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At least 739 records · Page 41Linked to original sources
USGS2019

Analysis and visualization of coastal ocean model data in the cloud

The traditional flow of coastal ocean model data is from High Performance Computing (HPC) centers to the local desktop, or to a file server where just the data needed can be extracted via services such as OPeNDAP. Analysis and visualization is then conducted using local hardware and software. This requires moving large amounts of data across the internet as well as acquiring and maintaining local hardware, software and support personnel. Further, as data sets increase in size, the traditional workflow may not be scalable. Alternatively, recent advances make it possible to move data from HPC to the Cloud and perform interactive, scalable, data-proximate analysis and visualization, with simply a web browser user interface. We use the framework advanced by the NSF-funded Pangeo project, a free, open-source Python system which provides multi-user login via JupyterHub and parallel analysis via Dask, both running in Docker containers orchestrated by Kubernetes. Data is stored in the Zarr format, a Cloud-friendly ndarray format that allows performant extraction of data by anyone without relying on data services like OPeNDAP. Interactive visual exploration of data on massive model grids is made possible by new tools in the Python PyViz ecosystem, which can render maps at screen resolution, dynamically updating on pan and zoom operations. Two example are given: (1) calculating the maximum water level at each grid cell from a 53GB, 720 time step, 9 million node triangular mesh ADCIRC simulation of Hurricane Ike; (2) creating a dashboard for visualizing data from the curvilinear orthogonal COAWST/ROMS forecast model.

Journal of Marine Science and Engineering↗
USGS2016

Deriving habitat models for northern long-eared bats from historical detection data: A case study using the Fernow Experimental Forest

The listing of the northern long-eared bat ( Myotis septentrionalis ) as federally threatened under the Endangered Species Act following severe population declines from white-nose syndrome presents considerable challenges to natural resource managers. Because the northern long-eared bat is a forest habitat generalist, development of effective conservation measures will depend on appropriate understanding of its habitat relationships at individual locations. However, severely reduced population sizes make gathering data for such models difficult. As a result, historical data may be essential in development of habitat models. To date, there has been little evaluation of how effective historical bat presence data, such as data derived from mist-net captures, acoustic detection, and day-roost locations, may be in developing habitat models, nor is it clear how models created using different data sources may differ. We explored this issue by creating presence probability models for the northern long-eared bat on the Fernow Experimental Forest in the central Appalachian Mountains of West Virginia using a historical, presence-only data set. Each presence data type produced outputs that were dissimilar but that still corresponded with known traits of the northern long-eared bat or are easily explained in the context of the particular data collection protocol. However, our results also highlight potential limitations of individual data types. For example, models from mist-net capture data only showed high probability of presence along the dendritic network of riparian areas, an obvious artifact of sampling methodology. Development of ecological niche and presence models for northern long-eared bat populations could be highly valuable for resource managers going forward with this species. We caution, however, that efforts to create such models should consider the substantial limitations of models derived from historical data, and address model assumptions.

West Virginia↗
USGS1998

Regional characterization of land cover using multiple sources of data

Many organizations require accurate intermediate-scale land-cover information for many applications, including modeling nutrient and pesticide runoff, understanding spatial patterns of biodiversity, land-use planning, and policy development. While many techniques have been successfully used to classify land cover in relatively small regions, there are substantial obstacles in applying these methods to large, multiscene regions. The purpose of this study was to generate and evaluate a large region land-cover classification product using a multiple-layer land-characteristics database approach. To derive land-cover information, mosaicked Landsat thematic mapper (TM) scenes were analyzed in conjunction with digital elevation data (and derived slope, aspect, and shaded relief), population census information, Defense Meteorological Satellite Program city lights data, prior land-use and land-cover data, digital line graph data, and National Wetlands Inventory data. Both leaf-on and leaf-off TM data sets were analyzed. The study area was U.S. Federal Region III, which includes the states of Pennsylvania, Virginia, Maryland, Delaware, and West Virginia. The general procedure involved (1) generating mosaics of multiple scenes of leaves-on TM data using histogram equalization methods; (2) clustering mosaics into 100 spectral classes using unsupervised classification; (3) interpreting and labeling spectral classes into approximately 15 land-cover categories (analogous to Anderson Level 1 and 2 classes) using aerial photographs; (4) developing decision-making rules and models using from one to several ancillary data layers to resolve confusion in spectral classes that represented two or more targeted land-cover categories; and (5) incorporating data from other sources (for example, leaf-off TM data and National Wetlands Inventory data) to yield a final land-cover product. Although standard accuracy assessments were not done, a series of consistency checks using available sources of land-cover information were conducted to evaluate the effectiveness of this approach for generating accurate land-cover information for large regions.

Photogrammetric Engineering and Remote Sensing↗
USGS2010

Development of inferential sensors for real-time quality control of water-level data for the Everglades Depth Estimation Network

The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and watersurface models designed to provide scientists, engineers, and water-resource managers with current (2000-present) water-depth information for the entire freshwater portion of the greater Everglades. The generation of EDEN waterlevel surfaces is derived from real-time data. Real-time data are automatically checked for outliers using minimum, maximum, and rate-of-change thresholds for each station. Smaller errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the gages. Correcting smaller errors in the data often is time consuming and water-level data may not be finalized for several months. To provide water-level surfaces on a daily basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous waterlevel data. A technology often used for industrial applications is “inferential sensor.” Rather than installing a redundant sensor to measure a process, such as an additional waterlevel gage, an inferential sensor, or virtual sensor, is developed that estimates the processes measured by the physical sensor. The advantage of an inferential sensor is that it provides a redundant signal to the sensor in the field but without exposure to environmental threats. In the event that a gage does malfunction, the inferential sensor provides an estimate for the period of missing data. The inferential sensor also can be used in the quality assurance and quality control of the data. Inferential sensors for gages in the EDEN network are currently (2010) under development. The inferential sensors will be automated so that the real-time EDEN data will continuously be compared to the inferential sensor signal and digital reports of the status of the real-time data will be sent periodically to the appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.

Florida↗
USGS1981

The role of change data in a land use and land cover map updating program

An assessment of current land use and a process for identifying and measuring change are needed to evaluate trends and problems associated with the use of our Nation's land resources. The U. S. Geological Survey is designing a program to maintain the currency of its land use and land cover maps and digital data base and to provide data on changes in our Nation's land use and land cover. Ways to produce and use change data in a map updating program are being evaluated. A dual role for change data is suggested. For users whose applications require specific polygon data on land use change, showing the locations of all individual category changes and detailed statistical data on these changes can be provided as byproducts of the map-revision process. Such products can be produced quickly and inexpensively either by conventional mapmaking methods or as specialized output from a computerized geographic information system. Secondly, spatial data on land use change are used directly for updating existing maps and statistical data. By incorporating only selected change data, maps and digital data can be updated in an efficient and timely manner without the need for complete and costly detailed remapping and redigitization of polygon data.

Pecora VII Symposium↗
USGS2015

The upper bound of abutment scour defined by selected laboratory and field data

The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, conducted a field investigation of abutment scour in South Carolina and used that data to develop envelope curves defining the upper bound of abutment scour. To expand upon this previous work, an additional cooperative investigation was initiated to combine the South Carolina data with abutment-scour data from other sources and evaluate the upper bound of abutment scour with the larger data set. To facilitate this analysis, a literature review was made to identify potential sources of published abutment-scour data, and selected data, consisting of 446 laboratory and 331 field measurements, were compiled for the analysis. These data encompassed a wide range of laboratory and field conditions and represent field data from 6 states within the United States. The data set was used to evaluate the South Carolina abutment-scour envelope curves. Additionally, the data were used to evaluate a dimensionless abutment-scour envelope curve developed by Melville (1992), highlighting the distinct difference in the upper bound for laboratory and field data. The envelope curves evaluated in this investigation provide simple but useful tools for assessing the potential maximum abutment-scour depth in the field setting.

South Carolina↗
USGS2012

Quantification of water-level variability effect on plant species populations using paleoecological and hydrological time series data

Soil cores provide valuable data on historical changes in vegetation and hydrologic conditions. Empirical models were developed to quantify the effect of meteorological and hydrologic forcing on plant species distributions over a 110-year period in Water Conservation Area 1 (WCA1) in the Florida Everglades, also known as the Arthur R. Marshall Loxahatchee National Wildlife Refuge. Empirical models that predict plant species distributions at sites within WCA1 were developed by linking temporally sparse seed bank data from soil cores with continuous multi-decadal daily meteorological and hydrologic time series data. The meteorological data included rainfall and maximum daily temperatures that spanned the entire study period of 110 years. The hydrologic data included stage data from two gages in WCA1 established in 1954. These stage data were hindcasted to be concurrent with the meteorological data by using correlation models that fit measured stages as a function of the meteorological parameters. The historical plant species data came from seven peat cores from WCA1. Different depths from each core were carbon-dated and assayed for relative percentages of 83 plant species using pollen counts. The oldest dates were more than 1,000 years old; however, only core data that overlapped the study period were used, for a total of 67 assays among the seven cores. Twenty-three of the species had ratios of at least 5 percent for one or more of the 67 assays, hereafter referred to as the "top23". Using the assays as input vectors, the top23 were grouped using the k-means clustering into four plant classes that represented the extent to which the various species have historically appeared together. This reduced the modeling problem to one of predicting the relative ratios of the four plant classes from the hindcasted stage time-series data. A separate empirical model was developed for each class using a multi-layer perceptron artificial neural network, which provides multivariate, nonlinear curve fitting. The models predicted the relative ratios of the classes, and the sums of the predictions are near 1. The coefficient of determination (R2) of the models varied from 0.87 to 0.96, indicating that the relative ratios of the plant classes are predictable, and therefore controllable, from stage forcing. Similar soil cores are available for the Coastal Plain of North Carolina and are planned for the Congaree National Park in South Carolina.

Florida↗
USGS2016

Mercury in fish and macroinvertebrates from New York's streams and rivers: A compendium of data sources

The U.S. Geological Survey has compiled a list of existing data sets, from selected sources, containing mercury (Hg) concentration data in fish and macroinvertebrate samples that were collected from flowing waters of New York State from 1970 through 2014. Data sets selected for inclusion in this report were limited to those that contain fish and (or) macroinvertebrate data that were collected across broad areas, cover relatively long time periods, and (or) were collected as part of a broader-scale (e.g. national) study or program. In addition, all data sets listed were collected, processed, and analyzed with documented methods, and contain critical sample information (e.g. fish species, fish size, Hg species) that is needed to analyze and interpret the reported Hg concentration data. Fourteen data sets, all from state or federal agencies, are listed in this report, along with selected descriptive information regarding each data source and data set contents. Together, these 14 data sets contain Hg and related data for more than 7,000 biological samples collected from more than 700 unique stream and river locations between 1970 and 2014.

New York↗
USGS2001

Transboundary movement of airborne pollutants — A methodology for integrating spaceborne images and ground based data

The availability of relevant and accurate environmental information is essential for environmental policy-makers. Recent improvements in satellite remote sensing technologies, groundbased monitors, and data access have resulted in the ability to observe and assess major atmospheric and ecological events around the world on a timely basis Each of these monitoring technologies reveals different and useful information, yet rarely are the resulting data sets used together in an integrated manner. The U.S. Environmental Protection Agency (EPA) and the United Nations Environment Programme (UNEP) Global Resource Information Database (GRID) office in Sioux Falls identified an environmental issue of global interest as a test case for applying an integrated approach: the transboundary movement of atmospheric pollutants. Transboundary movement of atmospheric pollutants has ramifications for human and environmental health, as well as economic impacts. As a result, it is the focus of many bilateral, regional, and international policy efforts. A central question with atmospheric pollutant transport is how to monitor pollutant movement and how to merge different monitoring datasets into useful information. Highly visible regional plumes of dust, smoke, and urban haze can be seen with satellite sensors, while ground-based monitoring of air pollutants such as fine particulates, SO2 , and toxics occurs at the local level. Integration of these two kinds of measurements allows the user to remotely observe large environmental effects in many areas of the world, while obtaining more detailed information from ground-based monitors. Hence, the combination of satellite-based sensor data and ground-based monitoring data promotes greater understanding of the movement of pollutants than either data set alone. Combined data sets are important for use by both scientists and international policy-makers. A standard methodology did not exist to guide and encourage integrated use of satellite images and ground-based data to monitor and understand major pollution events, such as air pollution. Thus, a small team was assembled to develop a methodology for the integration of satellite images and ground-based data. First, we conducted a literature and project review covering past and current integrated remote and ground-based data projects, a literature search of published work, and a search of data sets and technologies that could be used in a combined form. Second, based on this search and documentation, a general methodology was developed for using integrated spaceborne and ground-based data sets, intended as a guide for general scientists and policy-makers. Third, we found an existing project that was willing to be a pilot for testing the methodology: a U.S. EPANOAA project that was using aerial and ground-based sampling to learn more about the airborne sources of mercury deposition in the Florida Everglades. This document presents the results of the literature and project review, the complete methodology, and the outcome of the Florida Everglades pilot project.

Report↗
USGS1985

A relational approach to vector data structure conversion

The proliferation of geographic information systems and digital data bases is creating a need for efficient methods to convert data from one spatial data structure to another. One approach is to create ad hoc interfaces, with a potential of N(N-1) interfaces for N data structures. Using an intermediate data structure, at most 2N interfaces are required. An intermediate relational data structure is therefore proposed that takes the form of a set of normalized relations stored in a relational information management system. The advantages of this approach are found in the simplicity of the relational approach, and the availability of relational operators to be used as higher level tools, to convert from and to the relational data structure. The Relational Information Management System (RIM) is used for the ongoing research. In conjunction with the relational data structure, another higher level tool has been developed to cope with linked lists, tree structures, vectors, and matrices, which are not otherwise easily reduced. This data tracking system is programmable at a higher level, in a syntax that allows a concise expression of the desired restructuring. Output from this system can be further operated on by relational operators to arrive at the desired intermediate data structure. This, and other topology verification and checking tools, are visualized as part of a core system dedicated to the conversion and collation of spatial data from diverse origins.

Conference Paper↗
USGS2026

USGS Geochron—A database of geochronological and thermochronological dates and data—Technical documentation

Geochronological and thermochronological data are essential for constraining the timing and rates of geological processes, supporting geologic mapping, natural hazard assessment, and resource exploration. The U.S. Geological Survey (USGS) Geochron Database is a centralized, relational database that integrates USGS and State geological survey data in accordance with the National Geologic Mapping Act of 1992 and its reauthorizations. This report documents the structure and development of the database, including its standardized schema, controlled vocabularies, and protocols for compiling legacy and newly published data. The database is designed to adhere to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles and currently (2026) includes data from a wide range of geochronological and thermochronological methods. Public access is provided through the USGS Geochron Database Explorer, a browser-based geographic information system (GIS) interface, and through versioned data releases available on ScienceBase, which provide sample-level summary data and detailed analytical information. The USGS Geochron Database is structured to be extensible, supporting the inclusion of additional methods and data types as they are compiled. This format ensures long-term utility and aligns with the Mapping Act’s directive to create a national archive of geochronological information that adds interpretive value to geologic map data. Its design reflects a commitment to data transparency, scientific reproducibility, and national geoscience priorities.

Data Report↗
USGS2016

Archive of bathymetry and backscatter data collected in 2014 nearshore Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana

As part of the Barrier Island Monitoring Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off Breton and Gosier Islands, Louisiana, in July and August of 2014. To assist the United States Fish and Wildlife Service (USFWS) with restoration planning efforts, the USGS was tasked with answering fundamental questions about the physical environment of the southern Chandeleur Islands, including the geology, morphology, and oceanography. Baseline data needed to answer these questions were either insufficient or missing. The USGS conducted a comprehensive geologic investigation in the summer of 2014, collecting geophysical and sedimentological data. Breton Island, located at the southern end of the Chandeleur Island chain in southeastern Louisiana, was recognized as a natural, globally significant nesting sanctuary for several bird species and was established as the Breton National Wildlife Refuge (NWR) in 1904. The areal extent of Breton Island has diminished 90 percent since 1920. Land loss is attributed to ongoing relative sea-level rise, diminished sediment supply, and storm impacts. The bird population on Breton Island has also declined over the years, most notably after Hurricane George in 1998 and after Hurricane Katrina in 2015; the latter completely submerged the island. Despite decreasing habitable acreage, migratory seabirds continue to return and nest on Breton Island. To prevent the island from being submerged in the future, and to protect, stabilize, and provide more nesting and foraging areas for the bird population, the USFWS proposed a restoration effort to rebuild Breton Island to its pre-Katrina footprint. This data series serves as an archive of processed interferometric swath and single-beam bathymetry data, and side-scan sonar data, collected in the nearshore of Breton and Gosier Islands, NWR, Louisiana. The data were collected during two USGS cruises (USGS Field Activity Numbers 2014-314-FA and 2014-317-FA) in July and August 2014. Geographic information system data products include a 100-meter-cell-size interpolated bathymetry grid, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata. NOTE: These data are scientific in nature and are not to be used for navigation. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Louisiana↗
USGS2017

Coastal bathymetry data collected in 2013 from the Chandeleur Islands, Louisiana

As part of the Barrier Island Evolution Research Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys around the northern Chandeleur Islands, Louisiana, in July and August of 2013. The objective of the study is to better understand barrier-island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual timescales (1‒5 years). Collecting geophysical data will allow us to identify relationships between the geologic history of the island and its present day morphology and sediment distribution. This mapping effort was the third in a series of three planned surveys in this area. High resolution geophysical data collected in each of three consecutive years along this rapidly changing barrier island system will provide a unique time-series dataset that will significantly further the analyses and geomorphological interpretations of this and other coastal systems, improving our understanding of coastal response and evolution over short time scales (1‒5 years). This data series includes the geophysical data that were collected during two cruises (USGS Field Activity Numbers (FAN) 13BIM02, 13BIM03, and 13BIM04, in July 2013; and FANs 13BIM07 and 13BIM08 in August 2013) aboard the R/V Sallenger , the R/V Jabba Jaw , and the R/V Shark along the northern portion of the Chandeleur Islands, Breton National Wildlife Refuge, Louisiana. Primary data were acquired with the following equipment: (1) a Systems Engineering and Assessment, Ltd., SWATHplus interferometric sonar (468 kilohertz [kHz]), (2) an EdgeTech 424 (4‒24 kHz) chirp sub-bottom profiling system, and (3) two Odom Hydrographic Systems, Incorporated, Echotrach CV100 single beam echosounders. This data series report serves as an archive of processed interferometric swath and single-beam bathymetry data. Geographic information system data products include an interpolated digital elevation model, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata.

Louisiana↗
USGS2017

Sediment data collected in 2014 and 2015 from around Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana

Breton Island, located at the southern end of the Chandeleur Islands, supports one of Louisiana’s largest historical brown pelican ( Pelecanus occidentalis ) nesting colonies. Although the brown pelican was delisted as an endangered species in 2009, nesting areas are threatened by continued land loss and are extremely vulnerable to storm impacts. The U.S. Fish and Wildlife Service proposed to restore Breton Island to pre-Hurricane Katrina conditions through rebuilding the shoreface, dune, and back-barrier marsh environments. Prior to restoration, scientists from the U.S. Geological Survey’s (USGS) St. Petersburg Coastal and Marine Science Center Geologic and Morphologic Evolution of Coastal Margins project collected high-resolution geophysical (topography, bathymetry, and sub-bottom profiles) and sedimentologic data from around Breton Island to characterize the geologic framework of the island platform, nearshore, and shelf environments. These data will be used to characterize the geologic framework around Breton Island, identify potential borrow areas for restoration efforts, quantify seafloor change, and provide information for sediment transport and morphologic change models to assess island response to restoration and natural processes. This report, along with the accompanying USGS data release, serves as an archive of sediment data from vibracores, push cores, and submerged grab samples collected from around Breton and Gosier Islands, Louisiana, during two surveys conducted in July 2014 and January 2015 (USGS Field Activity Numbers 2014–314–FA and 2014–336–FA, respectively). Sedimentologic and stratigraphic metrics (for example, sediment texture or unit thicknesses) derived from these data can be used to ground-truth the geophysical data and characterize potential sand resources or can be incorporated into sediment transport or morphologic change models. Data products, including sample location tables, descriptive core logs, core photographs and x-radiographs, results of sediment grain-size analyses, and geographic information system data files with accompanying formal Federal Geographic Data Committee metadata can be downloaded from the accompanying data release.

Louisiana↗
USGS2017

Coastal single-beam bathymetry data collected in 2015 from the Chandeleur Islands, Louisiana

As part of the Louisiana Coastal Protection and Restoration Authority (CPRA) Barrier Island Comprehensive Monitoring Program, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a single-beam bathymetry survey around the Chandeleur Islands, Louisiana, in June 2015. The goal of the program is to provide long-term data on Louisiana’s barrier islands and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in this report, along with (1) USGS bathymetry data collected in 2013 as a part of the Barrier Island Evolution Research project covering the northern Chandeleur Islands, and (2) data collected in 2014 in collaboration with the Louisiana CPRA Barrier Island Comprehensive Monitoring Program around Breton Island, will be used to assess bathymetric change since 2006‒2007 as well as serve as a bathymetric control in supporting modeling of future changes in response to restoration and storm impacts. The survey area encompasses approximately 435 square kilometers of nearshore and back-barrier environments around Hewes Point, the Chandeleur Islands, and Curlew and Grand Gosier Shoals. This Data Series serves as an archive of processed single-beam bathymetry data, collected in the nearshore of the Chandeleur Islands, Louisiana, from June 17‒24, 2015, during USGS Field Activity Number 2015-317-FA. Geographic information system data products include a 200-meter-cell-size interpolated bathymetry grid, trackline maps, and xyz point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata.

Louisiana↗
USGS2006

Hydrologic and water-quality data, Honey Creek State Natural Area, Comal County, Texas, August 2001-September 2003

The U.S. Geological Survey collected rainfall, streamflow, evapotranspiration, and rainfall and stormflow water-quality data from seven sites in two adjacent watersheds in the Honey Creek State Natural Area, Comal County, Texas, during August 2001–September 2003, in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service, and the San Antonio Water System. Data collected during this period represent baseline hydrologic and water-quality conditions before proposed removal of ashe juniper ( Juniperus ashei ) from one of the two watersheds. Juniper removal is intended as a best-management practice to increase water quantity (aquifer recharge and streamflow) and to protect water quality. Continuous (5-minute interval) rainfall data are collected at four sites; continuous (5-minute interval) streamflow data are collected at three sites. Fifteen-minute averages of meteorological and solar-energy-related data recorded at two sites are used to compute moving 30-minute evapotranspiration values on the basis of the energy-balance Bowen ratio method. Periodic rainfall water-quality data are collected at one site and stormflow water-quality data at three sites. Daily rainfall, streamflow, and evapotranspiration totals are presented in tables; detailed data are listed in an appendix. Results of analyses of the periodic rainfall and stormflow water-quality samples collected during runoff events are summarized in the appendix; not all data types were collected at all sites nor were all data types collected during the entire 26-month period.

Texas↗
USGS2007

Enhanced Historical Land-Use and Land-Cover Data Sets of the U.S. Geological Survey

Historical land-use and land-cover data, available from the U.S. Geological Survey (USGS) for the conterminous United States and Hawaii, have been enhanced for use in geographic information systems (GIS) applications. The original digital data sets were created by the USGS in the late 1970s and early 1980s and were later converted by USGS and the U.S. Environmental Protection Agency (USEPA) to a geographic information system (GIS) format in the early 1990s. These data were made available on USEPA's Web site since the early 1990s and have been used for many national applications, despite minor coding and topological errors. During the 1990s, a group of USGS researchers made modifications to the data set for use in the National Water-Quality Assessment Program. These edited files have been further modified to create a more accurate, topologically clean, and seamless national data set. Several different methods, including custom editing software and several batch processes, were applied to create this enhanced version of the national data set. The data sets are included in this report in the commonly used shapefile and Tagged Image Format File (TIFF) formats. In addition, this report includes two polygon data sets (in shapefile format) representing (1) land-use and land-cover source documentation extracted from the previously published USGS data files, and (2) the extent of each polygon data file.

Data Series↗
USGS2008

Archive of digital boomer seismic reflection data collected during USGS field activity 96LCA04 in Lakes Mabel and Starr, Central Florida, August 1996

In August of 1996, the U.S. Geological Survey conducted geophysical surveys of Lakes Mabel and Starr, central Florida, as part of the Central Highlands Lakes project, which is part of a larger USGS Lakes and Coastal Aquifers (LCA) study. This report serves as an archive of unprocessed digital boomer seismic reflection data, trackline maps, navigation files, Geographic Information System (GIS) files, observer's logbook; and formal Federal Geographic Data Committee (FGDC) metadata. Filtered and gained (a relative increase in signal amplitude) digital images of the seismic profiles are also provided. Refer to the Acronyms page for expansions of acronyms and abbreviations used in this report. For detailed information about the hydrologic setting of Lake Starr and the interpretation of some of these seismic reflection data, see Swancar and others (2000) at http://fl.water.usgs.gov/publications/Abstracts/wri00_4030_swancar.html. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y format (Barry and others, 1975) and may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU). Example SU processing scripts and USGS software for viewing the SEG-Y files (Zihlman, 1992) are also provided. The USGS Florida Integrated Science Center (FISC) - St. Petersburg assigns a unique identifier to each cruise or field activity. For example, 96LCA04 tells us the data were collected in 1996 for the Lakes and Coastal Aquifers (LCA) study and the data were collected during the fourth field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. The boomer plate is an acoustic energy source that consists of capacitors charged to a high voltage and discharged through a transducer in the water. The transducer is towed on a sled floating on the water surface and when discharged emits a short acoustic pulse, or shot, which propagates through the water and sediment column. The acoustic energy is reflected at density boundaries (such as the seafloor or sediment layers beneath the lake bottom), detected by the receiver (a hydrophone streamer), and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (for example, 0.5 s) and recorded for specific intervals of time (for example, 100 ms). In this way, a two-dimensional (2-D) vertical image of the shallow geologic structure beneath the ship track is produced. Figure 1 displays the acquisition geometry. Refer to table 1 for a summary of acquisition parameters. Table 2 lists trackline statistics. Scanned images of the handwritten cruise logbook (1,020-KB PDF) is also provided as a PDF file. The unprocessed seismic data are stored in SEG-Y format (Barry and others, 1975). For a detailed description of the data format, refer to the SEG-Y Format page. See the How To Download SEG-Y Data page for download instructions. The printable profiles provided here are GIF images that were filtered and gained using Seismic Unix software. Refer to the Software page for details about the processing and examples of the processing scripts. The processed SEG-Y data were exported to Chesapeake Technology, Inc. (CTI) SonarWeb software to produce an interactive version of the seismic profile that allows the user to obtain a geographic location and depth from the profile for a curser position. This information is displayed in the status bar of the browser.

Florida↗