Fish and Wildlife Service Great Lakes Information Management System (GLIMS) : contractor guidelines
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The use of commercial geographic information system software to process large raster datasets of terrain elevation, population, land cover, vegetation, soils, temperature, and rainfall requires both projection from spherical coordinates to plane coordinate systems and transformation from one plane system to another. Decision support systems deliver information resulting in knowledge that assists in policies, priorities, or processes. This paper presents an approach to handling the problems of raster dataset projection and transformation through the development of a Web-enabled decision support system to aid users of transformation processes with the selection of appropriate map projections based on data type, areal extent, location, and preservation properties.
Digital flood-inundation maps for a 1.7-mile reach of the Leaf River were developed by the U.S. Geological Survey (USGS) in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District. The Leaf River study reach extends from just upstream of the U.S. Highway 11 crossing to just downstream of East Hardy/South Main Street and separates the cities of Hattiesburg and Petal, Mississippi. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent of flooding corresponding to selected water-surface elevations (stages) at the USGS streamgage at Leaf River at Hattiesburg, Mississippi (02473000). Current conditions at the USGS streamgage may be obtained through the National Water Information System Web site at http://waterdata.usgs.gov/ms/nwis/uv/?site_no=02473000&PARAmeter_cd=00065,00060 . In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood-warning system ( http://water.weather.gov/ahps/ ). The NWS forecasts flood hydrographs at many places that are often collocated at USGS streamgages. The forecasted peak-stage information, available on the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relations at the Leaf River at Hattiesburg, Mississippi, streamgage and documented high-water marks from recent and historical floods. The hydraulic model was then used to determine 13 water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water-surface elevation at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model [derived from Light Detection and Ranging (LiDAR) data having a 0.6-foot vertical accuracy and 9.84-foot horizontal resolution] in order to delineate the area flooded at each 1-foot increment of stream stage. The availability of these maps, when combined with real-time stage information from USGS streamgages and forecasted stream stage from the NWS, provides emergency management personnel and residents with critical information during flood-response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.
The diversity of geophysical methods and datatypes, as well as the isolated nature of various specialties (e.g., electromagnetic, seismic, potential fields) leads to a profusion of separate data file formats and documentation conventions. This can hinder cooperation and reduce the impact of datasets researchers have invested in heavily to collect and prepare. An open, portable, and well-supported community data standard could greatly improve the interoperability, transferability, and long-term archival of geophysical data. Airborne geophysical methods particularly need an open and accessible data standard, and they exemplify the complexity that is common in geophysical datasets where critical auxiliary information on the survey and system parameters are required to fully utilize and understand the data. Here, we propose a new Geophysical Standard, termed the GS convention, that leverages the well-established and widely used NetCDF file format and builds on the Climate and Forecasts (CF) metadata convention. We also present an accompanying open-source Python package, GSPy, to provide methods and workflows for building the GS-standardized NetCDF files, importing and exporting between common data formats, preparing input files for geophysical inversion software, and visualizing data and inverted models. By using the NetCDF format, handled through the Xarray Python package, and following the CF conventions, we standardize how metadata is recorded and directly stored with the data, from general survey and system information down to specific variable attributes. Utilizing the hierarchical nature of NetCDF, GS-formatted files are organized with a root Survey group that contains global metadata about the geophysical survey. Data are then organized into subgroups beneath Survey and are categorized as Tabular or Raster depending on the geometry and point of origin for the data. Lastly, the standard ensures consistency in constructing and tracking coordinate reference systems, which is vital for accurate portability and analysis. Development and adoption of a NetCDF-based data standard for geophysical surveys can greatly improve how these complex datasets are shared and utilized, making the data more accessible to a broader science community. The architecture of GSPy can be easily transferred to additional geophysical datatypes and methods in future releases.
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.
In order to be effective, information must be placed in the proper context and organized in a manner that is logical and (preferably) standardized. Recently, invasive alien species (IAS) scientists have begun to create online networks to share their information concerning IAS prevention and control. At a special networking session at the Beijing International Symposium on Biological Invasions, an online Eastern Asia-North American IAS Information Network (EA-NA Network) was proposed. To prepare for the development of this network, and to provide models for other regional collaborations, we compare four examples of global, regional, and national online IAS information networks: the Global Invasive Species Information Network, the Invasives Information Network of the Inter-American Biodiversity Information Network, the Chinese Species Information System, and the Invasive Species Information Node of the US National Biological Information Infrastructure. We conclude that IAS networks require a common goal, dedicated leaders, effective communication, and broad endorsement, in order to obtain sustainable, long-term funding and long-term stability. They need to start small, use the experience of other networks, partner with others, and showcase benefits. Global integration and synergy among invasive species networks will succeed with contributions from both the top-down and the bottom-up. ?? 2006 Springer.
As part of a program to support development of pesticide management plans for Indian Reservations, the U.S. Geological Survey has been working in cooperation with the U.S. Environmental Protection Agency to make selected information available to the Tribes or in a format easier for the Tribes to use. As a result of this program, four digital data sets related to the geology or hydrology of the Standing Rock Indian Reservation were produced as part of this report. The digital data sets are based on maps published in 1982 at the 1:250,000 scale in "Geohydrology of the Standing Rock Indian Reservation, North and South Dakota," U.S. Geological Survey Hydrologic Investigations Atlas HA-644 by L.W. Howells. The digital data sets were created by 1) scanning the appropriate map to create an image file, 2) registering the image file to real-world coordinates, 3) creating a new image file rectified to real-world coordinates, and 4) digitizing of the features of interest using the rectified image as a guide. As digital data sets, the information can be used in a geographic information system in combination with other information to help develop a pesticide management plan.
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.
The Pu'u 'O'o-Kupaianaha eruption started on January 3, 1983. The ensuing 20-year period of nearly continuous eruption is the longest at Kilauea Volcano since the famous lava-lake activity of the 19th century. No rift-zone eruption in more than 600 years even comes close to matching the duration and volume of activity of these past two decades. Fortunately, such a landmark event came during a period of remarkable technological advancements in volcano monitoring. When the eruption began, the Global Positioning System (GPS) and the Geographic Information System (GIS) were but glimmers on the horizon, broadband seismology was in its infancy, and the correlation spectrometer (COSPEC), used to measure SO2 flux, was still very young. Now, all of these techniques are employed on a daily basis to track the ongoing eruption and construct models about its behavior. The 12 chapters in this volume, written by present or past Hawaiian Volcano Observatory staff members and close collaborators, celebrate the growth of understanding that has resulted from research during the past 20 years of Kilauea's eruption. The chapters range widely in emphasis, subject matter, and scope, but all present new concepts or important modifications of previous ideas - in some cases, ideas long held and cherished.
Streamflow data, water-surface-elevation profiles derived from a Hydrologic Engineering Center River Analysis System hydraulic model, and geographical information system digital elevation models were used to develop a set of 18 flood-inundation maps for an approximately 5-mile reach of the West Branch Susquehanna River near the Borough of Jersey Shore, Pa. The inundation maps were created by the U.S. Geological Survey in cooperation with the Susquehanna River Basin Commission and Lycoming County as part of an ongoing effort by the National Oceanic and Atmospheric Administration's National Weather Service to focus on continued improvements to the flood forecasting and warning abilities in the Susquehanna River Basin and to modernize flood-forecasting methodologies. The maps, ranging from 23.0 to 40.0 feet in 1-foot increments, correspond to river stage at the U.S. Geological Survey streamgage 01549760 at Jersey Shore. The electronic files used to develop the maps were provided to the National Weather Service for incorporation into their Advanced Hydrologic Prediction Service website. The maps are displayed on this website, which serves as a web-based floodwarning system, and can be used to identify areas of predicted flood inundation associated with forecasted flood-peak stages. During times of flooding or predicted flooding, these maps can be used by emergency managers and the public to take proactive steps to protect life and reduce property damage caused by floods.
The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature resulting from changes forecast for air temperature and precipitation.
Describes the APSRS, an automated information system for conventional aerial photography projects, established after the formation of the National Cartographic Information Center in the US Geological Survey in 1974. -after Author
Overview The Geospatial Semantic Web (GSW) is an emerging technology that uses the Internet for more effective knowledge engineering and information extraction. Among the aims of the GSW are to structure the semantic specifications of data to reduce ambiguity and to link those data more efficiently. The data are stored as triples, the basic data unit in graph databases, which are similar to the vector data model of geographic information systems (GIS); that is, a node-edge-node model that forms a graph of semantically related information. The GSW is supported by emerging technologies such as linked geospatial data, described below, that enable it to store and manage geographical data that require new cartographic methods for visualization. This report describes a map that can interact with linked geospatial data using a simulation of a data query approach called the browsable graph to find information that is semantically related to a subject of interest, visualized using the Data Driven Documents (D3) library. Such a semantically enabled map functions as a map knowledge base (MKB) (Varanka and Usery, 2017). A MKB differs from a database in an important way. The central element of a triple, alternatively called the edge or property, is composed of a logic formalization that structures the relation between the first and third parts, the nodes or objects. Node-edge-node represents the graphic form of the triple, and the subject-property-object terms represent the data structure. Object classes connect to build a federated graph, similar to a network in visual form. Because the triple property is a logical statement (a predicate), the data graph represents logical propositions or assertions accepted to be true about the subject matter. These logical formalizations can be manipulated to calculate new triples, representing inferred logical assertions, from the existing data. To demonstrate a MKB system, a technical proof-of-concept is developed that uses geographically attributed Resource Description Framework (RDF) serializations of linked data for mapping. The proof-of-concept focuses on accessing triple data from visual elements of a geographic map as the interface to the MKB. The map interface is embedded with other essential functions such as SPARQL Protocol and RDF Query Language (SPARQL) data query endpoint services and reasoning capabilities of Apache Marmotta (Apache Software Foundation, 2017). An RDF database of the Geographic Names Information System (GNIS), which contains official names of domestic feature in the United States, was linked to a county data layer from The National Map of the U.S. Geological Survey. The county data are part of a broader Government Units theme offered to the public as Esri shapefiles. The shapefile used to draw the map itself was converted to a geographic-oriented JavaScript Object Notation (JSON) (GeoJSON) format and linked through various properties with a linked geodata version of the GNIS database called “GNIS–LD” (Butler and others, 2016; B. Regalia and others, University of California-Santa Barbara, written commun., 2017). The GNIS–LD files originated in Terse RDF Triple Language (Turtle) format but were converted to a JSON format specialized in linked data, “JSON–LD” (Beckett and Berners-Lee, 2011; Sorny and others, 2014). The GNIS–LD database is composed of roughly three predominant triple data graphs: Features, Names, and History. The graphs include a set of namespace prefixes used by each of the attributes. Predefining the prefixes made the conversion to the JSON–LD format simple to complete because Turtle and JSON–LD are variant specifications of the basic RDF concept. To convert a shapefile into GeoJSON format to capture the geospatial coordinate geometry objects, an online converter, Mapshaper, was used (Bloch, 2013). To convert the Turtle files, a custom converter written in Java reconstructs the files by parsing each grouping of attributes belonging to one subject and pasting the data into a new file that follows the syntax of JSON–LD. Additionally, the Features file contained its own set of geometries, which was exported into a separate JSON–LD file along with its elevation value to form a fourth file, named “features-geo.json.” Extracted data from external files can be represented in HyperText Markup Language (HTML) path objects. The goal was to import multiple JSON–LD files using this approach.
In this analysis we demonstrate how preferred fish habitat can be predicted and mapped for juveniles of two Alaskan groundfish species – Pacific halibut ( Hippoglossus stenolepis ) and flathead sole ( Hippoglossoides elassodon ) – at five sites (Kiliuda Bay, Izhut Bay, Port Dick, Aialik Bay, and the Barren Islands) in the central Gulf of Alaska. The method involves using geographic information system (GIS) software to extract appropriate information from National Ocean Service (NOS) smooth sheets that are available from NGDC (the National Geophysical Data Center). These smooth sheets are highly detailed charts that include more soundings, substrates, shoreline and feature information than the more commonly-known navigational charts. By bringing the information from smooth sheets into a GIS, a variety of surfaces, such as depth, slope, rugosity and mean grain size were interpolated into raster surfaces. Other measurements such as site openness, shoreline length, proportion of bay that is near shore, areas of rocky reefs and kelp beds, water volumes, surface areas and vertical cross-sections were also made in order to quantify differences between the study sites. Proper GIS processing also allows linking the smooth sheets to other data sets, such as orthographic satellite photographs, topographic maps and precipitation estimates from which watersheds and runoff can be derived. This same methodology can be applied to larger areas, taking advantage of these free data sets to describe predicted groundfish essential fish habitat (EFH) in Alaskan waters.
The purpose of this research was to develop a model that could be used to provide a spatial representation of uneven-aged silvicultural treatments on forest crown area. We began by developing species-specific linear regression equations relating tree DBH to crown area for eight bottomland tree species at White River National Wildlife Refuge, Arkansas, USA. The relationships were highly significant for all species, with coefficients of determination (r(2)) ranging from 0.37 for Ulmus crassifolia to nearly 0.80 for Quercus nuttalliii and Taxodium distichum. We next located and measured the diameters of more than 4000 stumps from a single tree-group selection timber harvest. Stump locations were recorded with respect to an established gl id point system and entered into a Geographic Information System (ARC/INFO). The area occupied by the crown of each logged individual was then estimated by using the stump dimensions (adjusted to DBHs) and the regression equations relating tree DBH to crown area. Our model projected that the selection cuts removed roughly 300 m(2) of basal area from the logged sites resulting in the loss of approximate to 55 000 m(2) of crown area. The model developed in this research represents a tool that can be used in conjunction with remote sensing applications to assist in forest inventory and management, as well as to estimate the impacts of selective timber harvest on wildlife.
Total nitrogen and phosphorous loads were estimated for 5,430 major point-source facilities (all types) and 11,537 minor wastewater treatment facilities discharging to streams in the conterminous United States during 2012. Facilities classified as a major discharger are typically a facility that discharges greater than one million gallons of water per day however some industrial facilities are classified as a major based on specific criteria developed by the U.S. Environmental Protection Agency (EPA) and the National Pollutant Discharge Elimination System state program. Data documenting discharge information from point sources were obtained from the EPA’s Integrated Compliance Information System (ICIS) and Permit Compliance System (PCS). When available, actual nutrient concentration measurements were used to calculate point-source loads. In the many cases in which concentration data were not available in either the ICIS or PCS databases, typical pollutant concentrations (TPCs) were developed using data from similar facilities. A new method for calculating TPCs was implemented that allows varying amounts of nutrient concentration data and (or) varying numbers of facilities to determine TPCs. This new method minimized the effect that any single facility discharging extremely large nutrient concentrations had on resultant TPC values. Because of the smaller TPC values from this new TPC method, the total nutrient load for many states was reduced compared to previous TPC methods. Major wastewater treatment facilities are the largest contributor of nutrient loads to streams even though there are almost three times as many minor wastewater treatment facilities. Specifically, 4,218 major wastewater treatment facilities account for 94 percent of the total nitrogen load for the conterminous United States, whereas 11,397 minor wastewater treatment facilities contribute 6 percent of the total nitrogen load. Total phosphorous loads are similarly divided among major (93 percent) and minor (7 percent) wastewater treatment facilities. Total nitrogen loads, including all facility types, primarily are from wastewater treatment facilities and some petroleum refining facilities. Total phosphorous loads also are primarily from wastewater treatment facilities, but several manufacturing facilities such as corn milling, pulp and paper mills, and industrial chemical facilities also contribute to total phosphorous loads.
In parts of Connecticut and Massachusetts, foundations of some homes are cracking and crumbling. Failing foundations can reduce the market value of a home and lifting a house to replace and repour a foundation is an expensive undertaking. In response, some homeowners are defaulting on their mortgages and abandoning their homes. The culprit is pyrrhotite, which occurs in construction aggregate (crushed stone) that was used as a filler in concrete. When pyrrhotite is naturally exposed to water and oxygen, it breaks down to produce sulfuric acid and secondary minerals, including gypsum, which have larger volumes than the pyrrhotite they replace. The expanded volume of the secondary minerals cracks and degrades concrete. Pyrrhotite occurs in rocks in many areas of the United States. To help assess the national risk of pyrrhotite in aggregate, the fiscal year 2019 appropriations bill for the U.S. Geological Survey’s (USGS) Mineral Resources Program allocated funds to develop a map showing the distribution of pyrrhotite across the United States. The purpose of this fact sheet is to (1) present a nationwide map that shows where pyrrhotite may occur in rocks in the United States, (2) describe and discuss the factors that control the presence and abundance of pyrrhotite in rocks, (3) provide information on geographic information system datasets that deliver more detailed information on these distributions, and (4) describe U.S. and international standards on aggregate that are designed to prevent failing concrete. While this map and fact sheet provide general information about the possible distribution of pyrrhotite in the United States, they are no substitute for site-specific characterization and quality control programs designed to ensure that aggregate used in concrete is of appropriate quality for its intended purpose.
This CD-ROM contains sidescan-sonar imagery, sub-bottom reflection profiles, and an interpretive map derived from these data. These data were collected in Lake Mohave, a reservoir behind the Davis Dam and below the Hoover Dam on the Colorado River. These data are veiwable within an Environmental system Research Institute, Inc. (ESRI) Geographic Information system (GIS) ArcView 3.2 project file stored on this CD-ROM