10,000+ results returned
-
Title: Industrial land use in Sydney
Contributors:- Image data
- 1975
Summary: Includes 21 insets of land use of towns and districts. Includes names of towns and districts. On back of sheet: "from study with same title, may 1975"
-
Title: Compilation of traffic regulations in thirteen Iowa cities
Contributors:- Not specified
- 1930
- Murray, Laurence W.
- Bowman, Alfred B.
- Iowa. State Planning Board. Committee on Urban Land Use and Traffic Studies
Summary: 12 leaves ; 29 cm
-
Title: New York City Neighborhoods, 2007
Contributors:- Polygon data
- 2007
Summary: New York City Neighborhoods is a polygon theme representing neighborhood areas in New York City. The neighborhoods are as used and defined by Community Studies of New York in the Infoshare Online database. The neighborhood boundaries were originally defined by a City informal taskforce, the boundaries are not official, but are meant to define the neighborhoods in which residents believe they live. Attribute data includes the name and the approximate perimeter and area of the neighborhood.
-
Title: Watersheet Plan, Boston Harbor, Massachusetts, 1998 (Raster Image)
Contributors:- Raster data
- 2014
- Harvard Map Collection, Harvard Library
- University of Massachusetts at Boston. Urban Harbors Institute.
Summary: This layer is a georeferenced raster image of the historic paper map entitled: Boston Harbor watersheet plan, prepared for the city of Boston by Urban Harbors Institute, University of Massachusetts Boston. It was published by Urban Harbors Institute in 1998. Scale [ca. 1:3,000]. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Massachusetts State Plane Coordinate System, Mainland Zone (in Feet) (Fipszone 2001). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as drainage, cities and other human settlements, territorial boundaries, shoreline features, and more. Includes also legend showing marine transportation, drainage, and landmark features. This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.
-
Title: Lhasa City 1:12,500
Contributors:- Image data
- 1995
Summary: Relief shown by contours and spot heights. Includes index. 1995
-
Title: Elizabeth street names
Contributors:- Image data
- 1962
Summary: Map includes names of districts, street names, and bulding plans "DRWG. No. S349A" Companion volume "Elizabeth street names". Princeton Library does not have this book.
-
Title: Plan of Detroit Woodward,Augustus Brevoort.
Contributors:- Not specified
- 1860
Summary: Facsimile. "Reproduced ... from the original in the Cornell University Library." "This is number 125 of an edition limited to 500 copies." 1 map; 26 x 21 cm, on sheet 48 x 38 cm
-
Title: Habitat: Offshore of Point Reyes, California, 2014
Contributors:- Polygon data
- 2014
- Greene, H. G.
- Endris, Charles A.
- Dieter, Bryan E.
- Golden, Nadine E.
- Center for Habitat Studies, Moss Landing Marine Laboratories
- Moss Landing Marine Laboratories
Summary: Using multibeam echosounder (MBES) bathymetry and backscatter data, potential marine benthic habitat maps were constructed. The habitats were based on substrate types and documented or "ground truthed" using underwater video images and seafloor samples obtained by the USGS. These maps display various habitat types that range from flat, soft, unconsolidated sediment-covered seafloor to hard, deformed (folded), or highly rugose and differentially eroded bedrock exposures. Rugged, high-relief, rocky outcrops that have been eroded to form ledges and small caves are ideal habitat for rockfish (Sebastes spp.) and other bottom fish such as lingcod (Ophiodon elongatus). The map that show these data are published in Open-File Report 2015-1114, "California State Waters Map Series—Offshore of Point Reyes, California." This layer is part of USGS Data Series 781. In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP) to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats and geology within the 3-nautical-mile limit of California's State Waters. CSMP has divided coastal California into 110 map blocks, each to be published individually as United States Geological Survey Open-File Reports (OFRs) or Scientific Investigations Maps (SIMs) at a scale of 1:24,000. Maps display seafloor morphology and character, identify potential marine benthic habitats and illustrate both the seafloor geology and shallow (to about 100 m) subsurface geology. Data layers for bathymetry, bathymetric contours, acoustic backscatter, seafloor character, potential benthic habitat and offshore geology were created for each map block, as well as regional-scale data layers for sediment thickness, depth to transition, transgressive contours, isopachs, predicted distributions of benthic macro-invertebrates and visual observations of benthic habitat from video cruises over the entire state. These data are intended for science researchers, students, policy makers, and the general public. This information is not intended for navigational purposes.The data can be used with geographic information systems (GIS) software to display geologic and oceanographic information. Additionally, this coverage can provide a geologic map for the public and geoscience community to aid in assessments and mitigation of geologic hazards in the coastal region and sufficient geologic information for land-use and land-management decisions both onshore and offshore. This information is not intended for navigational purposes. Endris, C.A., Greene, H.G. and Dieter, B.E. (2014). Habitat: Offshore of Point Reyes, California, 2014. California State Waters Map Series Data Catalog: U.S. Geological Survey Data Series 781. Available at: http://purl.stanford.edu/nt663ss8448. Data used for the creation of the potential marine benthic habitat interpretation consists of multibeam bathymetry, acoustic backscatter, sediment samples, camera-sled imagery, and existing geologic and seafloor interpretive maps. All data were compiled and displayed for interpretation using ESRI ArcGIS software, ArcMap v.10.0. The process consists of editing a shapefile within ArcMap, beginning with the construction of polygons to delineate benthic features. A benthic feature is an area with common characteristics which can be characterized as a single potential habitat type. The boundaries and extents of these features were determined from the bathymetric data. In general, interpretations were made at scales between 1:2,000 and 1:5,000. The USGS kindly provided the Center for Habitat Studies with a geodatabase consisting of feature datasets delineating geologic features and attributes for offshore of Point Reyes. Some of the delineated polygons were preserved as part of the potential marine benthic habitat characterization. However, the Greene and others (2007) code was used in attributing the dataset and additional polygons were added using the methods outlined below. High-resolution multibeam sonar data in the form of bathymetric depth grids (seafloor digital elevation models, referred to as the "bathymetry") were the primary data used in the interpretation of potential habitat types. Shaded-relief imagery ("hillshade") allows for visualization of the terrain and interpretation of submarine landforms. On the basis of these hillshades, areas of rock were identified by their often sharply defined edges and high relative relief; these may be contiguous outcrops, isolated parts of outcrop protruding through sediment cover (pinnacles), or isolated boulders. Although these types of features can be confidently characterized as exposed rock, it is not uncommon to find areas within or around the rocky feature that appear to be covered by a thin veneer of sediment. These areas are identified as "mixed" induration, containing both rock and sediment. Broad areas of the seafloor lacking sharp and angular characteristics are considered to be sediment. Sedimentary features may contain erosional or depositional characteristics recognizable in the bathymetry, such as dynamic bedforms (dunes or sand waves). General morphologic features such as scours, mounds, and depressions were also identified using the hillshade imagery. The combination of acoustic backscatter data and "ground truthed" sediment samples were used to delineate seafloor sediment types within areas identified as "soft (s)" induration. Initially, ground truth data, in the form of grab sample descriptions and average grain size measurements, were categorized into four grain-size categories: mud (m), muddy sand (s/m), sand (s), and sandy gravel (s/g). Backscatter data was then classified into four intensity categories (low, med, high, very high) that are assumed to correspond to relative grain sizes. The aim was to develop an intensity classification of the seafloor that correlated with the data collected from the sediment samples. Thus, the combination of remotely observed data (acoustic backscatter) and directly observed data (sediment grab samples) translates to higher confidence in our ability to interpret broad areas of the seafloor. Nonetheless, we caution against using our sediment type interpretations as anything more than "best-guess" because of the following issues: characterization of contiguous sediment bodies is a difficult procedure because even small areas can exhibit a wide spectrum of backscatter-intensity values that lack distinct boundaries; backscatter intensity can be affected by depth, vegetation, water column conditions, and seafloor relief; and directly observed sediment data, in the form of sediment samples, represents a very small area relative to remotely observed data, requiring broad areas of interpolation. Please refer to Greene and others (2007) for more information regarding the Benthic Marine Potential Habitat Classification Scheme and the codes used to represent various seafloor features. References Cited: Greene, H.G., Bizzarro, J.J., O'Connell, V.M., and Brylinsky, C.K., 2007, Construction of digital potential marine benthic habitat maps using a coded classification scheme and its application, in Todd, B.J., and Greene, H.G., eds., Mapping the seafloor for habitat characterization: Geological Association of Canada Special Paper 47, p. 141-155. Greene, H.G., Yoklavich, M.M., Starr, R.M., O'Connell, V.M., Wakefield, W.W., Sullivan, D.E., McRea, J.E., Jr., and Cailliet, G.M., 1999, A classification scheme for deep seafloor habitats: Oceanologica Acta, v. 22, no. 6, p. 663-678. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
-
Title: Habitat: Offshore of San Francisco, California, 2013
Contributors:- Polygon data
- 2014
- Dieter, Bryan E.
- Greene, H. G.
- Endris, Charles A.
- Golden, Nadine E.
- Center for Habitat Studies, Moss Landing Marine Laboratories
- Moss Landing Marine Laboratories
Summary: This polygon shapefile depicts potential benthic habitats within the offshore area of San Francisco, California. Using multibeam echosounder (MBES) bathymetry and backscatter data, potential marine benthic habitat maps were constructed. The habitats were based on substrate types and documented or "ground truthed" using underwater video images and seafloor samples obtained by the USGS. These maps display various habitat types that range from flat, soft, unconsolidated sediment-covered seafloor to hard, deformed (folded), or highly rugose and differentially eroded bedrock exposures. Rugged, high-relief, rocky outcrops that have been eroded to form ledges and small caves are ideal habitat for rockfish (Sebastes spp.) and other bottom fish such as lingcod (Ophiodon elongatus). A map that shows these data is published in Open-File Report 2015-1068, "California State Waters Map Series--Offshore of San Francisco, California." This layer is part of USGS Data Series 781. In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP) to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats and geology within the 3-nautical-mile limit of California's State Waters. CSMP has divided coastal California into 110 map blocks, each to be published individually as United States Geological Survey Open-File Reports (OFRs) or Scientific Investigations Maps (SIMs) at a scale of 1:24,000. Maps display seafloor morphology and character, identify potential marine benthic habitats and illustrate both the seafloor geology and shallow (to about 100 m) subsurface geology. Data layers for bathymetry, bathymetric contours, acoustic backscatter, seafloor character, potential benthic habitat and offshore geology were created for each map block, as well as regional-scale data layers for sediment thickness, depth to transition, transgressive contours, isopachs, predicted distributions of benthic macro-invertebrates and visual observations of benthic habitat from video cruises over the entire state. The purpose of this work is to construct nine potential marine benthic habitat maps characterized after Greene et al. (1999, 2007). These habitat maps are constructed in the same manner as the maps completed for phase I of the California Seafloor Mapping Program (CSMP). These data are intended for science researchers, students, policy makers, and the general public. This information is not intended for navigational purposes.The data can be used with geographic information systems (GIS) software to display geologic and oceanographic information. Additionally, this coverage can provide a geologic map for the public and geoscience community to aid in assessments and mitigation of geologic hazards in the coastal region and sufficient geologic information for land-use and land-management decisions both onshore and offshore. This information is not intended for navigational purposes. Endris, C.A., Greene, H.G., and Dieter, B.E. (2014). Habitat: Offshore of San Francisco, California, 2013. California State Waters Map Series Data Catalog: U.S. Geological Survey Data Series 781. Available at: http://purl.stanford.edu/bp352gx0117. Data used for the creation of the potential marine benthic habitat interpretation consists of multibeam bathymetry, acoustic backscatter, sediment samples, camera-sled imagery, and existing geologic and seafloor interpretive maps. All data were compiled and displayed for interpretation using ESRI ArcGIS software, ArcMap v.10.0. The process consists of editing a shapefile within ArcMap, beginning with the construction of polygons to delineate benthic features. A benthic feature is an area with common characteristics which can be characterized as a single potential habitat type. The boundaries and extents of these features were determined from the bathymetric data. In general, interpretations were made at scales between 1:2,000 and 1:5,000. The USGS kindly provided the Center for Habitat Studies with a geodatabase consisting of feature datasets delineating geologic features and attributes for offshore San Francisco. Some of the delineated polygons were preserved as part of the potential marine benthic habitat characterization. However, the Greene and others (2007) code was used in attributing the dataset and additional polygons were added using the methods outlined below. High-resolution multibeam sonar data in the form of bathymetric depth grids (seafloor digital elevation models, referred to as the "bathymetry") were the primary data used in the interpretation of potential habitat types. Shaded-relief imagery ("hillshade") allows for visualization of the terrain and interpretation of submarine landforms. On the basis of these hillshades, areas of rock were identified by their often sharply defined edges and high relative relief; these may be contiguous outcrops, isolated parts of outcrop protruding through sediment cover (pinnacles), or isolated boulders. Although these types of features can be confidently characterized as exposed rock, it is not uncommon to find areas within or around the rocky feature that appear to be covered by a thin veneer of sediment. These areas are identified as "mixed" induration, containing both rock and sediment. Broad areas of the seafloor lacking sharp and angular characteristics are considered to be sediment. Sedimentary features may contain erosional or depositional characteristics recognizable in the bathymetry, such as dynamic bedforms (dunes or sand waves). General morphologic features such as scours, mounds, and depressions were also identified using the hillshade imagery. The combination of acoustic backscatter data and "ground truthed" sediment samples were used to delineate seafloor sediment types within areas identified as "soft (s)" induration. Initially, ground truth data, in the form of grab sample descriptions and average grain size measurements, were categorized into four grain-size categories: mud (m), muddy sand (s/m), sand (s), and sandy gravel (s/g). Backscatter data was then classified into four intensity categories (low, med, high, very high) that are assumed to correspond to relative grain sizes. The aim was to develop an intensity classification of the seafloor that correlated with the data collected from the sediment samples. Thus, the combination of remotely observed data (acoustic backscatter) and directly observed data (sediment grab samples) translates to higher confidence in our ability to interpret broad areas of the seafloor. Nonetheless, we caution against using our sediment type interpretations as anything more than "best-guess" because of the following issues: characterization of contiguous sediment bodies is a difficult procedure because even small areas can exhibit a wide spectrum of backscatter-intensity values that lack distinct boundaries; backscatter intensity can be affected by depth, vegetation, water column conditions, and seafloor relief; and directly observed sediment data, in the form of sediment samples, represents a very small area relative to remotely observed data, requiring broad areas of interpolation. Please refer to Greene and others (2007) for more information regarding the Benthic Marine Potential Habitat Classification Scheme and the codes used to represent various seafloor features. References Cited: Greene, H.G., Bizzarro, J.J., O'Connell, V.M., and Brylinsky, C.K., 2007, Construction of digital potential marine benthic habitat maps using a coded classification scheme and its application, in Todd, B.J., and Greene, H.G., eds., Mapping the seafloor for habitat characterization: Geological Association of Canada Special Paper 47, p. 141-155. Greene, H.G., Yoklavich, M.M., Starr, R.M., O'Connell, V.M., Wakefield, W.W., Sullivan, D.E., McRea, J.E., Jr., and Cailliet, G.M., 1999, A classification scheme for deep seafloor habitats: Oceanologica Acta, v. 22, no. 6, p. 663-678. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
-
Title: Adelaide visitors guide
Contributors:- Image data
- 1974
Summary: Panel title. Includes indexes, illustrations, and tourist information.
-
Title: FHA Insurance in Force by Tract, 2016
Contributors:- Polygon data
- 2016
Summary: The Federal Housing Administration, generally known as "FHA", provides mortgage insurance on loans made by FHA-approved lenders throughout the United States and its territories. FHA insures mortgages on single family and multifamily homes including manufactured homes and hospitals. It is the largest insurer of mortgages in the world, insuring over 34 million properties since its inception in 1934. The insurance in force represents the outstanding balance of an active loan. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Note that this file only includes x, y coordinates and associated attributes for those addresses that can be geocoded to an interpolated point along a street segment, or to the centroid of the nearest U.S. Census block. Please consider this issue when using any datasets provided by HUD. Data is current as of 09/30/2016. This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). FHA Insurance in Force by Tract, 2016. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/mk300bj2992. To learn more: please visit: http://portal.hud.gov/hudportal/HUD?src=/program_offices/housing/fhahistory
-
Title: CDBG Activity, 1998-2015
Contributors:- Point data
- 2016
Summary: The Community Development Block Grant (CDBG) is a federal block grant distributed via formula to states and local governments. States and local governments use these grant funds to carry out housing, economic development, public services, and public improvement activities that serve low- and moderate-income people. The locations of CDBG activities are derived from addresses provided by HUD grantees from 1996 to present in HUDs Integrated Disbursement and Information System (IDIS). Until recently, these addresses were not validated on point of entry. The prevalence of missing or incorrect address data means that HUD cannot guarantee the accuracy of these locations. However, due to recent improvements to IDIS, HUD expects the quality of activity locations to improve over time. Data Current As Of: 9/25/2016 This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). CDBG Activity, 1998-2015. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/tn917bf6519.
-
Title: ACS 5 Year CHAS Data by County, 2008-2012
Contributors:- Polygon data
- 2016
Summary: This polygon shapefile contains Comprehensive Housing Affordability Strategy (CHAS) data at the county level. The CHAS is derived from the American Community Survey (ACS) data, which has a smaller sample size than the Decennial Census (which was the basis of the 2000 CHAS). As a result, the Census Bureau cannot produce data using only one year of survey responses, except in very populous areas. For areas with population 65,000 or greater, ACS estimates are available each year using only the most recent year’s survey responses (known as "1-year data"). For areas with population 20,000 or greater, ACS estimates are available each year based on averages of the previous three years of survey responses ("3-year data"). For areas with population less than 20,000—including all census tracts, and many places, counties, and minor civil divisions—the only ACS estimates available are based on averages of the previous five years of survey responses ("5-year data"). The primary purpose of the CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUDs programs (primarily 30, 50, and 80 percent of median income). It is also important to consider the prevalence of housing problems among different types of households, such as the elderly, disabled, minorities, and different household types. The CHAS data provide counts of the numbers of households that fit these HUD-specified characteristics in HUD-specified geographic areas. In addition to estimating low-income housing needs, the CHAS data contribute to a more comprehensive market analysis by documenting issues like lead paint risks, affordability mismatch, and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building. Dataset uses custom HAMFI figures calculated by HUD PDR staff based on 2008-2012 ACS income data. This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). ACS 5 Year CHAS Data by County, 2008-2012. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/dw607bb8018.
-
Title: HOME Activity by Tract, 2016
Contributors:- Polygon data
- 2016
Summary: This polygon shapefile contains Home Investment Partnerships Program (HOME) activity data at the tract level. HOME is a program of federal block grants distributed via formula to states and local governments. Participating jurisdictions may use HOME funds for a variety of housing activities, according to local housing needs. Eligible uses of funds include tenant-based rental assistance; housing rehabilitation; assistance to homebuyers; and new construction of housing. HOME funding may also be used for site acquisition, site improvements, demolition, relocation, and other necessary and reasonable activities related to the development of non-luxury housing. Funds may not be used for public housing development, public housing operating costs, or for Section 8 tenant-based assistance, nor may they be used to provide non-federal matching contributions for other federal programs, for operating subsidies for rental housing, or for activities under the Low-Income Housing Preservation Act. The locations of HOME activities are derived from addresses provided by HUD grantees from 1996 to present in HUDs Integrated Disbursement and Information System (IDIS). Until recently, these addresses were not validated at point of entry. The prevalence of missing or incorrect address data means that HUD cannot guarantee the accuracy of these locations. However, due to recent improvements to IDIS, HUD expects the quality of activity locations to improve over time. All tracts are included, except for those that have a Total Activity Count = 0 or the Total Activity Count is NULL. Data Current As Of: 5/4/2016 This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). HOME Activity by Tract, 2016. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/bk686cy3430.
-
Title: ACS 5 Year CHAS Data by Summary Level 080, 2008-2012
Contributors:- Polygon data
- 2016
Summary: This polygon shapefile contains Comprehensive Housing Affordability Strategy (CHAS) data at the geographic summary level 080 (State - County - County Subdivision - Place/Remainder - Tract). The CHAS is derived from the American Community Survey (ACS) data, which has a smaller sample size than the Decennial Census (which was the basis of the 2000 CHAS). As a result, the Census Bureau cannot produce data using only one year of survey responses, except in very populous areas. For areas with population 65,000 or greater, ACS estimates are available each year using only the most recent year’s survey responses (known as "1-year data"). For areas with population 20,000 or greater, ACS estimates are available each year based on averages of the previous three years of survey responses ("3-year data"). For areas with population less than 20,000—including all census tracts, and many places, counties, and minor civil divisions—the only ACS estimates available are based on averages of the previous five years of survey responses ("5-year data"). The primary purpose of the CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUDs programs (primarily 30, 50, and 80 percent of median income). It is also important to consider the prevalence of housing problems among different types of households, such as the elderly, disabled, minorities, and different household types. The CHAS data provide counts of the numbers of households that fit these HUD-specified characteristics in HUD-specified geographic areas. In addition to estimating low-income housing needs, the CHAS data contribute to a more comprehensive market analysis by documenting issues like lead paint risks, affordability mismatch, and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building. This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). ACS 5 Year CHAS Data by Summary Level 080, 2008-2012. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/rc622nx6841.
-
Title: FHA Insurance in Force by Tract, 2016
Contributors:- Polygon data
- 2016
Summary: The Federal Housing Administration, generally known as "FHA", provides mortgage insurance on loans made by FHA-approved lenders throughout the United States and its territories. FHA insures mortgages on single family and multifamily homes including manufactured homes and hospitals. It is the largest insurer of mortgages in the world, insuring over 34 million properties since its inception in 1934. The insurance in force represents the outstanding balance of an active loan. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Note that this file only includes x, y coordinates and associated attributes for those addresses that can be geocoded to an interpolated point along a street segment, or to the centroid of the nearest U.S. Census block. Please consider this issue when using any datasets provided by HUD. Data is current as of 09/30/2016. This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). FHA Insurance in Force by Tract, 2016. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/tk890cv5706. To learn more: please visit: http://portal.hud.gov/hudportal/HUD?src=/program_offices/housing/fhahistory
-
Title: LED for HOPWA Grantee Areas, 2016
Contributors:- Polygon data
- 2016
Summary: The U.S. Census Bureau, Center for Economic Studies, annual Local Employment Dynamics (LED) database provides a summary of job and worker counts and shares by industry sector. LED data is available at the Census Block geography and aggregated to Summary Level 070 (State + County + County Subdivision + Place/Remainder) geography where it is combined with the Housing Opportunities for Persons with AIDS (HOPWA) information to create the grantee areas. The HOPWA program funds are distributed to states and cities by formula allocations and made available as part of the area's Consolidated Plan. Persons living with HIV/AIDS and their families may require housing that provides emergency, transitional, or long-term affordable solutions. In addition, some projects are selected in national competitions to serve as service delivery models or operate in non-formula areas. Grantees partner with nonprofit organizations and housing agencies to provide housing and support to beneficiaries. To learn more about the LED data, please visit the following website: http://lehd.ces.census.gov/ To learn more about the HOPWA program, please visit the following website: http://portal.hud.gov/hudportal/HUD?src=/program_offices/comm_planning/aidshousing Data is current as: Fiscal Year 2016, Census LED: 2013 This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). LED for HOPWA Grantee Areas, 2016. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/tr455mc1932.
-
Title: Units of General Local Government, 2016
Contributors:- Polygon data
- 2016
Summary: The term "Unit of General Local Government" (UGLG) means a city, county, town, parish, village, or other general-purpose political subdivision of a State. UGLGs are comprised of several Census geographies, summary level 050 (State-County), summary level 060 (County Subdivision), summary level 070 (State-County-County Subdivision-Place/Remainder), summary level 160 (Place), summary level 170 (State-Consolidate City) and the remainder of county boundaries. This version has the CPD entitlement grantees removed. Data Current As Of: FY 2016 This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). Units of General Local Government, 2016. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/hb190bj4432.
-
Title: HUD Insured Hospitals, 2016
Contributors:- Point data
- 2016
Summary: This point shapefile contains the locations of Department of Housing and Urban Development (HUD) insured hospitals. HUD's multifamily property portfolio consists primarily of rental housing properties with five or more dwelling units such as apartments or town houses, but can also be nursing homes, hospitals, elderly housing, mobile home parks, retirement service centers, and occasionally vacant land. The portfolio can be broken down into two basic categories: insured and assisted. HUD provides subsidies and grants to property owners and developers designed to promote the development and preservation of affordable rental units for low-income populations and those with special needs, such as the elderly and disabled. The three largest assistance programs for Multifamily housing are Section 8 Project Based Assistance, Section 202 Supportive Housing for the Elderly, and Section 811 Supportive Housing for Persons with Disabilities. Data Current As Of: 09/30/2016 This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). HUD Insured Hospitals, 2016. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/dh400dz3578.
-
Title: HOPWA Grantee Areas, 2016
Contributors:- Polygon data
- 2016
Summary: The Housing Opportunities for Persons with AIDS (HOPWA) program funds are distributed to states and cities by formula allocations and made available as part of the area's Consolidated Plan. Persons living with HIV/AIDS and their families may require housing that provides emergency, transitional, or long-term affordable solutions. In addition, some projects are selected in national competitions to serve as service delivery models or operate in non-formula areas. Grantees partner with nonprofit organizations and housing agencies to provide housing and support to beneficiaries. Data Current As Of: FY2016 This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.) United States. Department of Housing and Urban Development. (2016). HOPWA Grantee Areas, 2016. United States. Department of Housing and Urban Development. Available at http://purl.stanford.edu/dh985jg7092. To learn more about the HOPWA program, please visit the following website: http://portal.hud.gov/hudportal/HUD?src=/program_offices/comm_planning/aidshousing.