Geology topics

Peter N. Schweitzer

Publications and source records attributed to Peter N. Schweitzer.

6 recordsLinked to original sources

USGS2016

Geology and mineral resources of the North-Central Montana Sagebrush Focal Area: Chapter D in Mineral resources of the Sagebrush Focal Areas of Idaho, Montana, Nevada, Oregon, Utah, and Wyoming

Summary The U.S. Department of the Interior has proposed to withdraw approximately 10 million acres of Federal lands from mineral entry (subject to valid existing rights) from 12 million acres of lands defined as Sagebrush Focal Areas (SFAs) in Idaho, Montana, Nevada, Oregon, Utah, and Wyoming (for further discussion on the lands involved see Scientific Investigations Report 2016–5089–A). The purpose of the proposed action is to protect the greater sage-grouse ( Centrocercus urophasianus ) and its habitat from potential adverse effects of locatable mineral exploration and mining. The U.S. Geological Survey Sagebrush Mineral-Resource Assessment (SaMiRA) project was initiated in November 2015 and supported by the Bureau of Land Management to (1) assess locatable mineral-resource potential and (2) to describe leasable and salable mineral resources for the seven SFAs and Nevada additions. This chapter summarizes the current status of locatable, leasable, and salable mineral commodities and assesses the potential of locatable minerals in the North-Central Montana SFA. The proposed withdrawal area that is evaluated in this report is located in north-central Montana, and includes parts of Fergus, Petroleum, Phillips, and Valley Counties.

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USGS2015

A case study of data integration for aquatic resources using semantic web technologies

Use cases, information modeling, and linked data techniques are Semantic Web technologies used to develop a prototype system that integrates scientific observations from four independent USGS and cooperator data systems. The techniques were tested with a use case goal of creating a data set for use in exploring potential relationships among freshwater fish populations and environmental factors. The resulting prototype extracts data from the BioData Retrieval System, the Multistate Aquatic Resource Information System, the National Geochemical Survey, and the National Hydrography Dataset. A prototype user interface allows a scientist to select observations from these data systems and combine them into a single data set in RDF format that includes explicitly defined relationships and data definitions. The project was funded by the USGS Community for Data Integration and undertaken by the Community for Data Integration Semantic Web Working Group in order to demonstrate use of Semantic Web technologies by scientists. This allows scientists to simultaneously explore data that are available in multiple, disparate systems beyond those they traditionally have used.

Open-File Report↗

USGS2015

Community for Data Integration 2013 Annual Report

The U.S. Geological Survey (USGS) conducts earth science to help address complex issues affecting society and the environment. In 2006, the USGS held the first Scientific Information Management Workshop to bring together staff from across the organization to discuss the data and information management issues affecting the integration and delivery of earth science research and investigate the use of “communities of practice” as mechanisms to share expertise about these issues. Out of this effort emerged the Council for Data Integration, which was conceived as an official organizational function that would help guide data integration activities and formalize communities of practice into working groups. However by 2009, it became apparent that many members of the council had an interest in developing data integration solutions and sharing expertise in a less formal grassroots perspective, thus transforming the “Council” into a “Community” for Data Integration (CDI). Today, the CDI represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the USGS and the CDI community. The CDI fosters an environment for collaboration and sharing by bringing together expertise from external partners and representatives across USGS who are involved in research, data management, and information technology. Membership is voluntary and open to USGS employees and other individuals and organizations willing to contribute to the community (if interested, contact cdi@usgs.gov). The purpose of the CDI is to advance understanding of Earth systems through enhanced use of data and information including associated tools and techniques provide a forum for people doing work with data integration to come together to share ideas as well as learn new skills and techniques, and grow overall USGS capabilities with data and information by increasing visibility of the work of many people throughout the USGS and the CDI community. To achieve these goals, the CDI operates within four applied areas: monthly forums, annual workshop/webinar series, working groups, and projects. The monthly forums, also known as the Opportunity/Challenge of the Month, provide an open dialogue to share and learn about data integration efforts or to present problems that invite the Community to offer solutions, advice, and support. Since 2010, the CDI has also sponsored annual workshops/webinar series to encourage the exchange of ideas, sharing of activities, presentations of current projects, and networking among members. Stemming from common interests, the working groups are focused on efforts to address data management and technical 2 challenges, including the development of standards and tools, improving interoperability and information infrastructure, and data preservation within USGS and its partners. The growing support for the activities of the working groups led to the CDI’s first formal request for proposals (RFP) process in 2013 to fund projects that produced tangible products. Today the CDI continues to hold an annual RFP that create data management tools and practices, collaboration tools, and training in support of data integration and delivery.

Open-File Report↗

USGS1995

Monthly average polar sea-ice concentration

The data contained in this CD-ROM depict monthly averages of sea-ice concentration in the modern polar oceans. These averages were derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) instruments aboard satellites of the U.S. Air Force Defense Meteorological Satellite Program from 1978 through 1992. The data are provided as 8-bit images using the Hierarchical Data Format (HDF) developed by the National Center for Supercomputing Applications.

Data Series↗

USGS1994

ANALOG: a program for estimating paleoclimate parameters using the method of modern analogs

Beginning in the 1970s with CLIMAP, paleoclimatologists have been trying to derive quantitative estimates of climatic parameters from the sedimentary record. In general the procedure is to observe the modern distribution of some component of surface sediment that depends on climate, find an empirical relationship between climate and the character of sediments, then extrapolate past climate by studying older sediments in the same way. Initially the empirical relationship between climate and components of the sediment was determined using a multiple regression technique (Imbrie and Kipp, 1971). In these studies sea-floor sediments were examined to determine the percentage of various species of planktonic foraminifera present in them. Supposing that the distribution of foraminiferal assemblages depended strongly on the extremes of annual sea-surface temperature (SST), the foraminiferal assemblages (refined through use of varimax factor analysis) were regressed against the average SST during the coolest and warmest months of the year. The result was a set of transfer functions, equations that could be used to estimate cool and warm SST from the faunal composition of a sediment sample. Assuming that the ecological preference of the species had remained constant throughout the last several hundred thousand years, these transfer functions could be used to estimate SSTs during much of the late Pleistocene. Hutson (1980) and Overpeck, Webb, and Prentice (1985) proposed an alternative approach to estimating paleoclimatic parameters. Their 'method of modern analogs' revolved not around the existence of a few climatically-sensitive faunal assemblages but rather on the expectation that similar climatic regimes should foster similar faunal and floral assemblages. From a large pool of modern samples, those few are selected whose faunal compositions are most similar to a given fossil sample. Paleoclimate estimates are derived using the climatic character of only the most similar modern samples, the modern analogs of the fossil sample. This report describes how to use the program ANALOG to carry out the method of modern analogs. It is assumed that the user has faunal census estimates of one or more fossil samples, and one or more sets of faunal data from modern samples. Furthermore, the user must understand the taxonomic categories represented in the data sets, and be able to recognize taxa that are or may be considered equivalent in the analysis. ANALOG provides the user with flexibility in input data format, output data content, and choice of distance measure, and allows the user to determine which taxa from each modern and fossil data file are compared. Most of the memory required by the program is allocated dynamically, so that, on systems that permit program segments to grow, the program consumes only as many system resources as are needed to accomplish its task.

Open-File Report↗

USGS1993

Modern average global sea-surface temperature

The data contained in this data set are derived from the NOAA Advanced Very High Resolution Radiometer Multichannel Sea Surface Temperature data (AVHRR MCSST), which are obtainable from the Distributed Active Archive Center at the Jet Propulsion Laboratory (JPL) in Pasadena, Calif. The JPL tapes contain weekly images of SST from October 1981 through December 1990 in nine regions of the world ocean: North Atlantic, Eastern North Atlantic, South Atlantic, Agulhas, Indian, Southeast Pacific, Southwest Pacific, Northeast Pacific, and Northwest Pacific. This data set represents the results of calculations carried out on the NOAA data and also contains the source code of the programs that made the calculations. The objective was to derive the average sea-surface temperature of each month and week throughout the whole 10-year series, meaning, for example, that data from January of each year would be averaged together. The result is 12 monthly and 52 weekly images for each of the oceanic regions. Averaging the images in this way tends to reduce the number of grid cells that lack valid data and to suppress interannual variability.

Data Series↗