Geospatial data about Hamilton County, Indiana TIF District. Export to CAD, GIS, PDF, CSV and access via API.

Geospatial data about Hamilton County, Indiana Regulated Subdivision Boundary. Export to CAD, GIS, PDF, CSV and access via API.

2018 Transit Routes in the SPC region (excluding Port Authority of Allegheny County). Routes for the following providers:Beaver County Transit Authority (BCTA)Butler Transit Authority (BTA)Fayette Area Coordinated Transit (FACT)Freedom Transit (Washington County)Heritage Transit (HCT)Indiana Area Transit (INDIGO)LenznerMountain Line Transit (MTL)Mid-Mon Valley Transit Authority (MMVTA)New Castle Transit Authority (NCTA)Town & Country Transit (TACT)Westmoreland County Transit Authority (WCTA)For information about Port Authority transit routes, visit Port Authority Open Data website.

Geospatial data about Hamilton County, Indiana Subdivision Regulated Drains. Export to CAD, GIS, PDF, CSV and access via API.

We collected open and publicly available data resources from the web from administrative, county- or state-level institutions in the United States and integrated and harmonized cadastral parcel data, tax assessment data, and building footprint data for 33 counties, where building footprint data and building construction year information was available. The result of this effort is a unique dataset which we call the Multi-Temporal Building Footprint Dataset for 33 U.S. Counties (MTBF-33). MTBF-33 contains over 6.2 million building footprints including their construction year, and is available in ESRI Shapefile format (Spatial reference system: SR-ORG:7480), organized per county. We compared the MTBF-33 dataset quantitatively to other building footprint data sources, achieving an overall F-1 score of 0.93. Moreover, we compared the MTBF-33 dataset qualitatively to urban extents from historical maps and find high levels of agreement. The MTBF-33 dataset can be used to support historical building stock assessments, to derive retrospective depictions of built-up areas from 1900 to 2015, at fine spatial and temporal grain and can be used for data validation purposes, or to train statistical learning approaches aiming to extract historical information on human settlements from remote sensing data, historical maps, or similar data sources.

Data sources: Boulder County (Colorado) Open Data Catalog / Florida Geographic Data Library / Hillsborough County, Florida / City of Tampa / Manatee County, Florida / Sarasota County, Florida / City of Evansville, Vanderburgh County, Indiana / Baltimore County Government, Maryland / Bureau of Geographic Information (MassGIS), Commonwealth of Massachusetts, Executive Office of Technology and Security Services / City of Boston / MetroGIS, Minnesota Geospatial Commons, Minnesota Geospatial Information Office, Anoka County, Carver County, Dakota County, Hennepin County, Ramsey County, and Washington County, Minnesota / Monmouth County, New Jersey / City of New York / Mecklenburg County, North Carolina. Data scraping was performed in 2016.

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer