The Dams dataset is a representation of the National Inventory of Dams (NID), maintained and published by the U.S. Army Corps of Engineers, in cooperation with the Association of State Dam Safety Officials, the states, territories, and federal agencies. It is also part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The Dams dataset (NID) includes all known dams of the United States and its territories, that meet the federal definition of a dam. Dams where downstream flooding would likely result in loss of human life (high hazard potential). Dams where downstream flooding would likely result in disruption of access to critical facilities, damage to public and private facilities, and require difficult mitigation efforts (significant hazard potential). Dams that meet minimum height and reservoir size requirements, even though they do not pose the same level of life or economic risk as those above - these low hazard potential dams equal or exceed 25 feet in height and exceed 15 acre-feet in storage, or equal or exceed 50 acre-feet storage and exceed 6 feet in height. The database contains more than 70 data fields for each dam. This includes the dam's location, size, purpose, type, last inspection, and regulatory facts. The information is updated periodically by the state and federal agencies, reflected by the "Data Last Updated Date". For more information on dams, visit the NID web site at https://nid.sec.usace.army.mil/#. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529016

This is a demonstration layer implementing INSPIRE Protected Sites (PS) - Nature Conservation (Surface) data according to the INSPIRE default data model. It is provided as a courtesy and should not be used for any purpose other than demonstration.DEMONSTRATION NOTE: This dataset uses the default INSPIRE data model (rather than flattened/streamlined Alternative Encoding). It is published from ArcGIS Pro to ArcGIS Enterprise with OGC map services enabled (WMS and WFS), then INSPIRE-specific custom capabilities are manually added to the INSPIRE View Service (WMS). This web service is then registered in ArcGIS Online and shared via the ArcGIS Hub catalog.About Protected SitesA protected site is an area designated or managed within a framework of international, Community and Member States' legislation to achieve specific conservation objectives. According to IUCN and adopted for the INSPIRE context a protected site is: An area of land and/or sea especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means.

Protected sites may be located in terrestrial, aquatic and/or marine environments, and may be under either public or private ownership. Learn more

This feature service is used by Rock County personnel to show addresses which contain permitted Private Onsite Wastewater Treatment Systems.Please note: Not all systems are on this map. Condo units such as Grand Videre, do not have a permit, missed by the original inventory, or there was a Tax ID number change that occurred may not be displayed. If you have questions or would like to report a system that is not on the map, please contact the Rock County Department of Public Health.

This web map shows the data on stock and completions of houses by district in Hong Kong. It is a subset of data made available by the Rating and Valuation Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong CSDI Portal at https://portal.csdi.gov.hk.

This web map shows the Private Building in Hong Kong. It is a set of data made available by the Home Affairs Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data is in FGDB format and has been processed and converted into Esri File Geodatabase format and uploaded to Esri's ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort. For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong CSDI Portal at https://portal.csdi.gov.hk.

The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

The Gap Analysis Program (GAP) is an element of the U.S. Geological Survey (USGS). GAP helps to implement the Department of Interior?s goals of inventory, monitoring, research, and information transfer. GAP has three primary goals: 1 Identify conservation gaps that help keep common species common; 2 Provide conservation information to the public so that informed resource management decisions can be made; and 3 Facilitate the application of GAP data and analysis to specific resource management activities. To implement these goals, GAP carries out the following objectives: --Map the land cover of the United States --Map predicted distributions of vertebrate species for the U.S. --Map the location, ownership and stewardship of protected areas --Document the representation of vertebrate species and land cover types in areas managed for the long-term maintenance of biodiversity --Provide this information to the public and those entities charged with land use research, policy, planning, and management --Build institutional cooperation in the application of this information to state and regional management activities. GAP provides the following data and web services: The Protected Areas Database of the United States (PAD-US) is a geodatabase that illustrates and describes public land ownership, management and other conservation lands, including voluntarily provided privately protected areas. The PADUS GAP Status Layer web service can be found at http://gis1.usgs.gov/arcgis/rest/services/gap/PADUS_Status/MapServer . The Land Cover Data creates a seamless data set for the contiguous United States from the four regional Gap Analysis Projects and the LANDFIRE project. The Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx . In addition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer The GAP species range data show a coarse representation of the total areal extent of a species or the geographic limits within which a species can be found (Morrison and Hall 2002). The GAP species distribution models represent the areas where species are predicted to occur based on habitat associations. A full report documenting the parameters used in each species model can be found via: http://gis1.usgs.gov/csas/gap/viewer/species/Map.aspx Web map services for species distribution models can be accessed from: http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Birds http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Mammals http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Amphibians http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Reptiles A table listing all of GAP's available web map services can be found here: http://gapanalysis.usgs.gov/species/data/web-map-services/

This web map shows the location of private primary schools in Hong Kong. It is a set of data made available by the Education Bureau under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and uploaded to Esri's ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong CSDI Portal at https://portal.csdi.gov.hk.

Dataset for the maps accompanying the Housing in Aotearoa New Zealand: 2025 report. This dataset contains counts and measures for:

• average number of private dwellings per square kilometre
• severe housing deprivation
• home ownership rates
• mould and damp.

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Data is available by territorial authority and Auckland local board.

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Average number of private dwellings per square kilometre has data for occupied, unoccupied, and total private dwellings from the 2013, 2018, and 2023 Censuses, including:

• dwelling counts
• percentage change in the count of dwellings
• average number of dwellings per square kilometre.

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Severe housing deprivation has data for the census usually resident population from the 2018 and 2023 Censuses, including:

• estimated prevalence rate of severe housing deprivation (per 10,000 people)
• estimated rate for those; without shelter, in temporary accommodation, sharing someone else’s private dwelling, in uninhabitable housing, for whom it could not be determined whether they were severely housing deprived or not.

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Home ownership rates has data for households in occupied private dwellings from the 2013, 2018, and 2023 Censuses, including:

• counts and percentages for households that owned their home or held it in a family trust, or did not own their home
• percentage change in the count of households that owned their home or held it in a family trust, or did not own their home.

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Mould and damp has data for occupied private dwellings from the 2018 and 2023 Censuses, including:

• counts and percentages for dwellings with or without mould or damp
• percentage change in the count of dwellings with or without mould or damp.

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Map shows the average number of private dwellings per square kilometre for the 2023 Census

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Map shows the estimated prevalence rate of severe housing deprivation (per 10,000 people) for the census usually resident population for the 2023 Census.

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Map shows the percentage of households in occupied private dwellings that owned their home or held it in a family trust for the 2023 Census.

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Map shows the percentage of occupied private dwellings that were damp or mouldy for the 2023 Census.

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Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city. 

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Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts. 

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

​

Severe housing deprivation time series

The 2018 estimates of severe housing deprivation have been updated using the 2023 methodology for estimating severe housing deprivation. Severe housing deprivation (homelessness) estimates – updated methodology: 2023 Census has more information.

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Severe housing deprivation

Figures in this map and geospatial file exclude Women’s refuge data, as well as estimates for children living in non-private dwellings. Severe housing deprivation (homelessness) estimates – updated methodology: 2023 Census has more information.

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Dwelling density

This data shows the average number of private dwellings (occupied and unoccupied) per square kilometre of land for an area. This is a measure of dwelling density.

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About the 2023 Census dataset

For information on the 2023 Census dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Census usually resident population count concept quality rating

The census usually resident population count is rated as very high quality.

Census usually resident population count – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Quality of severe housing deprivation data

Severe housing deprivation (homelessness) estimates – updated methodology: 2023 Census has more information on the data quality of this variable.

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Dwelling occupancy status quality rating

Dwelling occupancy status is rated as high quality.

Dwelling occupancy status – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Dwelling type quality rating

Dwelling type is rated as moderate quality.

Dwelling type – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Tenure of household quality rating

Tenure of household is rated as moderate quality.

Tenure of household – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Dwelling dampness indicator quality rating

Dwelling dampness indicator is rated as moderate quality.

Housing quality – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Dwelling mould indicator quality rating

Dwelling mould indicator is rated as moderate quality.

Housing quality – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Using data for good

Stats NZ expects that, when working with census

Dataset for the maps accompanying the Housing in Aotearoa New Zealand: 2025 report. This dataset contains data for severe housing deprivation from the 2018 and 2023 Censuses.

​

Data is available by health district.

​

Severe housing deprivation has data for the census usually resident population from the 2018 and 2023 Censuses, including:

• estimated prevalence rate of severe housing deprivation (per 10,000 people)
• estimated rate for those; without shelter, in temporary accommodation, sharing someone else’s private dwelling, in uninhabitable housing, for whom it could not be determined whether they were severely housing deprived or not.

​

Map shows the estimated prevalence rate of severe housing deprivation (per 10,000 people) for the census usually resident population for the 2023 Census.

​

Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

​

Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

​

Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city. 

​

Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts. 

​

Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

​

Severe housing deprivation time series

The 2018 estimates of severe housing deprivation have been updated using the 2023 methodology for estimating severe housing deprivation. Severe housing deprivation (homelessness) estimates – updated methodology: 2023 Census has more information.

​

Severe housing deprivation

Figures in this map and geospatial file exclude Women’s refuge data, as well as estimates for children living in non-private dwellings. Severe housing deprivation (homelessness) estimates – updated methodology: 2023 Census has more information.

​

About the 2023 Census dataset

For information on the 2023 Census dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

​

Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

​

Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

​

Census usually resident population count concept quality rating

The census usually resident population count is rated as very high quality.

Census usually resident population count – 2023 Census: Information by concept has more information, for example, definitions and data quality.

​

Quality of severe housing deprivation data

Severe housing deprivation (homelessness) estimates – updated methodology: 2023 Census has more information on the data quality of this variable.

​

Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

This dataset provides title information (excluding ownership) where there is a relationship to one or more primary parcels.

A Record of Title is a record of a property's owners, legal description and the rights and responsibilities registered against the title.This dataset does not contain any ownership information so that it can be freely distributed. If ownership information is required, you need to apply for access.

There can be multiple parcels associated with a title, and a title may only have a part share in a parcel. This means the shape representing the title will be an aggregation of all parcels that the title is associated with. The ‘spatial extents shared’ attribute when equal to ‘false’ will indicate that title has exclusive interest over all of the shape (this will be case for the vast majority).

The originating data for parcel/title associations includes some non-official sources where the official data does not support a link. For more information see the LINZ website

APIs and web services This dataset is available via ArcGIS Online and ArcGIS REST services, as well as our standard APIs. LDS APIs and OGC web services ArcGIS Online map services

The Los Angeles County Storm Drain System is a geometric network model representing the storm drain infrastructure within Los Angeles County. The long term goal of this network is to seamlessly integrate the countywide drainage infrastructure, regardless of ownership or jurisdiction. Current uses by the Department of Public Works (DPW) include asset inventory, operational maintenance, and compliance with environmental regulations.

GIS DATA DOWNLOADS: (More information is in the table below)

File geodatabase: A limited set of feature classes comprise the majority of this geometric network. These nine feature classes are available in one file geodatabase (.gdb). ArcMap versions compatible with the .gdb are 10.1 and later. Read-only access is provided by the open-source software QGIS. Instructions on opening a .gdb file are available here, and a QGIS plugin can be downloaded here.

Acronyms and Definitions (pdf) are provided to better understand terms used.

ONLINE VIEWING: Use your PC’s browser to search for drains by street address or drain name and download engineering drawings. The Web Viewer link is: https://dpw.lacounty.gov/fcd/stormdrain/

MOBILE GIS: This storm drain system can also be viewed on mobile devices as well as your PC via ArcGIS Online. (As-built plans are not available with this mobile option.)

More About these Downloads All data added or updated by Public Works is contained in nine feature classes, with definitions listed below. The file geodatabase (.gdb) download contains these eleven feature classes without network connectivity. Feature classes include attributes with unabbreviated field names and domains.

ArcMap versions compatible with the .gdb are 10.1 and later.

Feature Class Download Description

CatchBasin In .gdb Catch basins collect urban runoff from gutters

Culvert In .gdb A relatively short conduit that conveys storm water runoff underneath a road or embankment. Typical materials include reinforced concrete pipe (RCP) and corrugated metal pipe (CMP). Typical shapes are circular, rectangular, elliptical, or arched.

ForceMain In .gdb Force mains carry stormwater uphill from pump stations into gravity mains and open channels.

GravityMain In .gdb Underground pipes and channels.

LateralLine In .gdb Laterals connect catch basins to underground gravity mains or open channels.

MaintenanceHole In .gdb The top opening to an underground gravity main used for inspection and maintenance.

NaturalDrainage In .gdb Streams and rivers that flow through natural creek beds

OpenChannel In .gdb Concrete lined stormwater channels.

PumpStation In .gdb Where terrain causes accumulation, lift stations are used to pump stormwater to where it can once again flow towards the ocean

Data Field Descriptions

Most of the feature classes in this storm drain geometric network share the same GIS table schema. Only the most critical attributes are listed here per LACFCD operations.

Attribute Description

ASBDATE The date the design plans were approved “as-built” or accepted as “final records”.

CROSS_SECTIN_SHAPE The cross-sectional shape of the pipe or channel. Examples include round, square, trapezoidal, arch, etc.

DIAMETER_HEIGHT The diameter of a round pipe or the height of an underground box or open channel.

DWGNO Drain Plan Drawing Number per LACFCD Nomenclature

EQNUM Asset No. assigned by the Department of Public Works’ (in Maximo Database).

MAINTAINED_BY Identifies, to the best of LAFCD’s knowledge, the agency responsible for maintaining the structure.

MOD_DATE Date the GIS features were last modified.

NAME Name of the individual drainage infrastructure.

OWNER Agency that owns the drainage infrastructure in question.

Q_DESIGN The peak storm water runoff used for the design of the drainage infrastructure.

SOFT_BOTTOM For open channels, indicates whether the channel invert is in its natural state (not lined).

SUBTYPE Most feature classes in this drainage geometric nature contain multiple subtypes.

UPDATED_BY The person who last updated the GIS feature.

WIDTH Width of a channel in feet.

This digital soil survey information is used by soil scientists, hydrologists, ecologists, planners and other land managers to locate, compare, and select suitable areas for major kinds of land uses; to identify areas that need more intensive investigations; and to evaluate various management alternatives and predict the effects of the particular alternative on the land. Other intended uses of the soil survey include, but are not limited to, providing federal, state, and private organizations with resource information as it relates to activities such as power transmission right-of-way, coastal zone management, forest land management plans, mineral and energy exploration and development, and site suitability for buildings and dwellings. Tongass National Forest soil scientists began mapping soils in the early 1960s. By 1992 mapping was largely completed for approximately 10 million acres of the forest. During mapping, polylines were created using tones and textures on aerial photographs and field-verification. Soil map units were digitized from polygons drawn on 1:31,680 scale Mylar maps. Polygons on aerial photos were traced onto Mylar overlay sheets using a rapidiograph pen, which is accurate to .035 inches of the source data. Polygons were digitized to .001 inches of their location of the digitizing source (Mylar overlay). Accounting for the possibility of cumulative errors during transfer and digitizing, positional accuracy may vary by ± 250 feet. More recent inventories like Yakutat and South Kruzof were pre-mapped using on-screen digitizing with orthophotos and contours as base maps. Historically, the forest was divided into three soil survey areas-Stikine, Chatham, and Ketchikan. These areas are indicated in the FOREST field of the attribute table as follows: 2 = Stikine, 3 = Chatham, 5 = Ketchikan. By the end of the 1990s the digital soil inventory for the three survey areas on the forest were aggregated into one feature class. Beginning in the late 2000s an effort was made to move the soil inventory to Web Soil Survey (WSS). Each survey area was correlated separately. Updates to line work have occurred since 2010 to include areas not previously mapped. In 2020 a fourth area, the Yakutat Forelands was incorporated in WSS and the forest-wide feature class updated with that information. Line work for the southern half of Kruzof Island is included in this feature class but is currently in the correlation process and is not yet available on WSS. The update in 2020 also used all available line work from WSS to make the forest-wide dataset consistent with the data on WSS. Stikine Area (FOREST = 2): All lands within the Stikine Administrative Area have been mapped. This includes all federal, state, and private lands, including wilderness. The soil is mapped at different intensities across the area based on their Land Use Designations (LUDs) in the Tongass Land Management Plan, USDA-FS, 1979. Generally, areas designated for intensive land use (LUD III) are mapped at larger scales (Order 3 level, 1:15,840), while other areas designated for low intensity land use (LUD I&II) are mapped at smaller scales (Order 4 level, 1:31,680). Some areas that are currently LUD I&II were mapped to Order 3 prior to designation. All of the Stikine Area is mapped to an Order 3 level with the exception of the following, which were mapped to Order 4: the Stikine-LeConte Wilderness Area (Farm and Dry Islands are mapped to Order 3), Anan Creek area, and mainland areas designated for semi-remote recreation use. For exact locations, see Preliminary Soil Resource Inventory Report, Stikine Area. Order 3 surveys were mapped on 1:15,840 scale aerial photos. This resulted in map delineations no smaller than approximately 3 acres, ranging up to several hundred acres. The map units in the Order 3 survey area are composed of soil associations, some consociations and some complexes. The Order 4 surveys were mapped on 1:31,680 scale high-altitude infrared aerial photographs. This resulted in map units no smaller than approximately 10 acres and ranged as high as 500 acres in size. The map units in the Order 4 survey area are composed of phases of soil families, or subgroups. Design of initial mapping units in the Stikine area was strongly influenced by soil-vegetation relationships. This is referred to as the "Soil Ecosystem" type of mapping units, which are defined based on natural vegetation types, corresponding soil properties and associated landform types. Map units were also broken out by slope class.Chatham Area (FOREST = 3): The Chatham Area soil survey covers approximately 4.5 million acres of the Tongass National Forest. The inventory occurred in two stages and was done at two levels of detail. An Order 3 survey was conducted from 1981 to 1984, and an Order 4 survey was conducted from 1987 to 1989. Wilderness areas, national monuments, ANILCA additions, state, private and native lands were not mapped. The Order 3 survey is composed primarily of areas referred to as "Land Use Designations (LUDs) III and IV in the Tongass Land Management Plan, USDA-FS, 1979. LUD III were managed for a combination of uses, including recreation and some timber harvest. LUD IV were allocated to intensive resource use and development opportunities, primarily timber harvest and mining. Both LUD III and IV areas required the greater detail of an Order 3 survey. The Order 4 survey is composed primarily of LUD II. LUD II areas were allocated to roadless area management. The lower intensity management of LUD II justified a less detailed Order 4 survey. For exact locations, see Chatham Area Ecological Unit Inventory User Guide, figure 1. The inventory area was pre-mapped on either color aerial photographs at a scale of 1:15,840 (Order 3) or high altitude, color infrared aerial photographs at a scale of 1:63,360 (Order 4). South Kruzof soil survey covers about 60,795 acres of the Tongass National Forest. It represents the soils on the young Mount Edgecumbe volcanic field. The area was initially mapped during the 1981 to 1984 Order 3 Chatham soil survey. A second effort to gather more data began in 1994 but was not completed at that time. The effort to map South Kruzof restarted during 2009 and was completed in 2011. It was mapped digitally at a scale of 1:31,680 on 1998 2-meter black and white Digital Ortho Quads. The Yakutat soil survey covers about 487,758 acres of the Tongass, primarily on the Yakutat Forelands. This survey was also started during the 1981 to 1984 Order 3 soil survey. Additional data was collected in 1987, 1989, 1991, 1992, and 1993. The Yakutat survey was picked up again in 2009 and completed in 2013, although the mountainous areas are still unmapped. Yakutat was mapped digitally at a scale of 1:31,680 on 2008 Color 1 meter Digital Ortho Quarter Quads. The NRCS completed correlation on the Yakutat mapping area in 2020 but has not completed correlation of South Kruzof. The Chatham inventory was strongly influenced by soil-landform relationships. Additionally, vegetation, geology, and soils information was used to stratify the landscape into natural integral units that reflect ecological processes. Map units were also broken out by slope classes. The mapping criteria are based on features that may be either directly observed or inferred from natural landscape and vegetative features viewed on an aerial photograph. The intent of the mapping is to delineate integral ecological units that provide information required to achieve National Forest System management objectives. The Yakutat SMUs are nested in the landtype associations (LTAs) that were mapped in Landtype Associations of the Yakutat Foreland by Michael Shephard and Terry Brock (Technical Publication No. R10-TP-109, 2002). These LTAs were generalized for the soil survey.Ketchikan Area (FOREST = 5): The Ketchikan soil survey area covers approximately 3 million acres. It includes all of the area previously known as the Ketchikan Administrative Area except the following: Misty Fjords National Monument Wilderness and non-wilderness areas, the South Prince of Wales area and large tracts of federal (Bureau of Land Management), state, private borough and municipal lands. These unmapped lands are found on Cleveland Peninsula, Revillagigedo Island, Sukkwan Island, Long Island, Dall Island and Prince of Wales Island. Areas within the Ketchikan Area Soil Survey are mapped at different levels of intensity. Those designated as moderate and intensive development under the 1997 Tongass Land Management Plan (1997 TLMP) Revision, are mapped at an Order 3 level. Most wilderness areas were not included in the soil survey, although some areas now designated as wilderness and National Monument or 'Mostly Natural Setting' were mapped prior to those designations. These areas include: outside islands (Noyes, Lulu and Baker), Mt Calder/Mt. Holbrook Area, Salmon Bay, Coronation Island, Maurelle Islands, Warren Island, and the Karta River. Some other lands identified in the 1997 TLMP Revision under Wilderness and National Monument and 'Mostly Natural' settings were mapped at an Order 4 level. These areas include: Duke, Hotspur and Cat Islands, Cleveland Peninsula (North of Yes Bay), Bell Island, area east of Naha Bay, and area north of Cholmondeley Sound. For exact locations, see Ketchikan Area Soil Survey User Guide, Tongass N.F., p. 13. The Order 3 surveys were mapped on 1:15,840 or 1:40,000 aerial photos. This resulted in map delineations no smaller than approximately 3 acres ranging up to several hundred acres. The Order 3 survey areas are composed approximately of one-third each of map units of soil consociations, associations and complexes. The Order 4 surveys were mapped on 1:15,840 colored aerial photographs. This resulted in map delineations no smaller than approximately 10 acres and ranging as high as 500 acres in size. The map units are composed of phases of series, soil families, or subgroups.The criteria

**Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse. They are therefore identical and share the same refresh schedule. This map service is used by the GeoATLAS web application, sub-section Resource Map in the Mineral Exploration theme. It includes Base Metals Potential, Coal Potential, Gold Potential, Helium Potential, Bitumen (Oil Sands) Potential, Lithium Potential, Potash and Salt Resource Potential, Rare Earth Elements Potential and Uranium Potential schema in Production Data Warehouse. Note: Oil and Gas pools are found in the /Petroleum service.

The County zoning is not directly associated to parcels. The zoning polygons are managed separately from parcels therefore the zoning may not be coincidental to a parcel. Some parcels are created with more than one zoning value. for regulation about zoning, please refer to the Development Service Planning and Zoning Ordinance for the unincorporated areas of Yavapai County, Arizona. Please view other information on the Development Services County web page, https://YavapaiAZ.gov/devserv. The web service in WGS 1984 Web Mercator Auxiliary Sphere (WKID 3857). This data was intended for general location mapping purposes and is not suitable for legal, engineering, or surveying purposes. The intended purpose of this published data is for the County mapping application hosted on (gis.yavapai.us) and ArcGIS Online. Using a Map Service to share for Open Data.Access is granted to public agencies, educational institutions, non-profit organizations and private individuals for non-commercial purpose. For commercial use of the data see Arizona Revised Statutes 39-121.03. But per AGIC, Arizona Revised Statutes 27-178 section B in the Geospatial data sharing, "A public agency that shares geospatial data may exempt the data from commercial use fees prescribed in section 39-121.03, subsection A, paragraph 3." Regarding Arizona Revised Statutes 39-121.03 and the OpenData metadata sentence stating, geospatial data may exempt the data from commercial use fees prescribed in section 39-121.03, subsection A, paragraph 3

This dataset show the point locations of High Frequency (HF) radar systems across the US. HF radars measure the speed and direction of ocean surface currents in near real time. These radars can measure currents over a large region of the coastal ocean, from a few kilometers offshore up to 200 km, and can operate under any weather conditions. They are located near the water’s edge, and need not be situated atop a high point of land. Dozens of institutions own and operate HF radars within the United States, and many are coordinated through the US Integrated Ocean Observing System. Ocean surface current data from these radars are shared on national servers by the National Data Buoy Center and Scripps Institution of Oceanography. If specific information regarding a local radar system is needed, please contact Dr. Jack Harlan, Project Manager for the HF Radar Ocean Remote Sensing, US IOOS Program Office.

© US Integrated Ocean Observing System This layer is a component of Physical Oceanographic and Marine Habitat.

MarineCadastre.gov themed service for public consumption featuring layers related to the Physical and Oceanographic and Marine Habitat themes. This map service presents spatial information about MarineCadastre.gov services across the United States and Territories in the Web Mercator projection. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

© MarineCadastre.gov

This is the publicly shared version of the WFMRD&A merged Communication Sites dataset. View the larger version shared within the NIFC ArcGis Online Organization here. It was created for hazardous fuel treatment planning and wildland fire risk assessment and merges communication sites from the NPS and eight HIFLD Open Data layers. Check with the following authoritative sources for the most accurate and up-to-date information.Contact Wildland Fire Management Research, Development & Application with questions or comments: wfmrda.datasupport@firenet.gov HIFLD Currency: 09/25/2025Source: https://hifld-geoplatform.hub.arcgis.com/search?groupIds=65847c150c8449649bd33a74a0e1050b These layers went offline on 09/26/2025 due to HIFLD Open being DeprecatedAntenna Structure Registrate Broadband Radio Service Cellular Towers Land Mobile Broadcast Land Mobile Commercial Land Mobile Private Microwave Service Paging Transmission NPS Currency: 09/05/2025Source: https://nifc.maps.arcgis.com/home/item.html?id=9acab3e9a58f4667853b77ab75a265bdCommSiteCommunications Site

Lot numbers are converted from an annotation feature class which are related to recorded subdivisions. This data is being hosted on gis.yavapaiaz.gov as a feature web service is in WGS 1984 Web Mercator Auxiliary Sphere (WKID 3857). This data was intended for general location mapping purposes in ArcGIS Online and County applications and is known to be entered but not updated as spatial adjustments are made to the tax parcels. This is being shared for Open Data.Access is granted to public agencies, educational institutions, non-profit organizations and private individuals for non-commercial purpose. For commercial use of the data see Arizona Revised Statutes 39-121.03. But per AGIC, Arizona Revised Statutes 27-178 section B in the Geospatial data sharing, "A public agency that shares geospatial data may exempt the data from commercial use fees prescribed in section 39-121.03, subsection A, paragraph 3." Regarding Arizona Revised Statutes 39-121.03 and the OpenData metadata sentence stating, geospatial data may exempt the data from commercial use fees prescribed in section 39-121.03, subsection A, paragraph 3.

The National Cooperative Soil Survey (NCSS) is a nationwide partnership of Federal, regional, State, and local agencies and private entities and institutions. This partnership works to cooperatively investigate, inventory, document, classify, interpret, disseminate, and publish information about soils. NCSS standards are common or shared procedures that enhance technology transfer, data sharing, and communications among soil survey participants. NCSS cooperators collaborate on efforts to increase our understanding of soils through field studies, soil mapping projects, soil database development, and other technical soil services. NCSS Region Boundaries 2024NCSS Contacts States 2024NCSS Regions MapThe National Cooperative Soil Survey (NCSS) is a nationwide partnership dedicated to soils since 1899! National Cooperative Soil Survey

This web map shows the location of Professional Outreaching Teams for Private Residential Care Homes for Persons with Disabilities (including persons with physical and / or intellectual disabilities, persons in mental recovery or persons with suspected mental health problems, etc.) in Hong Kong. It is a set of the data made available by Social Welfare Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong CSDI Portal at https://portal.csdi.gov.hk.