The U.S. Geological Survey South Atlantic Water Science Center, in cooperation with the South Carolina Department of Transportation, implemented a South Carolina StreamStats application in 2018. This shapefile dataset contains vector lines representing streams, rivers, and ditches that were used in preparing the underlying data for the South Carolina StreamStats application. Data were compiled from multiple sources, but principally represent lidar-derived linework from the South Carolina Department of Natural Resources and the South Carolina Lidar Consortium.The South Carolina hydrography lines were created from elevation rasters that ranged from 4 to 10 ft resolution, to produce a product of approximately 1:6,000-scale. Other sources include the 1:24,000 scale high resolution National Hydrography Dataset streamlines [for streamlines in Georgetown County (SC), NC, and GA] and the 1:4,800 scale local-resolution North Carolina Stream Mapping Project lines (mountain counties). These ...

This layer contains the boundary of Williamson County in Central Texas. This layer is part of an original dataset provided and maintained by the City of Round Rock GIS/IT Department. The data in this layer are represented as a polyline. Williamson County (sometimes abbreviated as "Wilco") is a county in the U.S. state of Texas. As of the 2010 census, the population was 422,679. Its county seat is Georgetown. The county is named for Robert McAlpin Williamson (1804-1859), a community leader and a veteran of the Battle of San Jacinto. Williamson county is part of the Ausin-Round Rock, Texas Metropolitan Statistical Area. It was included with Austin in the Best Cities to Live in for 2009 by the Milken Institute. It is on both the Edwards Plateau to the west with rocky terrain and hills, and Texas Blackland Prairies in the each, with rich and fertile farming land. The two areas are roughly bisected by Interstate 35.You can read more about Williamson County here: https://en.wikipedia.org/wiki/Williamson_County,_Texas

Geospatial data about Williamson County, Texas Municipal Utility Districts. Export to CAD, GIS, PDF, CSV and access via API.

This map shows a simple summary of the social vulnerability of populations in the United States. Using Census 2010 information, the map answers the question “Where are the areas of relatively greater potential impact from disaster events within the U.S.?” from the perspective of social vulnerability to hazards. In other words, all areas of the U.S. are assessed relative to each other. Local and regional assessments of social vulnerability should apply the same model to their multi-county or multi-state region. For emergency response planning and hazard mitigation, populations can be assessed by their vulnerability to various hazards (fire, flood, etc). Physical vulnerability refers to a population’s exposure to specific potential hazards, such as living in a designated flood plain. There are various methods for calculating the potential or real geographic extents for various types of hazards. Social vulnerability refers to sensitivity to this exposure due to population and housing characteristics: age, low income, disability, home value or other factors. The social vulnerability score presented in this web service is based upon a 2000 article from the Annals of the Association of American Geographers which sums the values of 8 variables as a surrogate for "social vulnerability". For example, low-income seniors may not have access to a car to simply drive away from an ongoing hazard such as a flood. A map of the flood’s extent can be overlaid on the social vulnerability layer to allow planners and responders to better understand the demographics of the people affected by the hazard. This map depicts social vulnerability at the block group level. A high score indicates an area is more vulnerable. This web service provides a simplistic view of social vulnerability. There are more recent methods and metrics for determining and displaying social vulnerability, including the Social Vulnerability Index (SoVI) which capture the multi-dimensional nature of social vulnerability across space. See www.sovius.org for more information on SoVI. The refereed journal article used to guide the creation of the model in ModelBuilder was: Cutter, S. L., J. T. Mitchell, and M. S. Scott, 2000. "Revealing the Vulnerability of People and Places: A Case Study of Georgetown County, South Carolina." Annals of the Association of American Geographers 90(4): 713-737. Additionally, a white paper used to guide creation of the model in ModelBuilder was "Handbook for Conducting a GIS-Based Hazards Assessment at the County Level" by Susan L. Cutter, Jerry T. Mitchell, and Michael S. Scott.Off-the-shelf software and data were used to generate this index. ModelBuilder in ArcGIS 10.1 was used to connect the data sources and run the calculations required by the model.-------------------------The Civic Analytics Network collaborates on shared projects that advance the use of data visualization and predictive analytics in solving important urban problems related to economic opportunity, poverty reduction, and addressing the root causes of social problems of equity and opportunity. For more information see About the Civil Analytics Network.