USGS ScienceSearch

Geology topics

Michael S. O'Donnell

Publications and source records attributed to Michael S. O'Donnell.

5 recordsLinked to original sources

Geospatial considerations for a multiorganizational, landscape-scale program

Geospatial data play an increasingly important role in natural resources management, conservation, and science-based projects. The management and effective use of spatial data becomes significantly more complex when the efforts involve a myriad of landscape-scale projects combined with a multiorganizational collaboration. There is sparse literature to guide users on this daunting subject; therefore, we present a framework of considerations for working with geospatial data that will provide direction to data stewards, scientists, collaborators, and managers for developing geospatial management plans. The concepts we present apply to a variety of geospatial programs or projects, which we describe as a “scalable framework” of processes for integrating geospatial efforts with management, science, and conservation initiatives. Our framework includes five tenets of geospatial data management: (1) the importance of investing in data management and standardization, (2) the scalability of content/efforts addressed in geospatial management plans, (3) the lifecycle of a geospatial effort, (4) a framework for the integration of geographic information systems (GIS) in a landscape-scale conservation or management program, and (5) the major geospatial considerations prior to data acquisition. We conclude with a discussion of future considerations and challenges.

Journal of Map & Geography Libraries

Large scale Wyoming transportation data: a resource planning tool

The U.S. Geological Survey Fort Collins Science Center created statewide roads data for the Bureau of Land Management Wyoming State Office using 2009 aerial photography from the National Agriculture Imagery Program. The updated roads data resolves known concerns of omission, commission, and inconsistent representation of map scale, attribution, and ground reference dates which were present in the original source data. To ensure a systematic and repeatable approach of capturing roads on the landscape using on-screen digitizing from true color National Agriculture Imagery Program imagery, we developed a photogrammetry key and quality assurance/quality control protocols. Therefore, the updated statewide roads data will support the Bureau of Land Management’s resource management requirements with a standardized map product representing 2009 ground conditions. The updated Geographic Information System roads data set product, represented at 1:4,000 and +/- 10 meters spatial accuracy, contains 425,275 kilometers within eight attribute classes. The quality control of these products indicated a 97.7 percent accuracy of aspatial information and 98.0 percent accuracy of spatial locations. Approximately 48 percent of the updated roads data was corrected for spatial errors of greater than 1 meter relative to the pre-existing road data. Twenty-six percent of the updated roads involved correcting spatial errors of greater than 5 meters and 17 percent of the updated roads involved correcting spatial errors of greater than 9 meters. The Bureau of Land Management, other land managers, and researchers can use these new statewide roads data set products to support important studies and management decisions regarding land use changes, transportation and planning needs, transportation safety, wildlife applications, and other studies.

Wyoming

Spatial mapping and attribution of Wyoming wind turbines, 2012

These data represent locations of wind turbines found within Wyoming as of August 2012. We assigned each wind turbine to a wind farm and, in these data, provide information about each turbine’s potential megawatt output, rotor diameter, hub height, rotor height, the status of the land ownership where the turbine exists, the county each turbine is located in, wind farm power capacity, the number of units currently associated with each wind farm, the wind turbine manufacturer and model, the wind farm developer, the owner of the wind farm, the current purchaser of power from the wind farm, the year the wind farm went online, and the status of its operation. Some of the attributes are estimates based on the information we found via the American Wind Energy Association and other on-line reports. The locations are derived from National Agriculture Imagery Program (2009 and 2012) true color aerial photographs and have a positional accuracy of approximately +/-5 meters. These data will provide a planning tool for wildlife- and habitat-related projects underway at the U.S. Geological Survey’s Fort Collins Science Center and other government and non-government organizations. Specifically, we will use these data to support quantifying disturbances of the landscape as related to wind energy as well as to quantify indirect disturbances to flora and fauna. This data set represents an update to a previous version by O’Donnell and Fancher (2010).

Wyoming

Metadata Wizard: an easy-to-use tool for creating FGDC-CSDGM metadata for geospatial datasets in ESRI ArcGIS Desktop

Creating compliant metadata for scientific data products is mandated for all federal Geographic Information Systems professionals and is a best practice for members of the geospatial data community. However, the complexity of the The Federal Geographic Data Committee’s Content Standards for Digital Geospatial Metadata, the limited availability of easy-to-use tools, and recent changes in the ESRI software environment continue to make metadata creation a challenge. Staff at the U.S. Geological Survey Fort Collins Science Center have developed a Python toolbox for ESRI ArcDesktop to facilitate a semi-automated workflow to create and update metadata records in ESRI’s 10.x software. The U.S. Geological Survey Metadata Wizard tool automatically populates several metadata elements: the spatial reference, spatial extent, geospatial presentation format, vector feature count or raster column/row count, native system/processing environment, and the metadata creation date. Once the software auto-populates these elements, users can easily add attribute definitions and other relevant information in a simple Graphical User Interface. The tool, which offers a simple design free of esoteric metadata language, has the potential to save many government and non-government organizations a significant amount of time and costs by facilitating the development of The Federal Geographic Data Committee’s Content Standards for Digital Geospatial Metadata compliant metadata for ESRI software users. A working version of the tool is now available for ESRI ArcDesktop, version 10.0, 10.1, and 10.2 (downloadable at http:/www.sciencebase.gov/metadatawizard ).

Open-File Report

Spatial mapping and attribution of Wyoming wind turbines

This Wyoming wind-turbine data set represents locations of wind turbines found within Wyoming as of August 1, 2009. Each wind turbine is assigned to a wind farm. For each turbine, this report contains information about the following: potential megawatt output, rotor diameter, hub height, rotor height, land ownership, county, wind farm power capacity, the number of units currently associated with its wind farm, the wind turbine manufacturer and model, the wind farm developer, the owner of the wind farm, the current purchaser of power from the wind farm, the year the wind farm went online, and the status of its operation. Some attributes are estimates based on information that was obtained through the American Wind Energy Association and miscellaneous online reports. The locations are derived from August 2009 true-color aerial photographs made by the National Agriculture Imagery Program; the photographs have a positional accuracy of approximately ?5 meters. The location of wind turbines under construction during the development of this data set will likely be less accurate than the location of turbines already completed. The original purpose for developing the data presented here was to evaluate the effect of wind energy development on seasonal habitat used by greater sage-grouse. Additionally, these data will provide a planning tool for the Wyoming Landscape Conservation Initiative Science Team and for other wildlife- and habitat-related projects underway at the U.S. Geological Survey's Fort Collins Science Center. Specifically, these data will be used to quantify disturbance of the landscape related to wind energy as well as quantifying indirect disturbances to flora and fauna. This data set was developed for the 2010 project 'Seasonal predictive habitat models for greater sage-grouse in Wyoming.' This project's spatially explicit seasonal distribution models of sage-grouse in Wyoming will provide resource managers with tools for conservation planning. These specific data are being used for assessing the effect of disturbance resulting from wind energy development within Wyoming on sage-grouse populations.

Data Series