Purpose:This feature layer describes water quality sampling data performed at several operating coal mines in the South Fork of Cherry watershed, West Virginia.Source & Data:Data was downloaded from WV Department of Environmental Protection's ApplicationXtender online database and EPA's ECHO online database between January and April, 2023.There are five data sets here: Surface Water Monitoring Sites, which contains basic information about monitoring sites (name, lat/long, etc.) and NPDES Outlet Monitoring Sites, which contains similar information about outfall discharges surrounding the active mines. Biological Assessment Stations (BAS) contain similar information for pre-project biological sampling. NOV Summary contains locations of Notices of Violation received by South Fork Coal Company from WV Department of Environmental Protection. The Quarterly Monitoring Reports table contains the sampling data for the Surface Water Monitoring Sites, which actually goes as far back as 2018 for some mines. Parameters of concern include iron, aluminum and selenium, among others.A relationship class between Surface Water Monitoring Sites and the Quarterly Monitoring Reports allows access to individual sample results.Processing:Notices of Violation were obtained from the WV DEP AppXtender database for Mining and Reclamation Article 3 (SMCRA) Permitting, and Mining and Reclamation NPDES Permitting. Violation data were entered into Excel and loaded into ArcGIS Pro as a CSV text file with Lat/Long coordinates for each Violation. The CSV file was converted to a point feature class.Water quality data were downloaded in PDF format from the WVDEP AppXtender website. Non-searchable PDFs were converted via Optical Character Recognition, so that data could be copied. Sample results were copied and pasted manually to Notepad++, and several columns were re-ordered. Data was grouped by sample station and sorted chronologically. Sample data, contained in the associated table (SW_QM_Reports) were linked back to the monitoring station locations using the Station_ID text field in a geodatabase relationship class.Water monitoring station locations were taken from published Drainage Maps and from water quality reports. A CSV table was created with station Lat/Long locations and loaded into ArcGIS Pro. It was then converted to a point feature class.Stream Crossings and Road Construction Areas were digitized as polygon feature classes from project Drainage and Progress maps that were converted to TIFF image format from PDF and georeferenced.The ArcGIS Pro map - South Fork Cherry River Water Quality, was published as a service definition to ArcGIS Online.Symbology:NOV Summary - dark blue, solid pointLost Flats Surface Water Monitoring Sites: Data Available - medium blue point, black outlineLost Flats Surface Water Monitoring Sites: No Data Available - no-fill point, thick medium blue outlineLost Flats NPDES Outlet Monitoring Sites - orange point, black outlineBlue Knob Surface Water Monitoring Sites: Data Available - medium blue point, black outlineBlue Knob Surface Water Monitoring Sites: No Data Available - no-fill point, thick medium blue outlineBlue Knob NPDES Outlet Monitoring Sites - orange point, black outlineBlue Knob Biological Assessment Stations: Data Available - medium green point, black outlineBlue Knob Biological Assessment Stations: No Data Available - no-fill point, thick medium green outlineRocky Run Surface Water Monitoring Sites: Data Available - medium blue point, black outlineRocky Run Surface Water Monitoring Sites: No Data Available - no-fill point, thick medium blue outlineRocky Run NPDES Outlet Monitoring Sites - orange point, black outlineRocky Run Biological Assessment Stations: Data Available - medium green point, black outlineRocky Run Biological Assessment Stations: No Data Available - no-fill point, thick medium green outlineRocky Run Stream Crossings: turquoise blue polygon with red outlineRocky Run Haul Road Construction Areas: dark red (40% transparent) polygon with black outlineHaul Road No 2 Surface Water Monitoring Sites: Data Available - medium blue point, black outlineHaul Road No 2 Surface Water Monitoring Sites: No Data Available - no-fill point, thick medium blue outlineHaul Road No 2 NPDES Outlet Monitoring Sites - orange point, black outline

Crowther_Nature_Files.zip This description pertains to the original download. Details on revised (newer) versions of the datasets are listed below. When more than one version of a file exists in Figshare, the original DOI will take users to the latest version, though each version technically has its own DOI. -- Two global maps (raster files) of tree density. These maps highlight how the number of trees varies across the world. One map was generated using biome-level models of tree density, and applied at the biome scale. The other map was generated using ecoregion-level models of tree density, and applied at the ecoregion scale. For this reason, transitions between biomes or between ecoregions may be unrealistically harsh, but large-scale estimates are robust (see Crowther et al 2015 and Glick et al 2016). At the outset, this study was intended to generate reliable estimates at broad spatial scales, which inherently comes at the cost of fine-scale precision. For this reason, country-scale (or larger) estimates are generally more robust than individual pixel-level estimates. Additionally, due to data limitations, estimates for Mangroves and Tropical coniferous forest (as identified by WWF and TNC) were generated using models constructed from Topical moist broadleaf forest data and Temperate coniferous forest data, respectively. Because we used ecological analogy, the estimates for these two biomes should be considered less reliable than those of other biomes . These two maps initially appeared in Crowther et al (2015), with the biome map being featured more prominently. Explicit publication of the data is associated with Glick et al (2016). As they are produced, updated versions of these datasets, as well as alternative formats, will be made available under Additional Versions (see below).

Methods: We collected over 420,000 ground-sources estimates of tree density from around the world. We then constructed linear regression models using vegetative, climatic, topographic, and anthropogenic variables to produce forest tree density estimates for all locations globally. All modeling was done in R. Mapping was done using R and ArcGIS 10.1.

Viewing Instructions: Load the files into an appropriate geographic information system (GIS). For the original download (ArcGIS geodatabase files), load the files into ArcGIS to view or export the data to other formats. Because these datasets are large and have a unique coordinate system that is not read by many GIS, we suggest loading them into an ArcGIS dataframe whose coordinate system matches that of the data (see File Format). For GeoTiff files (see Additional Versions), load them into any compatible GIS or image management program.

Comments: The original download provides a zipped folder that contains (1) an ArcGIS File Geodatabase (.gdb) containing one raster file for each of the two global models of tree density – one based on biomes and one based on ecoregions; (2) a layer file (.lyr) for each of the global models with the symbology used for each respective model in Crowther et al (2015); and an ArcGIS Map Document (.mxd) that contains the layers and symbology for each map in the paper. The data is delivered in the Goode homolosine interrupted projected coordinate system that was used to compute biome, ecoregion, and global estimates of the number and density of trees presented in Crowther et al (2015). To obtain maps like those presented in the official publication, raster files will need to be reprojected to the Eckert III projected coordinate system. Details on subsequent revisions and alternative file formats are list below under Additional Versions.----------

Additional Versions: Crowther_Nature_Files_Revision_01.zip contains tree density predictions for small islands that are not included in the data available in the original dataset. These predictions were not taken into consideration in production of maps and figures presented in Crowther et al (2015), with the exception of the values presented in Supplemental Table 2. The file structure follows that of the original data and includes both biome- and ecoregion-level models.

Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip contains Revision_01 of the biome-level model, but stored in WGS84 and GeoTiff format. This file was produced by reprojecting the original Goode homolosine files to WGS84 using nearest neighbor resampling in ArcMap. All areal computations presented in the manuscript were computed using the Goode homolosine projection. This means that comparable computations made with projected versions of this WGS84 data are likely to differ (substantially at greater latitudes) as a product of the resampling. Included in this .zip file are the primary .tif and its visualization support files.

References:

Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M. N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., Wiser, S. K., Huber, M. O., Hengeveld, G. M., Nabuurs, G. J., Tikhonova, E., Borchardt, P., Li, C. F., Powrie, L. W., Fischer, M., Hemp, A., Homeier, J., Cho, P., Vibrans, A. C., Umunay, P. M., Piao, S. L., Rowe, C. W., Ashton, M. S., Crane, P. R., and Bradford, M. A. 2015. Mapping tree density at a global scale. Nature, 525(7568): 201-205. DOI: http://doi.org/10.1038/nature14967Glick, H. B., Bettigole, C. B., Maynard, D. S., Covey, K. R., Smith, J. R., and Crowther, T. W. 2016. Spatially explicit models of global tree density. Scientific Data, 3(160069), doi:10.1038/sdata.2016.69.

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

The US 301 Asphalt Test Road provides a unique opportunity to evaluate the real-world performance of new asphalt pavement technologies and innovative design concepts. It examines how various factors—such as traffic loads, pavement design, material properties, construction methods, and environmental conditions—interact and affect long-term performance. Built parallel to an existing highway and a concrete test road, the facility allows traffic to be safely diverted when needed, enabling continuous performance monitoring without disrupting regular travel.This facility comprises 12 main sections, with Sections 8 and 10 further divided into two smaller sub-sections. Each section is 1,000 feet long and includes both a travel lane and a passing lane.Sections 1 through 7 are focused on the base layer study, featuring a standard Florida top layer structure with varying base configurations. Section 8 is dedicated to studying reflective cracking and is divided into two 500-foot sub-sections: 8A with crack relief mix and 8B as control. Section 9 features the Superpave 5 study, while Section 10 focuses on a deep-lift pavement design involving two different mix designs and is also split into two 500-foot sub-sections. Sections 11 and 12 are part of the open-graded friction course study, with Section 11 as a common Florida OGFC section and Section 12 as the newly developed quiet friction course test section.Construction work on the test road began in 2023 and continued for about eight months. After completing all paving and safety work, the road was officially opened to public traffic in August 2024. The facility now serves as a real-world testing ground where pavement materials and designs can be evaluated under Florida’s unique traffic loads and weather conditions.

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

The data are derived from interpretation of seismic reflection profiles within the offshore Corinth Rift, Greece (the Gulf of Corinth) integrated with IODP scientific ocean drilling borehole data from IODP Expedition 381 (McNeill et al., 2019a, 2019b). The data include rift fault coordinate (location, geometry) information and slip rate and extension rate information for the major faults. Seismic reflection data were published in Taylor et al. (2011) and in Nixon et al. (2016). Preliminary fault interpretations and rate data, prior to IODP drilling, were published in Nixon et al. (2016). Details of datasets: The data can be viewed in GIS software (ArcGIS, QGIS) or the Excel and .dbf files can be used for viewing of rate data and import of fault coordinates into other software. The 4 folders are for different time periods with shape files for the N-Dipping and S-Dipping Faults in the offshore Corinth Rift and respective slip and extension (horizontal) rates. The shapefiles are digitised fault traces for the basement offsetting faults, picked from the Multichannel Seismic Data collected by the R/V Maurice Ewing. Fault traces are segmented and each segment has an average throw (vertical) rate (Tavg) in mm/yr. The rates for the segments are averages based on measurements at the ends of each segment. The major fault trace segments also have slip-rates (slip_rate) and extension-rates (ext_rate or extension_) in mm/yr. All rates as well as the names for major faults can be located in the attribute table of the shape files along with X- and Y-coordinates. The coordinate system is WGS84 UTM Zone 34N. The shape files can be loaded into a GIS (ArcGIS, QGIS etc.) allowing mapping and visualization of the fault traces and their activity rates. In addition, the attribute tables are .dbf files found within each folder. These have also been provided as .xlsx (Excel) files which include the fault coordinate information, and slip rates and extension rates along the major faults. References McNeill, L.C., Shillington, D.J., Carter, G.D.O., and the Expedition 381 Participants, 2019a. Corinth Active Rift Development. Proceedings of the International Ocean Discovery Program, 381: College Station, TX (International Ocean Discovery Program). McNeill, L.C., Shillington, D.J., et al., 2019b, High-resolution record reveals climate-driven environmental and sedimentary changes in an active rift, Scientific Reports, 9, 3116. Nixon, C.W., McNeill, L.C., Bull, J.M., Bell, R.E., Gawthorpe, R.L., Henstock, T.J., Christodoulou, D., Ford, M., Taylor, B., Sakellariou, S. et al., 2016. Rapid spatiotemporal variations in rift structure during development of the Corinth Rift, central Greece. Tectonics, 35, 1225–1248. Taylor, B., J. R. Weiss, A. M. Goodliffe, M. Sachpazi, M. Laigle, and A. Hirn (2011), The structures, stratigraphy and evolution of the Gulf of Corinth Rift, Greece, Geophys. J. Int., 185(3), 1189–1219.

Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under LIR Parcels.In Spring of 2016, the Land Information Records work group, an informal committee organized by the Governor’s Office of Management and Budget’s State Planning Coordinator, produced recommendations for expanding the sharing of GIS-based parcel information. Participants in the LIR work group included representatives from county, regional, and state government, including the Utah Association of Counties (County Assessors and County Recorders), Wasatch Front Regional Council, Mountainland and Bear River AOGs, Utah League of Cities and Towns, UDOT, DNR, AGRC, the Division of Emergency Management, Blue Stakes, economic developers, and academic researchers. The LIR work group’s recommendations set the stage for voluntary sharing of additional objective/quantitative parcel GIS data, primarily around tax assessment-related information. Specifically the recommendations document establishes objectives, principles (including the role of local and state government), data content items, expected users, and a general process for data aggregation and publishing. An important realization made by the group was that ‘parcel data’ or ‘parcel record’ products have a different meaning to different users and data stewards. The LIR group focused, specifically, on defining a data sharing recommendation around a tax year parcel GIS data product, aligned with the finalization of the property tax roll by County Assessors on May 22nd of each year. The LIR recommendations do not impact the periodic sharing of basic parcel GIS data (boundary, ID, address) from the County Recorders to AGRC per 63F-1-506 (3.b.vi). Both the tax year parcel and the basic parcel GIS layers are designed for general purpose uses, and are not substitutes for researching and obtaining the most current, legal land records information on file in County records. This document, below, proposes a schedule, guidelines, and process for assembling county parcel and assessment data into an annual, statewide tax parcel GIS layer. gis.utah.gov/data/sgid-cadastre/ It is hoped that this new expanded parcel GIS layer will be put to immediate use supporting the best possible outcomes in public safety, economic development, transportation, planning, and the provision of public services. Another aim of the work group was to improve the usability of the data, through development of content guidelines and consistent metadata documentation, and the efficiency with which the data sharing is distributed.GIS Layer Boundary Geometry:GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).Descriptive Attributes:Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systemsCOUNTY_NAME Text 20 - County name including spaces ex. BOX ELDERCOUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessorBOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorderDISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, OtherTAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17ATOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. ResidentialPRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. YHOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor SubdivisionBLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are countedBUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)

Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under LIR Parcels.In Spring of 2016, the Land Information Records work group, an informal committee organized by the Governor’s Office of Management and Budget’s State Planning Coordinator, produced recommendations for expanding the sharing of GIS-based parcel information. Participants in the LIR work group included representatives from county, regional, and state government, including the Utah Association of Counties (County Assessors and County Recorders), Wasatch Front Regional Council, Mountainland and Bear River AOGs, Utah League of Cities and Towns, UDOT, DNR, AGRC, the Division of Emergency Management, Blue Stakes, economic developers, and academic researchers. The LIR work group’s recommendations set the stage for voluntary sharing of additional objective/quantitative parcel GIS data, primarily around tax assessment-related information. Specifically the recommendations document establishes objectives, principles (including the role of local and state government), data content items, expected users, and a general process for data aggregation and publishing. An important realization made by the group was that ‘parcel data’ or ‘parcel record’ products have a different meaning to different users and data stewards. The LIR group focused, specifically, on defining a data sharing recommendation around a tax year parcel GIS data product, aligned with the finalization of the property tax roll by County Assessors on May 22nd of each year. The LIR recommendations do not impact the periodic sharing of basic parcel GIS data (boundary, ID, address) from the County Recorders to AGRC per 63F-1-506 (3.b.vi). Both the tax year parcel and the basic parcel GIS layers are designed for general purpose uses, and are not substitutes for researching and obtaining the most current, legal land records information on file in County records. This document, below, proposes a schedule, guidelines, and process for assembling county parcel and assessment data into an annual, statewide tax parcel GIS layer. gis.utah.gov/data/sgid-cadastre/It is hoped that this new expanded parcel GIS layer will be put to immediate use supporting the best possible outcomes in public safety, economic development, transportation, planning, and the provision of public services. Another aim of the work group was to improve the usability of the data, through development of content guidelines and consistent metadata documentation, and the efficiency with which the data sharing is distributed.GIS Layer Boundary Geometry:GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).Descriptive Attributes:Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systemsCOUNTY_NAME Text 20 - County name including spaces ex. BOX ELDERCOUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessorBOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorderDISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, OtherTAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17ATOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. ResidentialPRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. YHOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor SubdivisionBLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are countedBUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)

Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpageunder LIR Parcels.In Spring of 2016, the Land Information Records work group, an informal committee organized by the Governor’s Office of Management and Budget’s State Planning Coordinator, produced recommendations for expanding the sharing of GIS-based parcel information. Participants in the LIR work group included representatives from county, regional, and state government, including the Utah Association of Counties (County Assessors and County Recorders), Wasatch Front Regional Council, Mountainland and Bear River AOGs, Utah League of Cities and Towns, UDOT, DNR, AGRC, the Division of Emergency Management, Blue Stakes, economic developers, and academic researchers. The LIR work group’s recommendations set the stage for voluntary sharing of additional objective/quantitative parcel GIS data, primarily around tax assessment-related information. Specifically the recommendations document establishes objectives, principles (including the role of local and state government), data content items, expected users, and a general process for data aggregation and publishing. An important realization made by the group was that ‘parcel data’ or ‘parcel record’ products have a different meaning to different users and data stewards. The LIR group focused, specifically, on defining a data sharing recommendation around a tax year parcel GIS data product, aligned with the finalization of the property tax roll by County Assessors on May 22nd of each year. The LIR recommendations do not impact the periodic sharing of basic parcel GIS data (boundary, ID, address) from the County Recorders to AGRC per 63F-1-506 (3.b.vi). Both the tax year parcel and the basic parcel GIS layers are designed for general purpose uses, and are not substitutes for researching and obtaining the most current, legal land records information on file in County records. This document, below, proposes a schedule, guidelines, and process for assembling county parcel and assessment data into an annual, statewide tax parcel GIS layer. gis.utah.gov/data/sgid-cadastre/ It is hoped that this new expanded parcel GIS layer will be put to immediate use supporting the best possible outcomes in public safety, economic development, transportation, planning, and the provision of public services. Another aim of the work group was to improve the usability of the data, through development of content guidelines and consistent metadata documentation, and the efficiency with which the data sharing is distributed.GIS Layer Boundary Geometry:GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).Descriptive Attributes:Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systemsCOUNTY_NAME Text 20 - County name including spaces ex. BOX ELDERCOUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessorBOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorderDISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, OtherSalt Lake County Tax Exempt codes below:AE - Airport - ExemptCC - Commercial Common AreaCE - Conservation EasementCM - CemeteryEC - Exempt CharitableEE - Exempt EducationER - Exempt ReligiousGB - GreenbeltHE - Homeowners Assoc ExemptIL - In LieuIR - Irrigation CompanyMC - Master CardOE - Owner ExemptPE - Part ExemptPR - Pro-RatedPT - Privilege TaxPY - Privilege Tax on a YieldSA - State AssessedSC - State and Cnty AssessedSE - Special - ExemptSU - Salt Lake - Utah CntyTD - Divided Tax DistrictUI - Undivided_Interest TAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17ATOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. ResidentialSalt Lake County Property Class codes below:R - Residential / CondoC - CommercialI - IndustrialRE - RecreationalA - AgriculturalMH - Multi HousingMore information about the PROP_CLASS and PROP_TYPE for Salt Lake County can be found at http://slco.org/assessor/new/queryproptyp.cfmPROP_TYPE (expected) Text 100 - Single Family Res.,Townhome, CondoPRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. YHOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor SubdivisionBLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are countedBUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)

DC Middle School Attendance. This dataset shows D.C. public middle school attendance areas, and added to the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO). The boundaries were recommended by the Advisory Committee on Student Assignment and accepted by the Mayor. These new boundaries will go into effect in the 2015-16 school year and significant phasing in policies will be put into place. See DME.dc.gov for more information.All DC GIS data is stored and exported in Maryland State Plane coordinates NAD 83 meters.

This project aims to identify areas in Los Angeles that are at high risk of crime in the future and to propose optimal locations for new police stations in those areas. By applying machine learning to post-COVID-19 crime data and various socioeconomic indicators, we predict crime risk at the ZIP Code level. Using a location-allocation model, we then determine suitable locations for new police stations to improve coverage of high-risk zones. The results of our analysis can support the efficient allocation of public safety resources in response to growing demand and budget constraints, helping city officials optimize law enforcement services. The content of the archive- Jupyter Notebook- Data (GeoJSON, CSV)- Summary report PDF FileThe platform on which the notebook should be run.This notebook is designed to run on Datahub.Project materials - Project Material we created on AGOL 1 Los Angeles Crime Hotspothttps://ucsdonline.maps.arcgis.com/home/item.html?id=4bddbae65c164f2d9b0285e09cb2820e 2 Choropleth Map of Predicted Crime Levels by ZIP Codehttps://ucsdonline.maps.arcgis.com/home/item.html?id=e47abb448f0a411ab77c6ac754ba0c34 3. Optimizing LA Police Station: A Location Allocation Analysishttps://ucsdonline.maps.arcgis.com/home/item.html?id=2409da85c3fe410e9578a0eaaed8471e - ArcGIS StoryMaphttps://ucsdonline.maps.arcgis.com/home/item.html?id=cfbd4fc27a3b400296e4e31555951d27 Software dependencies - pandas: Used for loading, formatting, and performing matrix operations on tabular data.- geopandas: Used for loading and processing spatial data, including spatial joins and coordinate transformations.- shapely.geometry.Point: Used to create spatial point objects from latitude and longitude coordinates.- arcgis.gis, arcgis.features, arcgis.geometry, arcgis.geoenrichment: Used to retrieve and manipulate geographic data from ArcGIS Online and to extract population statistics using the GeoEnrichment module.- numpy: Used for feature matrix formatting and numerical computations prior to model training.- IPython.display (display, Markdown, Image): Used to format and display Markdown text, data tables, and images within Jupyter Notebooks.- scikit-learn: Used for building and evaluating machine learning models. Specifically, it was used for data preprocessing (StandardScaler), splitting data (train_test_split), model selection and tuning (GridSearchCV, cross_val_score), training various regressors (e.g.,LinearRegression, RandomForestRegressor, KNeighborsRegressor), and assessing performance using metrics such as R², RMSE, and MAE.Other Components we used - ArcGIS Online: Used to create and host interactive web maps for spatial visualization and public presentation purposes.- Flourish: Used to create interactive graphs and charts for visualizing trends and supporting the analysis.

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

Point feature class and related table containing the Precise Surveys measurement time series. Measurements include elevations, Northings and Eastings, distances, and point-to-point measurements. Northing and Easting measurements are in CA State Plane Coordinate systems, Elevations measurements are provided in NAVD88 or NGVD29. This dataset is for data exploration only. These measurements and point locations are not considered survey-grade since there may be nuances such as epochs, adjustments, and measurement methods that are not fully reflected in the GIS data. These values are not considered authoritative values and should not be used in-lieu of actual surveyed values provided by a licensed land surveyor. Related data and time series are stored in a table connected to the point feature class via a relationship class. There may be multiple table entries and time series associated to a single mark. Data was assembled through an import of Excel tables and import of mark locations in ArcGIS Pro. Records were edited by DOE, Geomatics, GDSS to resolve any non-unique mark names. This dataset was last updated 4/2024.

Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under LIR Parcels.In Spring of 2016, the Land Information Records work group, an informal committee organized by the Governor’s Office of Management and Budget’s State Planning Coordinator, produced recommendations for expanding the sharing of GIS-based parcel information. Participants in the LIR work group included representatives from county, regional, and state government, including the Utah Association of Counties (County Assessors and County Recorders), Wasatch Front Regional Council, Mountainland and Bear River AOGs, Utah League of Cities and Towns, UDOT, DNR, AGRC, the Division of Emergency Management, Blue Stakes, economic developers, and academic researchers. The LIR work group’s recommendations set the stage for voluntary sharing of additional objective/quantitative parcel GIS data, primarily around tax assessment-related information. Specifically the recommendations document establishes objectives, principles (including the role of local and state government), data content items, expected users, and a general process for data aggregation and publishing. An important realization made by the group was that ‘parcel data’ or ‘parcel record’ products have a different meaning to different users and data stewards. The LIR group focused, specifically, on defining a data sharing recommendation around a tax year parcel GIS data product, aligned with the finalization of the property tax roll by County Assessors on May 22nd of each year. The LIR recommendations do not impact the periodic sharing of basic parcel GIS data (boundary, ID, address) from the County Recorders to AGRC per 63F-1-506 (3.b.vi). Both the tax year parcel and the basic parcel GIS layers are designed for general purpose uses, and are not substitutes for researching and obtaining the most current, legal land records information on file in County records. This document, below, proposes a schedule, guidelines, and process for assembling county parcel and assessment data into an annual, statewide tax parcel GIS layer. gis.utah.gov/data/sgid-cadastre/ It is hoped that this new expanded parcel GIS layer will be put to immediate use supporting the best possible outcomes in public safety, economic development, transportation, planning, and the provision of public services. Another aim of the work group was to improve the usability of the data, through development of content guidelines and consistent metadata documentation, and the efficiency with which the data sharing is distributed.GIS Layer Boundary Geometry:GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).Descriptive Attributes:Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systemsCOUNTY_NAME Text 20 - County name including spaces ex. BOX ELDERCOUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessorBOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorderDISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, OtherTAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17ATOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. ResidentialPRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. YHOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor SubdivisionBLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are countedBUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)

There are many useful strategies for preparing GIS data for Next Generation 9-1-1. One step of preparation is making sure that all of the required fields exist (and sometimes populated) before loading into the system. While some localities add needed fields to their local data, others use an extract, transform, and load process to transform their local data into a Next Generation 9-1-1 GIS data model, and still others may do a combination of both.There are several strategies and considerations when loading data into a Next Generation 9-1-1 GIS data model. The best place to start is using a GIS data model schema template, or an empty file with the needed data layout to which you can append your data. Here are some resources to help you out. 1) The National Emergency Number Association (NENA) has a GIS template available on the Next Generation 9-1-1 GIS Data Model Page.2) The NENA GIS Data Model template uses a WGS84 coordinate system and pre-builds many domains. The slides from the Virginia NG9-1-1 User Group meeting in May 2021 explain these elements and offer some tips and suggestions for working with them. There are also some tips on using field calculator. Click the "open" button at the top right of this screen or here to view this information.3) VGIN adapted the NENA GIS Data Model into versions for Virginia State Plane North and Virginia State Plane South, as Virginia recommends uploading in your local coordinates and having the upload tools consistently transform your data to the WGS84 (4326) parameters required by the Next Generation 9-1-1 system. These customized versions only include the Site Structure Address Point and Street Centerlines feature classes. Address Point domains are set for address number, state, and country. Street Centerline domains are set for address ranges, parity, one way, state, and country. 4) A sample extract, transform, and load (ETL) for NG9-1-1 Upload script is available here.Additional resources and recommendations on GIS related topics are available on the VGIN 9-1-1 & GIS page.

This is the data repository for the PLOS ONE Manuscript: "Meeting radiation dosimetry capacity requirements of population-scale exposures by geostatistical sampling". This repository contains the following data:

1. "State-and-Subdivision-Boundary-Files.Edited-for-ArcMap-10.4.KML-Format.zip":

This file contains modified U.S. state and sub-division boundary files [in KML format], which can be imported into ArcMap using its KMLtoLayer function. These files have been modified to prevent sub-division naming issues that we encountered when importing boundary data into ArcMap: A) State sub-divisions with identical names are considered a single sub-division by ArcMap (corrected by adding a letter after each sub-division of the same name, i.e. CenterA, CenterB, etc), and; B) ArcMap would only identify the sub-division by its first word if sub-division name contained spaces (corrected by converting all spaces into dashes).

1. "HPAC-Plumes.Processed.zip" and "HPAC-Plumes.Unprocessed.zip":

These files contain HPAC plume coordinate (WGS1984) and dose (in cGy) values for all scenarios discussed in the manuscript. We provide "processed" and "unprocessed" HPAC plume data files. The "unprocessed" HPAC plume data is provided in its original XML format, which cannot be imported into ArcMap directly. The "processed" HPAC plumes are provided in tab-delimited X,Y,Z format (Latitude, Longitude, and Dose). We have also added a "0 cGy" contour in the "processed" plumes (surrounding the HPAC plume), as the presence of unirradiated data points adjacent to the plume was found to be crucial for accurate kriging, since these points served as boundaries for kriging.

1. "Final-Derived-Plumes.Data-Points.zip":

This file contains geostatistically-derived plume coordinate (WGS1984) and dose (in cGy) values for all scenarios discussed in the manuscript. Data is in comma-delimited format (Latitude, Longitude, and Dose). Data points consist of a set of initial coordinates generated at random locations within each Census sub-division using the ArcMap tool, ‘CreateRandomPoints_management’, and subsequent points generated by densification (the geostatistical procedure that targets and localizes an additional small cohort of irradiated individuals to mitigate uncertainty in environmental measurements). These data points were assigned radiation level values corresponding to the adjacent outer HPAC contour by a script comparing each sample with its location within the HPAC plume of the same scenario.

1. “Intermediate-Derived-Plumes.Data-Points.zip”

This archive contains coordinate data (WGS1984) and dose values (in cGy) for all intermediary steps of plume development (using our geostatistical method) for all scenarios. Like (3), the data is comma-delimited (Latitude, Longitude, and Dose), and were assigned radiation level values by a script comparing sampling locations with the location of the HPAC plume of the same scenario. Scenario replicate folders contains text files for each iteration step of the plume derivation process, including a file containing just the initial random sampling (“Iteration-1”), a file containing initial sampling and sampling locations selected by the first densification step (“Iteration-2”), a file containing initial sampling and sampling locations selected by the first and second densification steps (“Iteration-3”), and so on.

This archive also contains a Table (“Progression-of-New-Densification-Selected-Sampling-Locations-For-All-Scenarios.xslx”) which provides a categorical breakdown of how many unique densification-selected sampling locations occur within the irradiated region (i.e. overlap the HPAC plume) for each iteration of all scenario replicates. The fraction of irradiated to unirradiated sampling locations varies among each scenario and individual replicates for the same scenario. Our analysis shows that these results depend on the population densities and exact topography of the HPAC plume which is different among each scenario.

1. "Geostatistical-Sampling-Project.All-Scripts.zip"

This archive contains all programs required for this project. This includes Python scripts meant to be run within the ArcMap software environment (for random point generation and data extraction), and Perl scripts used to process HPAC and U.S. State and Sub-division boundary files, and to assign radiation values to sample locations based on a modified HPAC plume. A java program, “CompareReplicates.jar”, compares the overlapping areas between a pair of polygons that overlap one other using the ArcMap software environment, and requires access to the ArcGIS Runtime SDK (https://developers.arcgis.com/arcgis-runtime/).

Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under LIR Parcels.In Spring of 2016, the Land Information Records work group, an informal committee organized by the Governor’s Office of Management and Budget’s State Planning Coordinator, produced recommendations for expanding the sharing of GIS-based parcel information. Participants in the LIR work group included representatives from county, regional, and state government, including the Utah Association of Counties (County Assessors and County Recorders), Wasatch Front Regional Council, Mountainland and Bear River AOGs, Utah League of Cities and Towns, UDOT, DNR, AGRC, the Division of Emergency Management, Blue Stakes, economic developers, and academic researchers. The LIR work group’s recommendations set the stage for voluntary sharing of additional objective/quantitative parcel GIS data, primarily around tax assessment-related information. Specifically the recommendations document establishes objectives, principles (including the role of local and state government), data content items, expected users, and a general process for data aggregation and publishing. An important realization made by the group was that ‘parcel data’ or ‘parcel record’ products have a different meaning to different users and data stewards. The LIR group focused, specifically, on defining a data sharing recommendation around a tax year parcel GIS data product, aligned with the finalization of the property tax roll by County Assessors on May 22nd of each year. The LIR recommendations do not impact the periodic sharing of basic parcel GIS data (boundary, ID, address) from the County Recorders to AGRC per 63F-1-506 (3.b.vi). Both the tax year parcel and the basic parcel GIS layers are designed for general purpose uses, and are not substitutes for researching and obtaining the most current, legal land records information on file in County records. This document, below, proposes a schedule, guidelines, and process for assembling county parcel and assessment data into an annual, statewide tax parcel GIS layer. gis.utah.gov/data/sgid-cadastre/ It is hoped that this new expanded parcel GIS layer will be put to immediate use supporting the best possible outcomes in public safety, economic development, transportation, planning, and the provision of public services. Another aim of the work group was to improve the usability of the data, through development of content guidelines and consistent metadata documentation, and the efficiency with which the data sharing is distributed.GIS Layer Boundary Geometry:GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).Descriptive Attributes:Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systemsCOUNTY_NAME Text 20 - County name including spaces ex. BOX ELDERCOUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessorBOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorderDISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, OtherTAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17ATOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. ResidentialPRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. YHOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor SubdivisionBLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are countedBUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)

An exclusive economic zone (EEZ) is a sea zone prescribed by the United Nations Convention on the Law of the Sea over which a sovereign state has special rights over the exploration and use of marine resources, including energy production from water and wind. The 200 NM zone is measured, country-by-country, from another maritime boundary, the baseline (usually but not in all cases the mean low-water mark, used is not the same thing as the coast line. For each country, the official list of the baseline points is obtained from the United Nations Law of the Sea Maritime Space (http://www.un.org/depts/los/LEGISLATIONANDTREATIES/regionslist.htm).

The data for this layer were obtained from http://www.marineregions.org/eezmethodology.php. The Preferred Citation for this data is Flanders Marine Institute (VLIZ) (2014), Maritime Boundaries Geodatabase, version 8 in conjunction with NOAA. The exclusive economic zone (EEZ) limits and boundaries were created for NOAA's purposes only to update the charted maritime limits and maritime boundaries on NOAA charts and for official depiction, please see NOAA's paper or raster nautical charts (Sourced from NOAA_Version 4.1, 9/10/2013). NOAA provides shapefiles of the Exclusive Economic Zones for different regions of the United States and its overseas territories. In a second phase the database of negotiated treaties from the United Nations Law of the Sea was consulted and imported into a GIS. The geographic coordinates from the documents were converted to decimal degrees and imported into a database. After importing them in ArcGIS, the points were connected by a line. The remaining boundaries were calculated in a GIS in accordance with the United Nations Convention on the Law of the Sea: a 200 Nautical Mile buffer was drawn from the baseline or a median line between 2 countries was calculated.

Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under LIR Parcels.In Spring of 2016, the Land Information Records work group, an informal committee organized by the Governor’s Office of Management and Budget’s State Planning Coordinator, produced recommendations for expanding the sharing of GIS-based parcel information. Participants in the LIR work group included representatives from county, regional, and state government, including the Utah Association of Counties (County Assessors and County Recorders), Wasatch Front Regional Council, Mountainland and Bear River AOGs, Utah League of Cities and Towns, UDOT, DNR, AGRC, the Division of Emergency Management, Blue Stakes, economic developers, and academic researchers. The LIR work group’s recommendations set the stage for voluntary sharing of additional objective/quantitative parcel GIS data, primarily around tax assessment-related information. Specifically the recommendations document establishes objectives, principles (including the role of local and state government), data content items, expected users, and a general process for data aggregation and publishing. An important realization made by the group was that ‘parcel data’ or ‘parcel record’ products have a different meaning to different users and data stewards. The LIR group focused, specifically, on defining a data sharing recommendation around a tax year parcel GIS data product, aligned with the finalization of the property tax roll by County Assessors on May 22nd of each year. The LIR recommendations do not impact the periodic sharing of basic parcel GIS data (boundary, ID, address) from the County Recorders to AGRC per 63F-1-506 (3.b.vi). Both the tax year parcel and the basic parcel GIS layers are designed for general purpose uses, and are not substitutes for researching and obtaining the most current, legal land records information on file in County records. This document, below, proposes a schedule, guidelines, and process for assembling county parcel and assessment data into an annual, statewide tax parcel GIS layer. gis.utah.gov/data/sgid-cadastre/It is hoped that this new expanded parcel GIS layer will be put to immediate use supporting the best possible outcomes in public safety, economic development, transportation, planning, and the provision of public services. Another aim of the work group was to improve the usability of the data, through development of content guidelines and consistent metadata documentation, and the efficiency with which the data sharing is distributed.GIS Layer Boundary Geometry:GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).Descriptive Attributes:Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systemsCOUNTY_NAME Text 20 - County name including spaces ex. BOX ELDERCOUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessorBOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorderDISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, OtherTAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17ATOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. ResidentialPRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. YHOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor SubdivisionBLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are countedBUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)

Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under LIR Parcels.In Spring of 2016, the Land Information Records work group, an informal committee organized by the Governor’s Office of Management and Budget’s State Planning Coordinator, produced recommendations for expanding the sharing of GIS-based parcel information. Participants in the LIR work group included representatives from county, regional, and state government, including the Utah Association of Counties (County Assessors and County Recorders), Wasatch Front Regional Council, Mountainland and Bear River AOGs, Utah League of Cities and Towns, UDOT, DNR, AGRC, the Division of Emergency Management, Blue Stakes, economic developers, and academic researchers. The LIR work group’s recommendations set the stage for voluntary sharing of additional objective/quantitative parcel GIS data, primarily around tax assessment-related information. Specifically the recommendations document establishes objectives, principles (including the role of local and state government), data content items, expected users, and a general process for data aggregation and publishing. An important realization made by the group was that ‘parcel data’ or ‘parcel record’ products have a different meaning to different users and data stewards. The LIR group focused, specifically, on defining a data sharing recommendation around a tax year parcel GIS data product, aligned with the finalization of the property tax roll by County Assessors on May 22nd of each year. The LIR recommendations do not impact the periodic sharing of basic parcel GIS data (boundary, ID, address) from the County Recorders to AGRC per 63F-1-506 (3.b.vi). Both the tax year parcel and the basic parcel GIS layers are designed for general purpose uses, and are not substitutes for researching and obtaining the most current, legal land records information on file in County records. This document, below, proposes a schedule, guidelines, and process for assembling county parcel and assessment data into an annual, statewide tax parcel GIS layer. gis.utah.gov/data/sgid-cadastre/It is hoped that this new expanded parcel GIS layer will be put to immediate use supporting the best possible outcomes in public safety, economic development, transportation, planning, and the provision of public services. Another aim of the work group was to improve the usability of the data, through development of content guidelines and consistent metadata documentation, and the efficiency with which the data sharing is distributed.GIS Layer Boundary Geometry:GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).Descriptive Attributes:Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systemsCOUNTY_NAME Text 20 - County name including spaces ex. BOX ELDERCOUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessorBOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorderDISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, OtherTAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17ATOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. ResidentialPRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. YHOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor SubdivisionBLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are countedBUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)