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Data collected monthly from urbanized area transit systems. The Monthly module includes a limited set of key indicators reported by transit properties. Data is reported on a monthly basis, by mode and type of service, for a calendar year. The four data items included are: Unlinked Passenger Trips, Vehicle Revenue Miles, Vehicle Revenue Hours, and Vehicles Operated in Maximum Service (Peak Vehicles). Monthly data are reported by mode and type of service.

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The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the Universal Transverse Mercator Coordinate System (ZONE 18N) and projection. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.

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The goal of the Global Land Data Assimilation System (GLDAS) is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes (Rodell et al., 2004a). The software, which has been streamlined and parallelized by the Land Information System (LIS) sister project, drives multiple, offline (not coupled to the atmosphere) land surface models, integrates a huge quantity of observation based data, executes globally at high resolutions (2.5-degrees to 1 km), and is capable of producing results in near-real time. A vegetation-based tiling approach is used to simulate sub-grid scale variability, with a 1-km global vegetation dataset as its basis. Soil and elevation parameters are based on high resolution global datasets. Observation-based precipitation and downward radiation products and the best available analyses from atmospheric data assimilation systems are employed to force the models. Intercomparison and validation of these products is being performed with the aim of identifying an optimal forcing scheme. Data assimilation techniques for incorporating satellite based hydrological products, including snow cover and water equivalent, soil moisture, surface temperature, and leaf area index, are now being implemented as part of a follow-on project funded by the NASA Energy and Water Cycle Study (NEWS) Initiative. The high-quality, global land surface fields provided by GLDAS support several current and proposed weather and climate prediction, water resources applications, and water cycle investigations. The project has resulted in a massive archive of modeled and observed, global, surface meteorological data, parameter maps, and output which includes 1-degree and 0.25-degree resolution 1979-present simulations of the Noah, CLM, VIC, and Mosaic land surface models. For more information visit: http://ldas.gsfc.nasa.gov/gldas/ For data access visit: http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings

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The Employee Skills Tracking System (ESTS) application is used to track the expertise available in each section of the Criminal Division along with contact information for the individuals and describing their expertise. The application produces an Experti

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The discovery of oil within the Swanson River Field by the Richfield Oil Corp. on July 19, 1957 fused the words oil and Kenai into almost synonymous terms. Although clouds of impending conflict had been building for some time, it was following discovery that moose and oil became something akin to incendiary icons hotly debated not only in the halls of Congress and the upper echelon of the Eisenhower Administration including the Interior Department, but the Alaska State Legislature, an elite corps of Anchorage businessmen, coalition of various national conservation groups as well as an assortment of various politicos, hardened homesteaders and just plain folk at the local levelincluding the then Kenai National Moose Range Refuge Manager and staff. Residents of the Kenai Peninsula were suddenly thrust into a rapidly progressing oil boom with an industrial behemoth which, at best, it poorly understood and was illprepared to support. Social and economic conditions in the Kenai, Soldotna and Nikiski then Nikishka areas were transformed overnight from a predominately fisheries based seasonal economy to one of constantly flowing fast cash, call girls and correspondingly inflated real estate values.

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A large body of scientific study over the last thirty years has resulted in ever increasing appreciation of the value of marshes and other wetlands as valuable natural resources. This study details investigations made by the University of Maryland in 19791981 into a number of these processes identified as possible factors in the disappearance of brackish tidal marshlands in Dorchester County, Maryland. The primary objectives of this study were 1 To determine the causes of marsh loss at Blackwater National Wildlife Refuge 2 To make recommendations based on the findings for proper management practices.

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To ensure an accurate sampling frame for its Law Enforcement Management and Administrative Statistics (LEMAS) survey, the Bureau of Justice Statistics periodically sponsors a census of the nation's state and local law enforcement agencies. This census, kn

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The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe navigation and to provide background data for engineers, scientific, and other commercial and industrial activities. Hydrographic survey data primarily consist of water depths, but may also include features (e.g. rocks, wrecks), navigation aids, shoreline identification, and bottom type information. NOAA is responsible for archiving and distributing the source data as described in this metadata record.

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The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating. TRMM was successfully launched on November 27, at 4:27 PM (EST) from the Tanegashima Space Center in Japan. The rainfall measuring instruments on the TRMM satellite include the Precipitation Radar (PR), an electronically scanning radar operating at 13.8 GHz; TRMM Microwave Image (TMI), a nine-channel passive microwave radiometer; and Visible and Infrared Scanner (VIRS), a five-channel visible/infrared radiometer. The purpose of 3B43 algorithm is to produce the best-estimate precipitation rate (in mm/hr) and root-mean-square (RMS) precipitation-error estimates from TRMM and other data sources. The algorithm combines multiple independent precipitation estimates from the TMI, Advanced Microwave Scanning Radiometer for Earth Observing Systems (AMSR-E), Special Sensor Microwave Imager (SSMI), Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS), microwave-adjusted merged geo-infrared (IR), and monthly accumulated Global Precipitation Climatology Centre (GPCC) rain gauge analysis. All input microwave data are intercalibrated to TRMM Combined Instrument (TCI) precipitation estimates (TRMM product 3B31); the iIR estimates are computed using monthly matched microwave-IR histogram matching; then missing data in individual 3-hourly merged-microwave fields are filled with the IR estimates. After the preprocessing is complete, the 3-hourly multi-satellite fields are summed for the month and combined with the monthly gauge analysis using inverse-error-variance weighting to form the best-estimate precipitation rate and RMS precipitation-error estimates. These gridded estimates have a calendar month temporal resolution and a 0.25-degree by 0.25-degree spatial resolution. Spatial coverage extends from 50 degrees south to 50 degrees north latitude. The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata. The file size is about 5 MB. Important Changes: After the initial Version 7 processing, it was discovered that AMSU data were neglected in the first retrospective processing of both the Version 7 TMPA (3B42/43) and TMPA-RT (3B40/41/42RT) data series, which created an important shortcoming in the inventory of microwave precipitation estimates used during 2000-2010. In addition, a coding error in the TMPA-RT replaced the occasional missings in product 3B42RT with zeros. Accordingly, both product series were retrospectively processed again. The main impact in both series was to improve the fine-scale patterns of precipitation during 2000-2010 (and for 3B4xRT into late 2012). Averages over progressively larger time/space scales should be progressively less affected. [This is the reason the lack of AMSU went undiscovered; the merger system copes very reasonably with missing data.] Nonetheless, users are urged to switch to the newest Version 7 data sets. The newest runs may be identified by the file names: V.7 3B42/43 suffix of "7A.HDF" for January 2000 - September 2010; V.7 3B4xRT suffix of "7R2.bin" for 1 March 2000 - 6 November 2012. It continues to be the case that the Version 7 3B42/43 is some 4% higher than the calibrating data set (2B31) over oceans, which is still under study. However, the initial conclusion is that it results from the sampling mismatch between the (very sparse) TCI and the (much denser) microwave constellation. At the large scales this offset seems to be nearly a proportional constant. TRMM Product FAQ: http://disc.sci.gsfc.nasa.gov/additional/faq/precipitation_faq.shtml Sign up to receive announcements on the latest data information, tools and services that become available, data announcements from PPS and more! Contact the GES DISC User Services (gsfc-help-disc@lists.nasa.gov) to be added...

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Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data for the Jefferson/Clallam study area on March 23rd-25th, April 13th-15th, and May 7th, 2012 for the Puget Sound LiDAR Consortium in partnership with the Federal Emergency Management Agency (FEMA). The requested area of 32,034 acres for the Jefferson/ Clallam AOI was expanded to include a 100m buffer to ensure complete coverage and adequate point densities around survey area boundaries. The total acreage of this delivery is 42,038 buffered acres of LiDAR data. The LiDAR survey utilized a Leica ALS50 Phase II in a Cessna Caravan 208B and a Leica ALS60 sensor in a Partenavia. See "Process Report" for detailed information about airborne/ground survey methods. This data set has a point spacing of 11.58 points per square meter.

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Rate of deaths by age/gender (per 100,000 population) for people killed in crashes involving a driver with BAC =>0.08%, 2012 Source: Fatality Analysis Reporting System (FARS) Note: Blank cells indicate data are suppressed. Fatality rates based on fewer than 20 deaths are suppressed.

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A map service on the www depicting ownership parcels of the surface estate. Each surface ownership parcel is tied to a particular legal transaction. The same individual or organization may currently own many parcels that may or may not have been acquired through the same legal transaction. Therefore, they are captured as separate entities rather than merged together. Surface Ownership provides the land status user with a current snapshot of ownership within National Forest boundaries. The purpose of the data is to provide display, identification, and analysis tools for determining current boundary information for Forest Service managers, GIS Specialists, and others.

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A list of hospitals participating in the Hospital VBP Program and their scores for the Patient Experience of Care HCAHPS dimensions.

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Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

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This map was produced by the Division of Realty to depict landownership at Rachel Carson National Wildlife Refuge. It was generated from rectified aerial photography, cadastral surveys and recorded documents.

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The Floodplain Mapping/Redelineation study deliverables depict and quantify the flood risks for the study area. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The Floodplain Mapping/Redelineation flood risk boundaries are derived from the engineering information Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA).

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EDI Redaction letter

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This release contains the Basic Stand Alone (BSA) Skilled Nursing Facility (SNF) Beneficiary Public Use Files (PUF) with information from Medicare SNF claims. The CMS BSA SNF Beneficiary PUF is a beneficiary-level file in which each record is a beneficiary who had at least one SNF claim from a random 5 percent sample of Medicare beneficiaries. There are some demographic and claim-related variables provided in this PUF.

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This data set includes statewide counts of Medi-Cal certified eligibles by Month, Aid Code and Delivery System. The term certified eligible refers to beneficiaries who have been determined eligible for Medi-Cal based on a valid eligibility determination.

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HPMS compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially-enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.

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The Medical SAS system provides a variety of SAS-formatted files containing medical data for use by VA staff. These files, and the ability to create user files, are available by connecting to the Austin Information Technology Center (AITC) mainframe. SAS files publish unique patient statistics, utilization, financial and workload information and include extracts from the National Patient Care Database, the Patient Treatment File, the Administrative Data Repository and other databases located at the AITC.

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These data were collected by the U.S. Geological Survey, Alaska Science Center, Polar Bear Research Program as part of long-term research on the southern Beaufort Sea polar bear population.

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MBS Pool-Level Monthly New Issuance file (pool file of New Issuances for the month)

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This survey is the sixth in a series of comprehensive nationwide surveys designed to help the Department of Veterans Affairs (VA) plan its future programs and services for Veterans. This is the first time VA has included groups other than Veterans.

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The outcomes/goals supported by effective use of an EA are: Improved Service Delivery, Functional Integration, Resource Optimization and Authoritative Reference. VA has recognized the four outcomes proposed by the CAF as consistent with meeting VA transformation objectives and adopted them to evolve the OneVA EA