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An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation has been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. For this dataset, 2-foot pixel resolution natural color digital orthimages were obtained from the West Virginia Statewide Addressing and Mapping Board. The orthoimages were mosaicked and reprojected by the USGS from the original 2-foot pixel, West Virginia North and South State Plane (feet) Coordinate Systems to Universal Transverse Mercator (UTM) (meters), Zone 17, NAD83 datum. Each orthoimage (DOQQ) provides the equivalent to a quarter of a 7.5-minute map (3.75 minutes of latitude and longitude) with overedge. The overedge is approximately 300 meters beyond the extremes of the corners of coverage. The naming convention is based on the U.S. Geological Survey 1:24,000 Topographic Map Series with the quadrant abbreviation, i.e. athens_ne.tif, etc. This data set covers the entire state of West Virginia including into UTM zone 17 on the east edge.

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Volcanoes have contributed significantly to the formation of the surface of our planet. Volcanism produced the crust we live on and most of the air we breathe. The remnants of an eruption reveal as much as the eruption itself, for they tell us many things about the eruption. Included here are examples of several volcanic products and other magmatic features, with descriptions of how they were formed and what they tell us about volcanism. Most volcanic rock material begins as molten rock material formed within Earth and is called magma. Eruptive products include lava (fluid rockmaterial) and pyroclastics or tephra (fragmentary solid or liquid rock material). Tephra includes volcanic ash, lapilli (fragments between 2 and 64 mm), blocks, and bombs. Perhaps the best known volcanic product is lava, the fluid rock material that flows rather quietly from volcanic vents. The external and internal structures of lava flows are the result of the physical properties of the magma from which it was derived. Of these physical properties viscosity is the most important and it is in turn affected by the temperature and chemical composition of the magma. Lavas of low viscosity can spread great distances from the vent. Greater viscosity produces thicker lava flows that generally cover less area. The rate of supply of magma relative to the velocity of the lava as it flows from the vent and the external environment through which the lava flows also affect the structure of the solidified lava. Products of explosive eruptions include pyroclastic (fire broken) rocks and rock fragments. The force that produces explosive eruptions is the release of trapped gas. Ejecta from these explosions may be derived from the magma or from rocks in the vicinity of the volcanic conduit that are blasted out in the eruption. These may be ejected more or less vertically, then fall back to earth in the form of ash fall deposits. Pyroclastic flows result when the eruptive fragments follow the contours of the volcano and surrounding terrain. They are of three main types: glowing ash clouds (nuee ardente), ash flows, and mudflows. Volcanic structures can take many forms. A few of the smaller structures built directly around vents include cinder, spatter, and lava cones. Thick lavas may pile up over their vents to form lava domes. Larger structures produced by low viscosity lava flows include lava plains. The erosion of volcanoes leaves volcanic remnants, interesting reminders of the volcano's former fury. Erosion of the layers of lava and ash that built the volcano leaves the congealed magma in the conduit. This feature, sometimes referred to as a plug or the volcanic neck or throat, is a dramatic pillar of rock rising above the surrounding plain. These plugs or necks may be composed partially of fragments of the walls of the pipe and partially of congealed magma. They may be as more than a kilometer in diameter. Magma flowing into cracks in the rocks produces dikes, sills and laccoliths. This intrusive rock is generally resistant to erosion and often remains after the surrounding rock has eroded away. These exposed intrusive rocks give us a glimpse of the complex underground network of piping in active volcanoes. These igneous features are constant reminders of the timelessness of the processes that relentlessly form, and reform, the surface of planet Earth.

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In Phase II of this SBIR, Harmonic Devices (HDI) proposes to develop miniaturized MEMS filters at UHF, S-band and Ka-band to address the requirements of NASA's next-generation software defined EVA radio. The filters are a key enabler for this highly reconfigurable, fault tolerant, cell-phone sized EVA radio. For UHF and S-band, HDI will employ its proprietary contour-mode aluminum nitride MEMS piezoelectric resonator technology. Processed on silicon substrates, the resonators have their natural frequency defined by the lateral, in-plane dimensions of the structure. This feature enables the definition of different frequencies directly at the CAD layout level. Thus, the low insertion loss UHF and S-band filters can be monolithically integrated into a single chip. For the Ka-band, HDI will employ coaxial 3D MEMS interdigital filters that exhibit low insertion and ripple in a miniaturized form factor. Several US companies have expressed a keen interest in HDI's technology. In Phase I, HDI successfully proved the feasibility of employing the proposed UHF, S-band, and Ka-band filters in NASA's software defined EVA radio through simulation and microfabrication pilot studies. The filters can be monolithically integrated onto the same silicon substrate, resulting in substantial savings in board space. The objective of Phase II is to build the filter prototypes and deliver them to NASA for testing. The results of the Phase I feasibility study convincingly justify Phase II continuation.

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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). In addition to the preceding, required text, the Abstract should also describe the projection and coordinate system as well as a general statement about horizontal accuracy.

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NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the National Tsunami Hazard Mitigation Program's (NTHMP) efforts to improve community preparedness and hazard mitigation. These integrated bathymetric-topographic DEMs are used to support tsunami and coastal inundation mapping. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to various vertical and horizontal datums depending on the specific modeling requirements of each State. For specific datum information on each DEM, refer to the appropriate DEM documentation. Cell sizes also vary depending on the specification required by modelers in each State, but typically range from 8/15 arc-second (~16 meters) to 8 arc-seconds (~240 meters).

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Monitoring project designed to evaluate effectiveness of Natural Drainage Systems built by Seattle Public Utilities in the Piper Creek watershed. We collected data on three groups of stream organisms: fish, benthic invertebrates, and periphyton (the layer of biofilm covering the stream benthos). Benthic invertebrate and periphyton data were collected annually in the early fall (September). Fish surveys were conducted in the spring and fall for 2006-2007, and thereafter in September only. Fish movement was monitored continuously with a combination of mobile and fixed-array Passive Integrated Transponder (PIT)-tag antennas beginning in the summer of 2007. Fish (density, biomass, movement, growth, diet), benthic invertebrates, periphyton

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Provides the seniority list for entry into HSA 90 day emergency shelter waitlist. The list will be generated on 2/24/14 and updated twice daily.

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This data set contains a 1999 Landsat ETM+ mosaic image land of cover classification showing forested and deforestation areas in Uruara, Para, Brazil. This image may be overlain with the cadastral property map of the same area (see related data set LBA-ECO LC-24 Cadastral Property Map of Uruara, Para, Brazil: ca.1975). This data sets contains a single geotiff image distributed as deforested_large.zip.

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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). In addition to the preceding, required text, the Abstract should also describe the projection and coordinate system as well as a general statement about horizontal accuracy.

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Automated detection of land cover changes between multitemporal images has long been a goal of the remote sensing discipline. Most research in this area has focused on methods for detecting and categorizing changes captured by two or more images [Jensen, 1991, Singh, 1989; Coppin and Bauer, 1996], but precise coregistration of images is required and remains a key challenge [Dai and Khorram, 1998, Stow and Chen, 2002, Verbyla and Boles, 2000]. This SBIR project team proposes to develop a software package specifically optimized for automatic and precise coregistration of two or more images, which will in turn enable change detection algorithms to focus on salient changes rather than highlight image registration errors. In accordance with this subtopic?s guidance to ??focus on the systems engineering aspect of application development rather than fundamental research??, our project will emphasize integration of state of the art methods to create a flexible, robust, and easy to use tool. Presuming success through Phase II, this will enable NASA researchers and unsophisticated users to minimize or eliminate false ?changes? caused by image coregistration errors and thus increase utilization of Earth Science observations from NASA sensors and other data sources (IKONOS, aerial photography, etc.).

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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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ENTERPRISE COMPONENT INTEGRATION SYSTEM (eCIS) Project

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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 UTM projection and coordinate system. 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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This data set contains the boundaries of U.S. Fish and Wildlife Service (USFWS) Designated Critical Habitats and National Wildlife Refuges and Bureau of Land Management (BLM) properties for the North Slope of Alaska. Vector polygons in this data set represent the management areas. Location-specific type and source information is stored in relational data tables (described below) designed to be used in conjunction with this spatial data layer.This data set comprises a portion of the Environmental Sensitivity Index (ESI) data for North Slope, Alaska. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. See also the SOCECON (Socioeconomic Resource Points and Lines) data layer, part of the larger North Slope, Alaska ESI database, for additional human-use information.

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Carbon bonded carbon fiber (CBCF) insulating material is the basis for several highly successful NASA developed thermal protection systems (TPS). Among the innovative TPS are Genesis, PICA (phenolic impregnated carbonaceous ablator) currently employed on the Stardust Mission and TUFROC (Toughened Uni-piece Fibrous Reinforced Oxidation-resistant Composite). NASA-Ames has a patent pending concerning TUFROC and the technology is planned for transfer to Boeing for fabrication of the X-37 leading edge. Carbon bonded carbon fiber (CBCF) utilized in the above mentioned TPS is attractive because of its low cost and density, superior thermal performance and compatibility with other components. However, the current CBCF manufacturing processes do not produce materials engineered to the necessary control required of these emerging and highly innovative TPS designs. This program will develop and demonstrate advanced processes and manufacturing approaches to consistently fabricate CBCF insulating material to desired specifications. The benefits derived include significantly improved flexibility for the TPS design engineer as well as more cost efficient CBCF derived TPS fabrication. It will also enable greater availability to this class of superior insulating materials.

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The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by non-visible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2010 Census blocks nest within every other 2010 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

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Marine seismic reflection data are used to image and map sedimentary and structural features of the seafloor and subsurface. These data are useful in mapping stratigraphy and in assessing other submarine geologic characteristics and features. The data presented here are useful in mapping sand deposits that may be used in Louisiana beach nourishment projects. These data were collected as part of a Louisiana Sand Resources Study done in cooperation between the USGS, U.S. Army Corps of Engineers, University of New Orleans, Louisiana Department of Natural Resources, and Eckerd College. This study is part of the USGS Subsidence and Coastal Change (SCC) Project.

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The NASA IceBridge Geometrics 823A Cesium Magnetometer L2 Geolocated Magnetic Anomalies (IMGEO2) data set contains magnetic anomaly measurements taken over Antarctica using the Geometrics 823A Cesium Magnetometer. The data were collected by scientists working on the Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project, which is funded by the National Science Foundation (NSF) and the Natural Environment Research Council (NERC) with additional support from NASA Operation IceBridge. The data are stored in ASCII text format and are available for periodic, ongoing campaigns from 16 November 2009 to the present via FTP.

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The Violent Criminal Apprehension Program (ViCAP) serves as the national information center that collects, collates and analyzes crimes of violence. The system contains solved and unsolved cases involving homicide or attempted homicide, sexual assaults,

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This digital data set consists of faults for the High Plains aquifer in the central United States. The High Plains aquifer extends from south of 32 degrees to almost 44 degrees north latitude and from 96 degrees 30 minutes to 106 degrees west longitude. The outcrop area covers 174,000 square miles and is present in Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. This digital data set was created by digitizing the faults from a 1:1,000,000-scale base map created by the U.S. Geological Survey High Plains Regional Aquifer-System Analysis (RASA) project (Gutentag, E.D., Heimes, F.J., Krothe, N.C., Luckey, R.R., and Weeks, J.B., 1984, Geohydrology of the High Plains aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming: U.S. Geological Survey Professional Paper 1400-B, 63 p.) The data are not intended for use at scales larger than 1:1,000,000.

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This data set contains vector polygons representing the coastal wetlands for Virginia, classified according to the Environmental Sensitivity Index (ESI) classification system. This data set comprises a portion of the ESI data for Virginia. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. See also the ESI data layer, part of the larger Virginia ESI database, for additional coastal habitat information.

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This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer. The DEMs created for this project were developed using the NOAA National Weather Service's Weather Forecast Office (WFO) boundaries. Because the WFO boundaries can cover large areas, the WFO DEM was divided into smaller DEMs to ensure more manageable file sizes. The Miami (FL) WFO DEM was split into two smaller DEMs. They are divided along county lines and are: 1. Miami (FL) WFO - Collier and Monroe (Mainland) Counties 2. Miami (FL) WFO - Palm Beach, Broward, Miami-Dade, and Monroe (Keys) Counties This metadata record describes the DEM for Miami (FL) WFO - Palm Beach, Broward, Miami-Dade, and Monroe (Keys) Counties. The DEM includes the best available lidar data known to exist at the time of DEM creation for the coastal areas of Palm Beach, Broward, Miami-Dade, and Monroe (Keys) counties, that met project specifications. The DEM is derived from LiDAR datasets collected for the Florida Department of Emergency Management (FDEM). LiDAR data for Monroe, Miami-Dade, Broward and Palm Beach counties was collected in 2007 and 2008. Hydrographic breaklines used in the creation of the DEM were obtained from FDEM and the South Florida Water Management District. The DEMs are hydro flattened such that water elevations are less than or equal to 0 meters. The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 5 meters.

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This layer contains spatial information for 25 plots sampled during vegetation mapping and classification efforts at Casa Grande Ruins NM, AZ. Data was collected by field crews employeed by the Sonoran Desert Network, Inventory and Monitoring program (SODN). Points represent plot origin corners.

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This factsheet provides an overview of the U.S. Fish and Wildlife Service Catalog ServCat, a centralized web application that compiles documents and organizes datasets, such as reports, surveys, databases, geospatial data and images.

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Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance study, which includes the hydrologic data expected by FEMA for new riverline studies. (Source: FEMA Guidelines and Specifications, Appendix N)