The boundaries for Kentucky's 15 Area Development Districts or ADDs. Derived from Kentucky's county boundary polygon layer.Download: https://ky.box.com/v/kymartian-KyBnds-ADDs

This map shows the Housing and Urban Development Areas in Jackson County and was Map 12 in the Jackson County Community Fire Plan. The page size is 11 inches by 17 inches.

The Neighborhood Development Area designation encourages municipalities and/or developers to plan for new and infill housing in the area within walking distance of its designated downtown, village center, new town center, or within its designated growth center and incentivizes needed housing, further supporting the commercial establishments in the designated centers. If available, the data is submitted by the Regional Planning Commissions as Shapefiles otherwise the approved map is scanned and digitized or parcel boundaries are used to build the boundary. Learn more about the Vermont Designation Programs.

Developer Areas by Construction Status (Proposed, Topsoil Stripping and Grading, Base Asphalt, Basetop Asphalt, Top Asphalt) showing assigned Inspectors, inspector boundaries and corresponding City File Numbers

Welcome to Apiscrapy, your ultimate destination for comprehensive location-based intelligence. As an AI-driven web scraping and automation platform, Apiscrapy excels in converting raw web data into polished, ready-to-use data APIs. With a unique capability to collect Google Address Data, Google Address API, Google Location API, Google Map, and Google Location Data with 100% accuracy, we redefine possibilities in location intelligence.

Key Features:

Unparalleled Data Variety: Apiscrapy offers a diverse range of address-related datasets, including Google Address Data and Google Location Data. Whether you seek B2B address data or detailed insights for various industries, we cover it all.

Integration with Google Address API: Seamlessly integrate our datasets with the powerful Google Address API. This collaboration ensures not just accessibility but a robust combination that amplifies the precision of your location-based insights.

Business Location Precision: Experience a new level of precision in business decision-making with our address data. Apiscrapy delivers accurate and up-to-date business locations, enhancing your strategic planning and expansion efforts.

Tailored B2B Marketing: Customize your B2B marketing strategies with precision using our detailed B2B address data. Target specific geographic areas, refine your approach, and maximize the impact of your marketing efforts.

Use Cases:

Location-Based Services: Companies use Google Address Data to provide location-based services such as navigation, local search, and location-aware advertisements.

Logistics and Transportation: Logistics companies utilize Google Address Data for route optimization, fleet management, and delivery tracking.

E-commerce: Online retailers integrate address autocomplete features powered by Google Address Data to simplify the checkout process and ensure accurate delivery addresses.

Real Estate: Real estate agents and property websites leverage Google Address Data to provide accurate property listings, neighborhood information, and proximity to amenities.

Urban Planning and Development: City planners and developers utilize Google Address Data to analyze population density, traffic patterns, and infrastructure needs for urban planning and development projects.

Market Analysis: Businesses use Google Address Data for market analysis, including identifying target demographics, analyzing competitor locations, and selecting optimal locations for new stores or offices.

Geographic Information Systems (GIS): GIS professionals use Google Address Data as a foundational layer for mapping and spatial analysis in fields such as environmental science, public health, and natural resource management.

Government Services: Government agencies utilize Google Address Data for census enumeration, voter registration, tax assessment, and planning public infrastructure projects.

Tourism and Hospitality: Travel agencies, hotels, and tourism websites incorporate Google Address Data to provide location-based recommendations, itinerary planning, and booking services for travelers.

Discover the difference with Apiscrapy – where accuracy meets diversity in address-related datasets, including Google Address Data, Google Address API, Google Location API, and more. Redefine your approach to location intelligence and make data-driven decisions with confidence. Revolutionize your business strategies today!

This is a thin-sheet model of the regional geoelectric field covering the UK and Ireland, which is a combination of the response of the ground conductivity in a region with the spatial and temporal measurements of the rate of change of the horizontal components of the magnetic field. Output from the BGS Space Weather Impact on Ground-based Systems (SWIGS)

Manuscript geological maps produced by the Survey geologists or other recognised geologists on County Series (1:10560) and National Grid (1:10560 & 1:10000) Ordnance Survey base maps of Great Britain. A small number are produced at larger scale. Similar maps compiled from other sources. Maps produced since the 1850's, current holdings over 35,000 maps, all now scanned and available internally as image files.

Index to manuscript geological maps produced by the Survey geologists or other recognised geologists on County Series (1:10560) and National Grid (1:10560 & 1:10000) Ordnance Survey base maps. The index was set up in 1991. Current holdings for Great Britain are over 35,000. There are entries for all registered maps but the level of detail depends on nature of original Survey, ie not all fields are complete for all entries.

This feature set contains the current boundaries of Priority Development Areas (PDAs) used by the Metropolitan Transportation Commission (MTC) and the Association of Bay Area Governments (ABAG) for analysis and mapping related to Plan Bay Area 2050+. These areas, which are nominated by a local government resolution and approved by the ABAG Executive Board, are eligible for grant funding allocated to planning and projects in PDAs.Plan Bay Area 2050+ is the latest update to the long-range Regional Transportation Plan and Sustainable Communities Strategy for the nine-county San Francisco Bay Region. It will update Plan Bay Area 2050, approved in 2021.This PDA feature set is limited to use in general mapping and analysis related to Plan Bay Area 2050+ and the planning activities of local governments that have nominated PDAs.More information on PDA planning at the Association of Bay Area Governments and Plan Bay Area 2050+ can be found at:Priority Development Areas - https://abag.ca.gov/our-work/land-use/pda-priority-development-areas.Plan Bay Area 2050+ -https://abag.ca.gov/our-work/land-use/plan-bay-area-2050.DO NOT USE this feature layer for mapping or analysis related to earlier versions of Plan Bay Area. Data and feature layers for those PDA versions are available as separate resources.

To create this app:

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

HEPGIS is a web-based interactive geographic map server that allows users to navigate and view geo-spatial data, print maps, and obtain data on specific features using only a web browser. It includes geo-spatial data used for transportation planning. HEPGIS previously received ARRA funding for development of Economically distressed Area maps. It is also being used to demonstrate emerging trends to address MPO and statewide planning regulations/requirements , enhanced National Highway System, Primary Freight Networks, commodity flows and safety data . HEPGIS has been used to help implement MAP-21 regulations and will help implement the Grow America Act, particularly related to Ladder of Opportunities and MPO reforms.

The data in this archive was acquired during the development of the GASE (Gradient-Echo Slice Excitation Imaging Asymmetric Spin Echo; GESEPI ASE) technique. GASE can be used to map the reversible transverse relaxation rate R2′ (a contrast used in Magnetic Resonance Imaging - MRI) without the need to separately acquire a magnetic field map to correct for residual magnetic field gradients not compensated by magnet shimming. This technique has application in measuring blood oxygenation using the quantitative BOLD (1,2) (baseline levels) and calibrated BOLD (3) (dynamic changes) techniques as well as iron deposition (4).

This dataset consists of three experiments; - phantom.zip containing an initial validation of the GASE technique. - fmapping.zip used to investigate the distribution of magnetic field gradients in the head. - gesepi.zip where a range of GASE variants were tested against uncorrected ASE.

Images are encoded as compressed NIFTI files and contain basic information about voxel size, repetition time and orientation. Further information is contained in a YAML formatted file, which is both human and machine readable. These files are inherited by image files at lower levels of the directory structure unless they are overridden by a file at the lower level.

Phantom data - phantom.zip

This dataset consists of ASE and GASE4 images acquired with different applied magnetic field gradients in the z-direction: 0, 100, 150 microTesla/meter. A standard phantom based on the FBIRN agar doped construction was used.

Field mapping data - fmapping.zip

This dataset consists of high resolution magnetic field maps in order to investigate the distribution of magnetic field gradients in healthy volunteers. High resolution Magnetisation Prepared RApid Gradient Echo (MPRAGE) images for each subject were acquired for coregistration and segmentation purposes. MPRAGE images are brain extracted (5) in order to preserve anonymity of the subjects.

GESEPI data - gesepi.zip

This dataset consists of 4 different ASE variants for comparison with standard ASE: GASE4, GASE8 and GASE128 (see glossary below). High resolution MPRAGE images for each subject were acquired for coregistration and segmentation purposes. MPRAGE images are brain extracted (5) in order to preserve anonymity of the subjects.

See each individual directory for file naming conventions.

Glossary

EPI - Echo Planar Imaging ASE - Standard Asymmetric Spin Echo data acquired with EPI GASE4 - GESEPI ASE data acquired with 4 subslices (partitions) at 1.24mm each with 3D EPI GASE8 - GESEPI ASE data acquired with 8 subslices (partitions) at 0.63mm each with 3D EPI GASE128 - GASE4 data with doubled in-plane resolution from 64 to 128 matrix

References

1. An H, Lin W. Quantitative measurements of cerebral blood oxygen saturation using magnetic resonance imaging. J. Cereb. Blood Flow Metab. 2000;20:1225–1236. doi: 10.1097/00004647-200008000-00008.
2. He X, Yablonskiy DA. Quantitative BOLD: Mapping of human cerebral deoxygenated blood volume and oxygen extraction fraction: Default state. Magn. Reson. Med. 2007;57:115–126. doi: 10.1002/mrm.21108.
3. Blockley NP, Griffeth VEM, Simon AB, Dubowitz DJ, Buxton RB. Calibrating the BOLD response without administering gases: Comparison of hypercapnia calibration with calibration using an asymmetric spin echo. Neuroimage 2015;104:423–429. doi: 10.1016/j.neuroimage.2014.09.061.
4. Ordidge RJ, Gorell JM, Deniau JC, Knight RA, Helpern JA. Assessment of relative brain iron concentrations using T2-weighted and T2*-weighted MRI at 3 Tesla. Magn. Reson. Med. 1994;32:335–341.
5. Smith SM. Fast robust automated brain extraction. Hum. Brain Mapp. 2002;17:143–155. doi: 10.1002/hbm.10062.

HUD is organized into 10 Regions where each Region is managed by a Regional Administrator, who also oversees the Regional Office. Each Field Office within a Region is managed by a Field Office Director, who reports to the Regional Administrator. There is at least one HUD Field Office in every State and a total of 10 Regional Offices. Staff who answer the main office telephone will be able to respond to or direct your calls to the appropriate person. To learn more about the HUD Field Office Locations visit: https://www.huduser.gov/portal/regions/Regional.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_HUD Field Office LocationsDate of Coverage: Current Data Updated: As Needed

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Point Conception map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Point Conception map area data layers. Data layers are symbolized as shown on the associated map sheets.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Following development of vegetation classifications after plot sampling, the preliminary vegetation map was further edited and refined in 2005. Using ArcGIS 9.0, polygon boundaries were revised on-screen based on plot data and additional field observations collected during 2004 field visits. Field notes and limited field mapping supplemented GIS mapping. Each polygon was attributed with a map class name that is the common name of a USNVC association, a park-specific map class name representing a variant of an association, or an Anderson Level II use/land cover map class based on plot data, field observations, aerial photography signatures, and topographic maps. Map units in the 2005 vegetation map were equivalent to the association level with few exceptions. The overall 2005 map accuracy and Kappa index was 76%, which fell below the USGS/NPS vegetation mapping protocol requirement of 80%. Revisions were subsequently made to the 2005 vegetation map to increase the accuracy of the final product. The final 2007 vegetation map accuracy was 85.7% and Kappa index was 84.6%.

Environmentally critical area layer used as an overlay for the City of Seattle Zone Development Capacity Model. Areas represent the ECAs that would reduce the amount of development on a development site. This layer is for analytical purposes only and does not represent actual regulatory areas or development regulation, rather an approximation of the potential impact on a development site.

This dataset represents coverage data harmonized according to INSPIRE. It is an airborne geophysical map representing the total residual field. This image has been reprojected to EPSG:3035. Description copied from here

In 1984, the General Assembly enacted the Chesapeake Bay Critical Area Act to regulate development, manage land use and conserve natural resources on land in those areas designated as Critical Area. For this document, the Critical Area is all land and water areas within 1000 feet of the tidal waters' edge or from the landward edge of adjacent tidal wetlands and the lands under them. Georeferenced digital data files of the critical Area have been produced for Baltimore City and the 16 Maryland counties with land located within the Critical Area. The digital maps produced for each jurisdiction are polygons depicting the Critical Area and the land use classifications recognized by the Chesapeake Bay Critical Area Commission (CBCAC). Each jurisdiction is a separate file. The data were produced from hard copy parcel maps originally submitted by the counties as part of the requirements for developing their Critical Area Program. For the purpose of the MD iMap web service the Critical Area Data is displayed by two data layers, one general layer and one layer showing the available critical area data for local towns.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link: https://mdgeodata.md.gov/imap/rest/services/Environment/MD_CriticalAreas/MapServer/1