DCS Terrain Submission for City of Longview PAL, Cowlitz County WA
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Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create the elevation data representing the terrain environment of a watershed and/or floodplain. Terrain data requirements allow for flexibility in the types of information provided as sources used to produce final terrain deliverables. Once this type of data is provided, FEMA will be able to account for the origins of the flood study elevation data. (Source: FEMA Guidelines and Specifications, Appendix M, Section M.1.2).
DCS Terrain Submission for WHATCOM COUNTY, WASHINGTON
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Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create the elevation data representing the terrain environment of a watershed and/or floodplain. Terrain data requirements allow for flexibility in the types of information provided as sources used to produce final terrain deliverables. Once this type of data is provided, FEMA will be able to account for the origins of the flood study elevation data. (Source: FEMA Guidelines and Specifications, Appendix N, Section N.1.2). Source information for each is included in the Data Quality section.
TERRAIN, City of Clark Fork Levee PMR, BONNER COUNTY, IDAHO
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The dataset encompasses portions of Northern Oregon, Eastern Washington, Northern Idaho, and Northwestern Montana within the Columbia River drainage. The bare earth digital elevation models (DEM) represent the earth's surface with all vegetation and human-made structures removed. The bare earth DEMs were derived from LiDAR data using TIN processing of the ground point returns. The DEM grid cell size is 1 m. The elevation units are in meters. Some elevation values have been interpolated across areas in the ground model where there is no elevation data (e.g. over dense vegetation). Breaklines derived from lidargrammetry were used to enforce water boundaries and interpolate some areas where the ground was obscured from the LiDAR data. Water surfaces were derived from a TIN of the 3-D water edge breaklines. Watershed Sciences, Inc. collected the LiDAR and created this data set for David C. Smith & Associates, Inc. and the U.S. Army Corps of Engineers
County Boundaries for Selected Items from the Census of Agriculture, 1950-2012 (COA STCOFIPS)
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This polygon shapefile provides county or county-equivalent boundaries for the conterminous United States and was created specifically for use with the data tables published as Selected Items from the Census of Agriculture for the Conterminous United States, 1950-2012 (LaMotte, 2015). This data layer is a modified version of Historic Counties for the 2000 Census of Population and Housing produced by the National Historical Geographic Information System (NHGIS) project, which is identical to the U.S. Census Bureau TIGER/Line Census 2000 file, with the exception of added shorelines. Excluded from the CAO_STCOFIPS boundary layer are Broomfield County, Colorado, Menominee County, Wisconsin, and the independent cities of Virginia with the exception of the 3 county-equivalent cities of Chesapeake City, Suffolk, and Virginia Beach. The census of agriculture was not taken in the District of Columbia for 1959, but available data indicate few if any farms in that area, the polygon was left in place to preserve the areas of the surrounding counties. Baltimore City, Maryland was combined with Baltimore County and the St. Louis City, Missouri, was combined with St. Louis County. La Paz County, Arizona was combined with Yuma County, Arizona and Cibola County, New Mexico was combined with Valencia County, New Mexico. Minor county border changes were at a level of precision beyond the scope of the data collection. A major objective of the census data tabulation is to maintain a reasonable degree of comparability of agricultural data from census to census. The tabular data collection is from 14 different censuses where definitions and data collection techniques may change over time and while the data are mostly comparable, a degree of caution should be exercised when using the data in analysis procedures. While the data are at a county-level resolution, a regional approach is more appropriate than a county-by-county analysis. The main purpose of this layer is to provide a base to generate a county raster for the allocation of agricultural census values to specific (agricultural) pixels. Vector format is provided so the raster pixel size can be user designated. References cited: LaMotte, A.E., 2015, Selected items from the Census of Agriculture at the county level for the conterminous United States, 1950-2012: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7H13016. National Historical Geographic Information System, Minnesota Population Center, 2004, Historic counties for the 2000 census of population and housing: Minneapolis, MN, University of Minnesota, accessed 03/18/2013 at http://nhgis.org