As Esri’s commercial partner for parcel data, Regrid invites you to enjoy this free tile layer of parcel boundaries covering 100% of the United States. Complete parcel attributes are also available from an integrated Data Store."I think it’s fantastic that this layer exists. It's really helpful for my staff to see parcel boundaries in a quick and accessible layer."- Kate Berg, Geographic Information Systems (GIS) Manager | Department of Environment, Great Lakes, and EnergyVisit the Regrid Data Store for the ArcGIS User CommunityHassle-Free Parcel Data for Esri UsersWhen you click a parcel in the tile layer, you will see its address, size, and parcel ID number, along with a convenient link to purchase additional parcel attributes in The Regrid Data Store for the ArcGIS User Community. Once in the Data Store, you can purchase and download parcel files with attributes by the county and state for use in ArcGIS, as well as our add-on datasets like standardized zoning, matched building footprints, and matched secondary addresses.See regrid.com/esri for all of Regrid’s parcel products for the Esri ecosystem, including Feature Service delivery for ongoing parcel updates at scale.Key Features of Regrid's Parcel DataSourced & Standardized: Data combines authoritative public sources & third-party enrichments, aggregated, standardized, and matched by the Regrid team.158+ Million Parcel Records: Covering all 3,200+ US counties and territories.143+ Standardized Data Fields: Including geometry, ownership, buildings, secondary addresses, land use, and zoning.Universal Parcel ID & Placekey Location Identifier: Ensuring precise identification and integration.Detailed Attributes: Tax assessments, building counts, square footage, stacked parcels (condos), right-of-way, vacancy indicators and USPS deliverability. Comprehensive Coverage: 100% land parcel coverage across the US.Parcel Data Resources & DocumentationRegrid Data Dictionary / Parcel Data SchemaRegrid Coverage ReportParcel Data FAQsThank you to all the GIS professionals, state, county and federal officials, assessors, recorders, and public officials across the country who maintain the nation's parcel data and infrastructure.

TO VIEW AND DOWNLOAD THE ACTUAL DATA, CLICK ON ONE OF THE LAYERS BELOWIn 2022 the Western Reserve Land Conservancy (WRLC) led a project with the City of Cleveland to survey every property in the City, gathering data and photos about structure condition, signs of vacancy, sidewalk condition, and more.For more information, see WRLC's page and content explaining the survey process and results.This service is a modified version of the survey results by City of Cleveland Office of Urban Analytics and Building & Housing. Original fields from the survey results were cleaned and formatted by UAI to a higher standard, with accurate, compliant field names and human-readable aliases.Data GlossaryProperty Survey Data DictionaryAll survey information is in fields prefixed with "survey". All other fields preceding "survey_" fields are part of the survey system and County property data used during the taking of the survey. For more information about the Regrid fields that precede survey fields, see their parcel schema (https://support.regrid.com/parcel-data/schema).The survey is published as 1) parcels (areas), 2) parcel centroids (points at the center of the parcel).This dataset is featured on the following app(s):Cleveland Property Survey Viewer Update FrequencyNeverContactsCity of Cleveland, Building & HousingCity of Cleveland, Urban Analytics & Innovation

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

The layer in question describes faults interpreted to occur within the base of Permian geology within the Arckaringa Basin.

Purpose

Fault deformation was considered an important architectural feature of the Arckaringa basin to map, particularly with respect to the potential for inter-aquifer connectivity with other basins such as the Great Artesian Basin such faulting may engender.

Dataset History

The shapefile was developed by Frogtech in 2013. The generation of this and other interpretations developed by Frogtech followed this work flow pattern: 1.Complete all seismic and well interpretations after mistie analysis and fixes. 2.Define extent polygons for each unit using well data, surface geology polygons, seismic data and faults as constraints. This includes making detailed polygons of inclusions and exclusion areas for each grid to allow for erosional highs etc. 3.Define fault polygons in Kingdom for each surface where there is a mappable, significant offset on a horizon. 4.Create a test grid in twt using the gridding modules in Kingdom. The default gridding parameters used are 200m cell size, fault convergence (where faults are relevant) and moderate grid smoothng. 5.Review and interrogate the test map looking for grid artefacts. Review, check, adjust seismic interpretations as relevant. 6.Regrid. Iterate. 7.Once satisfied with the twt map, depth convert the relevant seismic horizon using the inbuilt Kingdom function to depth-convert by selected time-depth curve. After QA/QC we used the Cootanoorina-2 checkshot data to depth convert horizons in the north and east and the Arkeeta-1 checkshot data to depth convert horizons in the south. 8.Grid the horizon in the depth domain using the depth converted horizon and relevant depth-domain formation tops. 9.Review and assess the resultant draft depth structure map. 10.Remove grid artefacts and adjust interpretation as necessary. Regrid. Iterate. 11.Local smoothing of grids to create continuation of inferred troughs between control points and where first iteration isopachs show grid overlaps. Regrid. Iterate. 12.Create final maps in Kingdom. Export to ArcGIS. Create contours and apply consistent colour stretches to each map.

Dataset Citation

SA Department of Environment, Water and Natural Resources (2015) FrogTech, Permian Geology Base Faults - ARC. Bioregional Assessment Source Dataset. Viewed 26 May 2016, http://data.bioregionalassessments.gov.au/dataset/ab5e2e15-3666-4ad3-a11d-b12e453990f3.