyan Northern Rangelands Trust (NRT), the U.S. Geological Survey, in collaboration with the DOI International Technical Assistance Program and the U.S. Agency for International Development’s regional mission in East Africa, created a high spatial and time-sensitive live vegetation monitoring system for NRT. The system built with advanced field and sensor technologies produced directly calibrated and highly accurate satellite mapping that is extendable both forward and backward in time. The maps are produced in a simple 0–100-percent representation of live vegetation status and change over time. The backbone of the mapping is the Sentinel satellite remote sensing systems with 5-day collection frequencies and ground spatial resolutions of 10 meters. The European Space Agency (ESA) offers free Sentinel satellite image data through conveniently accessed websites and free user-friendly image processing software downloadable directly onto a personal workstation. ESA provides free online software support. The mapping capability was extended from the forward mapping of Sentinel back in time with the Landsat satellite remote sensing system that has an available and free data archive back to 1983. Although Landsat has coarser spatial resolution, the Landsat to Sentinel live vegetation mapping comparison supports the use of Landsat to provide NRT the historical recreation of prominent live vegetation changes.

Open-File Report↗
USGS2024

Converting non-standard data to standardized data

Fishery biologists spend considerable effort over multiple years collecting data on fish population and community status using a particular sampling method or set of methods. However, new (and often more effective) sampling methods and technologies are continuously being developed. To incorporate these new sampling techniques, fishery biologists need a means for converting fish sampling data collected using old methods so that they can be compared with data collected using new sampling methods. Similarly, fishery biologists often need a means to compare fish sampling data collected using the same method over time (e.g., from year to year) and space (e.g., between sample sites). If fish abundance, species presence, or richness are estimated using an unbiased statistical estimator (e.g., occupancy estimation, capture-recapture estimation), the estimates can be validly compared even if the fish sample data were collected with different methods. However, if unbiased statistical estimators were not used, biologists need methods for adjusting fish sampling data collected using different methods or using the same method collected under different sampling conditions. In this chapter, we describe and provide examples of statistical techniques for converting nonstandard fish sampling data to American Fisheries Society (AFS) standardized data and for making comparisons of fish sampling data collected at different times or at different locations. We define standard fish sampling data as data collected using the standardized fish sampling methods described throughout this book. Any other sampling methods and associated data are thus defined as nonstandard. Before delving into the details of the techniques that can be used to convert data, we describe the nature of fish sample data, their uses, and their limitations.

Book chapter↗
USGS1972

ERTS and EROS

In June the National Aeronautics & Space Administration is to launch its first experimental satellite designed to view the Earth systematically with remote-sensing instruments that will provide new information about our resources and environment. The launching will culminate more than 8 years of planning and research by resource agencies of the Federal Government in cooperation with NASA, state and local governments, universities, and industry. The first Earth Resources Technology Satellite, ERTS-A, will be followed a year later by ERTS-B. Analyses of data from them, it is hoped, will lead to design of operational satellites for Earth resources investigations in the future. In the belief that satellite systems will be of significant assistance in meeting its responsibilities to map, monitor, and manage the vast resources and the public lands of the United States, the Department of the Interior assumed a major role in the ERTS-A Experiment.

Geotimes↗
USGS2008

Vegetation Types in Coastal Louisiana in 2007

During the summer and fall of 2007, the U.S. Geological Survey, the Louisiana State University Agricultural Center, and the Louisiana Department of Wildlife and Fisheries Fur and Refuge Division jointly completed an aerial survey to collect data on 2007 vegetation types in coastal Louisiana. The current map presents the data collected in this effort. The 2007 aerial survey was conducted by using techniques developed over the last thirty years while conducting similar vegetation surveys. Transects flown were oriented in a north-south direction and spaced 1.87 mi (3 km) apart and covered coastal marshes from the Texas State line to the Mississippi State line and from the northern extent of fresh marshes to the southern end of saline (saltwater) marshes on the beaches of the Gulf of Mexico or of coastal bays. Navigation along these transects and to each sampling site was accomplished by using Global Positioning System (GPS) technology and geographic information system (GIS) software. As the surveyors reached each sampling station, observed areas of marsh were assigned as fresh, intermediate, brackish, or saline (saltwater) types, and dominant plant species were listed and ranked according to abundance. Delineations of marsh boundaries usually followed natural levees, bayous, or other features that impede or restrict water flow.

Louisiana↗
USGS2010

Joint Agency Commercial Imagery Evaluation (JACIE)

Remote sensing data are vital to understanding the physical world and to answering many of its needs and problems. The United States Geological Survey's (USGS) Remote Sensing Technologies (RST) Project, working with its partners, is proud to sponsor the annual Joint Agency Commercial Imagery Evaluation (JACIE) Workshop to help understand the quality and usefulness of remote sensing data. The JACIE program was formed in 2001 to leverage U.S. Federal agency resources for the characterization of commercial remote sensing data. These agencies sponsor and co-chair JACIE: U.S. Geological Survey (USGS) National Aeronautics and Space Administration (NASA) National Geospatial-Intelligence Agency (NGA) U.S. Department of Agriculture (USDA) JACIE is an effort to coordinate data assessments between the participating agencies and partners and communicate the knowledge and results of the quality and utility of the remotely sensed data available for government and private use.

Fact Sheet↗
USGS2001

Laboratory and field evaluations of the LISST-100 instrument for suspended particle size determinations

Advances in technology have resulted in a new instrument that is designed for in-situ determination of particle size spectra. Such an instrument that can measure undisturbed particle size distributions is much needed for sediment transport studies. The LISST-100 (Laser In-Situ Scattering and Transmissometry) uses the principle of laser diffraction to obtain the size distribution and volume concentration of suspended material in 32 size classes logarithmically spaced between 1.25 and 250 μm. This paper describes a laboratory evaluation of the ability of LISST-100 to determine particle sizes using suspensions of single size, artificial particles. Findings show the instrument is able to determine particle size to within about 10% with increasing error as particle size increases. The instrument determines volume (or mass) concentration using a volume conversion factor C v . This volume conversion factor is theoretically a constant. In the laboratory evaluation C v is found to vary by a factor of about three over the particle size range between 5 and 200 μm. Results from field studies in South San Francisco Bay show that values of mass concentration of suspended marine sediments estimated by LISST-100 agree favorably with estimates from optical backscatterance sensors if an appropriate value of C v , according to mean size, is used and the assumed average particle (aggregate) density is carefully chosen. Analyses of size distribution of suspended materials in South San Francisco Bay over multiple tide cycles suggest the likelihood of different sources of sediment because of different size characteristics during flood and ebb cycles.

Marine Geology↗
USGS2023

GeoAI for spatial image processing

The development of digital image processing, as a subset of digital signal processing, depended upon the maturity of photography and image science, introduction of computers, discovery and advancement of digital recording devices, and the capture of digital images. In addition, government and industry applications in the Earth and medical sciences were paramount to the growth of the technology. From the early days when photography was first introduced to science to today, artificial intelligence and deep learning technologies have been intensively used to analyze imagery. Spatial image processing has experienced breakthroughs and evolutions. This chapter presents an overview of the history of image processing, GeoAI-based image processing applications, and the role of GeoAI in advancing image processing methods and research. We also discussed the remaining challenges to using GeoAI for image processing regarding training data annotation, the issues of scale, resolution, and change in space over time.

Book chapter↗
USGS2019

Multi‐scale habitat selection of elk in response to beetle‐killed forest

Forests of the Rocky Mountains (USA and Canada) have experienced a large‐scale bark‐beetle ( Dendoctronus ponderosae ) epidemic that has led to widespread mortality of pine trees, followed by structural and compositional changes to the forest. The millions of dead trees resulting from this event likely have an effect on ecosystem processes, but currently those effects are mostly unclear. Changes to forest canopy and understory structure are likely to affect behavior and space use of large ungulates as forage abundance, thermal cover, and locomotive costs are presumably altered. We developed and tested hypotheses for how resource selection in summer of female elk ( Cervus canadensis ; n = 47; 2012–2016), the primary large mammal in our study area, was influenced by changes in canopy, understory vegetation, and downed logs in bark‐beetle affected forest in south‐central Wyoming, USA. We employed global positioning system (GPS) technology, an imagery‐derived land cover classification specifically depicting beetle‐affected forest, and on‐the‐ground forest measurements to develop resource and step selection functions. At the study area scale, elk avoided beetle‐killed forest during nearly all parts of the day and selected for intact conifer forest during the day. At the micro‐habitat scale, as canopy cover decreased in beetle‐killed areas, there was a concomitant increase in grass biomass and downed logs. Nevertheless, while in the forest, elk did not alter resource selection relative to changes in understory vegetation or downed logs. The boost in forage abundance within beetle‐killed areas was insufficient to overcome the presumed increases in energy expenditures associated with locomotion and thermoregulation in beetle‐killed forests. The bark‐beetle epidemic has altered how elk use the landscape and has resulted in a potential loss of forest habitat that elk use during the day. Our results indicate that habitat treatments (i.e., fire or harvest) that remove standing dead trees and downed logs in beetle‐killed forest would further facilitate understory growth while reducing the locomotion costs associated with foraging in beetle‐killed forest.

Wyoming, Colorado↗
USGS2009

Methods for assessing movement path recursion with application to African buffalo in South Africa

Recent developments of automated methods for monitoring animal movement, e.g., global positioning systems (GPS) technology, yield high-resolution spatiotemporal data. To gain insights into the processes creating movement patterns, we present two new techniques for extracting information from these data on repeated visits to a particular site or patch ("recursions"). Identification of such patches and quantification of recursion pathways, when combined with patch-related ecological data, should contribute to our understanding of the habitat requirements of large herbivores, of factors governing their space-use patterns, and their interactions with the ecosystem. We begin by presenting output from a simple spatial model that simulates movements of large-herbivore groups based on minimal parameters: resource availability and rates of resource recovery after a local depletion. We then present the details of our new techniques of analyses (recursion analysis and circle analysis) and apply them to data generated by our model, as well as two sets of empirical data on movements of African buffalo (Syncerus coffer): the first collected in Klaserie Private Nature Reserve and the second in Kruger National Park, South Africa. Our recursion analyses of model outputs provide us with a basis for inferring aspects of the processes governing the production of buffalo recursion patterns, particularly the potential influence of resource recovery rate. Although the focus of our simulations was a comparison of movement patterns produced by different resource recovery rates, we conclude our paper with a comprehensive discussion of how recursion analyses can be used when appropriate ecological data are available to elucidate various factors influencing movement. Inter alia, these include the various limiting and preferred resources, parasites, and topographical and landscape factors. ?? 2009 by the Ecological Society of America.

Ecology↗
USGS2022

Optimizing trilateration estimates for tracking fine-scale movement of wildlife using automated radio telemetry networks

A major advancement in the use of radio telemetry has been the development of automated radio tracking systems (ARTS), which allow animal movements to be tracked continuously. A new ARTS approach is the use of a network of simple radio receivers (nodes) that collect radio signal strength (RSS) values from animal-borne radio transmitters. However, the use of RSS-based localization methods in wildlife tracking research is new, and analytical approaches critical for determining high-quality location data have lagged behind technological developments. We present an analytical approach to optimize RSS-based localization estimates for a node network designed to track fine-scale animal movements in a localized area. Specifically, we test the application of analytical filters (signal strength, distance among nodes) to data from real and simulated node networks that differ in the density and configuration of nodes. We evaluate how different filters and network configurations (density and regularity of node spacing) may influence the accuracy of RSS-based localization estimates. Overall, the use of signal strength and distance-based filters resulted in a 3- to 9-fold increase in median accuracy of location estimates over unfiltered estimates, with the most stringent filters providing location estimates with a median accuracy ranging from 28 to 73 m depending on the configuration and spacing of the node network. We found that distance filters performed significantly better than RSS filters for networks with evenly spaced nodes, but the advantage diminished when nodes were less uniformly spaced within a network. Our results not only provide analytical approaches to greatly increase the accuracy of RSS-based localization estimates, as well as the computer code to do so, but also provide guidance on how to best configure node networks to maximize the accuracy and capabilities of such systems for wildlife tracking studies.

Ecology and Evolution↗
USGS2015

A new method for discovering behavior patterns among animal movements

Advanced satellite tracking technologies enable biologists to track animal movements at fine spatial and temporal scales. The resultant data present opportunities and challenges for understanding animal behavioral mechanisms. In this paper, we develop a new method to elucidate animal movement patterns from tracking data. Here, we propose the notion of continuous behavior patterns as a concise representation of popular migration routes and underlying sequential behaviors during migration. Each stage in the pattern is characterized in terms of space (i.e., the places traversed during movements) and time (i.e. the time spent in those places); that is, the behavioral state corresponding to a stage is inferred according to the spatiotemporal and sequential context. Hence, the pattern may be interpreted predictably. We develop a candidate generation and refinement framework to derive all continuous behavior patterns from raw trajectories. In the framework, we first define the representative spots to denote the underlying potential behavioral states that are extracted from individual trajectories according to the similarity of relaxed continuous locations in certain distinct time intervals. We determine the common behaviors of multiple individuals according to the spatiotemporal proximity of representative spots and apply a projection-based extension approach to generate candidate sequential behavior sequences as candidate patterns. Finally, the candidate generation procedure is combined with a refinement procedure to derive continuous behavior patterns. We apply an ordered processing strategy to accelerate candidate refinement. The proposed patterns and discovery framework are evaluated through conceptual experiments on both real GPS-tracking and large synthetic datasets.

International Journal of Geographical Information ↗
USGS2020

Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges

Unoccupied aircraft systems (UAS) are developing into fundamental tools for tackling the grand challenges in volcanology; here, we review the systems used and their diverse applications. UAS can typically provide image and topographic data at two orders of magnitude better spatial resolution than space-based remote sensing, and close-range observations at temporal resolutions down to those of video frame rates. Responsive deployments facilitate dense time-series measurements, unique opportunities for geophysical surveys, sample collection from hostile environments such as volcanic plumes and crater lakes, and emergency deployment of ground-based sensors (and robots) into hazardous regions. UAS have already been used to support hazard management and decision-makers during eruptive crises. As technologies advance, increased system capabilities, autonomy and availability, supported by more diverse and lighter-weight sensors, will offer unparalleled potential for hazard monitoring. UAS are expected to provide opportunities for pivotal advances in our understanding of complex physical and chemical volcanic processes.

Volcanica↗
USGS1997

Deep-ocean field test of methane hydrate formation from a remotely operated vehicle

We have observed the process of formation of clathrate hydrates of methane in experiments conducted on the remotely operated vehicle (ROY) Ventana in the deep waters of Monterey Bay. A tank of methane gas, acrylic tubes containing seawater, and seawater plus various types of sediment were carried down on Ventana to a depth of 910 m where methane gas was injected at the base of the acrylic tubes by bubble stream. Prior calculations had shown that the local hydrographic conditions gave an upper limit of 525 m for the P-T boundary defining methane hydrate formation or dissociation at this site, and thus our experiment took place well within the stability range for this reaction to occur. Hydrate formation in free sea-water occurred within minutes as a buoyant mass of translucent hydrate formed at the gas-water interface. In a coarse sand matrix the Filling of the pore spaces with hydrate turned the sand column into a solidified block, which gas pressure soon lifted and ruptured. In a fine-grained black mud the gas flow carved out flow channels, the walls of which became coated and then filled with hydrate in larger discrete masses. Our experiment shows that hydrate formation is rapid in natural seawater, that sediment type strongly influences the patterns of hydrate formation, and that the use of ROV technologies permits the synthesis of large amounts of hydrate material in natural systems under a variety of conditions so that fundamental research on the stability and growth of these substances is possible.

Geology↗
USGS2004

Toward a scientifically rigorous basis for developing mapped ecological regions.

Despite the wide use of ecological regions in conservation and resource-management evaluations and assessments, a commonly accepted theoretical basis for ecological regionalization does not exist. This fact, along with the paucity of focus on ecological regionalization by professional associations, journals, and faculties, has inhibited the advancement of a broadly acceptable scientific basis for the development, use, and verification of ecological regions. The central contention of this article is that ecological regions should improve our understanding of geographic and ecological phenomena associated with biotic and abiotic processes occurring in individual regions and also of processes characteristic of interactions and dependencies among multiple regions. Research associated with any ecoregional framework should facilitate development of hypotheses about ecological phenomena and dominant landscape elements associated with these phenomena, how these phenomena are structured in space, and how they function in a hierarchy. Success in addressing the research recommendations outlined in this article cannot occur within an ad hoc, largely uncoordinated research environment. Successful implementation of this plan will require activities--coordination, funding, and education--that are both scientific and administrative in nature. Perhaps the most important element of an infrastructure to support the scientific work of ecoregionalization would be a national or international authority similar to the Water and Science Technology Board of the National Academy of Sciences.

Environmental Management↗