The Peoria County GIS open data website provides GIS data, interactive maps, and digital maps free of charge under an open data license agreement. Please click the Download button to download and view the current Peoria County GIS open data license agreement.Contact InformationEmail: gis@peoriacounty.orgPhysical AddressPeoria County CourthouseIT Service Department - GIS Division324 Main St.Room G11Peoria, IL 61602

This web map references the live tiled map service from the OpenStreetMap (OSM) project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: https://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in ESRI products under a Creative Commons Attribution-ShareAlike license. Tip: This service is one of the basemaps used in the ArcGIS.com map viewer. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10. Tip: Here are some well known locations as they appear in this web map, accessed by launching the web map with a URL that contains location parameters: Athens, Cairo, Jakarta, Moscow, Mumbai, Nairobi, Paris, Rio De Janeiro, Shanghai

MapMasq for Protected Health Data (by GISinc).COVID-19 and regulations being put in place to slow the spread have affected all of us in many ways. There is potential for data science in conjunction with spatial analysis to inform decision-makers during this pandemic through broadly disseminated data—especially data that has protected or geomasked the PHI for HIPAA alignment. In the hope to promote additional data sharing that needs to take place, we at GISinc are offering free trial licenses (until September 20) of a tool that can help: MapMasq. About GISinc..._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

description: USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a planimetric map. USGS digital orthoimage resolution may vary from 6 inches to 1 meter. In the former resolution, every pixel in an orthoimage covers a six inch square of the earth's surface, while in the latter resolution, one meter square is represented by each pixel. Blue Marble: Next Generation source is displayed at small to medium scales. However, the majority of the imagery service source is from the National Agriculture Imagery Program (NAIP) for the conterminous United States. The data is 1-meter pixel resolution with "leaf-on". Collection of NAIP imagery is administered by the U.S. Department of Agriculture's Farm Service Agency (FSA). In areas where NAIP data is not available, other imagery may be acquired through partnerships by the USGS. The National Map program is working on acquisition of high resolution orthoimagery (HRO) for Alaska and Hawaii. Most of the new Alaska imagery data will not be available in this service due to license restrictions. The National Map viewer allows free downloads of public domain, 1-meter resolution orthoimagery in JPEG 2000 (jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution also in JPEG 2000 (jp2) format. For scales below 1:18,000, use the dynamic USGS Imagery Only Large service, https://services.nationalmap.gov/arcgis/rest/services/USGSImageOnlyLarge/MapServer.; abstract: USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a planimetric map. USGS digital orthoimage resolution may vary from 6 inches to 1 meter. In the former resolution, every pixel in an orthoimage covers a six inch square of the earth's surface, while in the latter resolution, one meter square is represented by each pixel. Blue Marble: Next Generation source is displayed at small to medium scales. However, the majority of the imagery service source is from the National Agriculture Imagery Program (NAIP) for the conterminous United States. The data is 1-meter pixel resolution with "leaf-on". Collection of NAIP imagery is administered by the U.S. Department of Agriculture's Farm Service Agency (FSA). In areas where NAIP data is not available, other imagery may be acquired through partnerships by the USGS. The National Map program is working on acquisition of high resolution orthoimagery (HRO) for Alaska and Hawaii. Most of the new Alaska imagery data will not be available in this service due to license restrictions. The National Map viewer allows free downloads of public domain, 1-meter resolution orthoimagery in JPEG 2000 (jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution also in JPEG 2000 (jp2) format. For scales below 1:18,000, use the dynamic USGS Imagery Only Large service, https://services.nationalmap.gov/arcgis/rest/services/USGSImageOnlyLarge/MapServer.

The Peoria County GIS open data website provides GIS data, interactive maps, and digital maps free of charge under an open data license agreement. Peoria County GIS also provides custom GIS services upon request for GIS data and digital maps not available on the open data website. Please click the Download button to download and view the current request form for custom GIS services. All custom services are charged at $60 per hour.Contact InformationEmail: gis@peoriacounty.orgPhysical AddressPeoria County CourthouseIT Service Department - GIS Division324 Main St.Room G11Peoria, IL 61602

An aerial imagery basemap of New Zealand in Web Mercator (WGS 1984) using the latest quality data from Land Information New Zealand.Add the map service directly to your ArcGIS Online map, or copy the Web Map Tile Service (WMTS) URL below for use in the desktop.This basemap is also available in NZTM from: https://linz.maps.arcgis.com/home/item.html?id=39cf07ebf8a2413696d8fd4d80570b84 The LINZ Aerial Imagery Basemap details New Zealand in high resolution - from a nationwide view all the way down to individual buildings.This basemap combines the latest high-resolution aerial imagery down to 5cm in urban areas and 10m satellite imagery to provide full coverage of mainland New Zealand, Chathams and other offshore islands.LINZ Basemaps are powered by data from the LINZ Data Service and other authoritative open data sources, providing you with a basemap that is free to use under an open licence.A XYZ tile API (Web Mercator only) is also available for use in web and mobile applications.See more information or provide your feedback at https://basemaps.linz.govt.nz/.For attribution requirements and data sources see: https://www.linz.govt.nz/data/linz-data/linz-basemaps/data-attribution.

This dataset contains both large (A0) printable maps of the Torres Strait broken into six overlapping regions, based on a clear sky, clear water composite Sentinel 2 composite imagery and the imagery used to create these maps. These maps show satellite imagery of the region, overlaid with reef and island boundaries and names. Not all features are named, just the more prominent features. This also includes a vector map of Ashmore Reef and Boot Reef in Coral Sea as these were used in the same discussions that these maps were developed for. The map of Ashmore Reef includes the atoll platform, reef boundaries and depth polygons for 5 m and 10 m.

This dataset contains all working files used in the development of these maps. This includes all a copy of all the source datasets and all derived satellite image tiles and QGIS files used to create the maps. This includes cloud free Sentinel 2 composite imagery of the Torres Strait region with alpha blended edges to allow the creation of a smooth high resolution basemap of the region.

The base imagery is similar to the older base imagery dataset: Torres Strait clear sky, clear water Landsat 5 satellite composite (NERP TE 13.1 eAtlas, AIMS, source: NASA).

Most of the imagery in the composite imagery from 2017 - 2021.

Method: The Sentinel 2 basemap was produced by processing imagery from the World_AIMS_Marine-satellite-imagery dataset (not yet published) for the Torres Strait region. The TrueColour imagery for the scenes covering the mapped area were downloaded. Both the reference 1 imagery (R1) and reference 2 imagery (R2) was copied for processing. R1 imagery contains the lowest noise, most cloud free imagery, while R2 contains the next best set of imagery. Both R1 and R2 are typically composite images from multiple dates.

The R2 images were selectively blended using manually created masks with the R1 images. This was done to get the best combination of both images and typically resulted in a reduction in some of the cloud artefacts in the R1 images. The mask creation and previewing of the blending was performed in Photoshop. The created masks were saved in 01-data/R2-R1-masks. To help with the blending of neighbouring images a feathered alpha channel was added to the imagery. The processing of the merging (using the masks) and the creation of the feathered borders on the images was performed using a Python script (src/local/03-merge-R2-R1-images.py) using the Pillow library and GDAL. The neighbouring image blending mask was created by applying a blurring of the original hard image mask. This allowed neighbouring image tiles to merge together.

The imagery and reference datasets (reef boundaries, EEZ) were loaded into QGIS for the creation of the printable maps.

To optimise the matching of the resulting map slight brightness adjustments were applied to each scene tile to match its neighbours. This was done in the setup of each image in QGIS. This adjustment was imperfect as each tile was made from a different combinations of days (to remove clouds) resulting in each scene having a different tonal gradients across the scene then its neighbours. Additionally Sentinel 2 has slight stripes (at 13 degrees off the vertical) due to the swath of each sensor having a slight sensitivity difference. This effect was uncorrected in this imagery.

Single merged composite GeoTiff: The image tiles with alpha blended edges work well in QGIS, but not in ArcGIS Pro. To allow this imagery to be used across tools that don't support the alpha blending we merged and flattened the tiles into a single large GeoTiff with no alpha channel. This was done by rendering the map created in QGIS into a single large image. This was done in multiple steps to make the process manageable.

The rendered map was cut into twenty 1 x 1 degree georeferenced PNG images using the Atlas feature of QGIS. This process baked in the alpha blending across neighbouring Sentinel 2 scenes. The PNG images were then merged back into a large GeoTiff image using GDAL (via QGIS), removing the alpha channel. The brightness of the image was adjusted so that the darkest pixels in the image were 1, saving the value 0 for nodata masking and the boundary was clipped, using a polygon boundary, to trim off the outer feathering. The image was then optimised for performance by using internal tiling and adding overviews. A full breakdown of these steps is provided in the README.md in the 'Browse and download all data files' link.

The merged final image is available in export\TS_AIMS_Torres Strait-Sentinel-2_Composite.tif.

Change Log: 2023-03-02: Eric Lawrey Created a merged version of the satellite imagery, with no alpha blending so that it can be used in ArcGIS Pro. It is now a single large GeoTiff image. The Google Earth Engine source code for the World_AIMS_Marine-satellite-imagery was included to improve the reproducibility and provenance of the dataset, along with a calculation of the distribution of image dates that went into the final composite image. A WMS service for the imagery was also setup and linked to from the metadata. A cross reference to the older Torres Strait clear sky clear water Landsat composite imagery was also added to the record.

22 Nov 2023: Eric Lawrey Added the data and maps for close up of Mer. - 01-data/TS_DNRM_Mer-aerial-imagery/ - preview/Torres-Strait-Mer-Map-Landscape-A0.jpeg - exports/Torres-Strait-Mer-Map-Landscape-A0.pdf Updated 02-Torres-Strait-regional-maps.qgz to include the layout for the new map.

Source datasets: Complete Great Barrier Reef (GBR) Island and Reef Feature boundaries including Torres Strait Version 1b (NESP TWQ 3.13, AIMS, TSRA, GBRMPA), https://eatlas.org.au/data/uuid/d2396b2c-68d4-4f4b-aab0-52f7bc4a81f5

Geoscience Australia (2014b), Seas and Submerged Lands Act 1973 - Australian Maritime Boundaries 2014a - Geodatabase [Dataset]. Canberra, Australia: Author. https://creativecommons.org/licenses/by/4.0/ [license]. Sourced on 12 July 2017, https://dx.doi.org/10.4225/25/5539DFE87D895

Basemap/AU_GA_AMB_2014a/Exclusive_Economic_Zone_AMB2014a_Limit.shp The original data was obtained from GA (Geoscience Australia, 2014a). The Geodatabase was loaded in ArcMap. The Exclusive_Economic_Zone_AMB2014a_Limit layer was loaded and exported as a shapefile. Since this file was small no clipping was applied to the data.

Geoscience Australia (2014a), Treaties - Australian Maritime Boundaries (AMB) 2014a [Dataset]. Canberra, Australia: Author. https://creativecommons.org/licenses/by/4.0/ [license]. Sourced on 12 July 2017, http://dx.doi.org/10.4225/25/5539E01878302 Basemap/AU_GA_Treaties-AMB_2014a/Papua_New_Guinea_TSPZ_AMB2014a_Limit.shp The original data was obtained from GA (Geoscience Australia, 2014b). The Geodatabase was loaded in ArcMap. The Papua_New_Guinea_TSPZ_AMB2014a_Limit layer was loaded and exported as a shapefile. Since this file was small no clipping was applied to the data.

AIMS Coral Sea Features (2022) - DRAFT This is a draft version of this dataset. The region for Ashmore and Boot reef was checked. The attributes in these datasets haven't been cleaned up. Note these files should not be considered finalised and are only suitable for maps around Ashmore Reef. Please source an updated version of this dataset for any other purpose. CS_AIMS_Coral-Sea-Features/CS_Names/Names.shp CS_AIMS_Coral-Sea-Features/CS_Platform_adj/CS_Platform.shp CS_AIMS_Coral-Sea-Features/CS_Reef_Boundaries_adj/CS_Reef_Boundaries.shp CS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth5m_Coral-Sea.shp CS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth10m_Coral-Sea.shp

Murray Island 20 Sept 2011 15cm SISP aerial imagery, Queensland Spatial Imagery Services Program, Department of Resources, Queensland This is the high resolution imagery used to create the map of Mer.

Marine satellite imagery (Sentinel 2 and Landsat 8) (AIMS), https://eatlas.org.au/data/uuid/5d67aa4d-a983-45d0-8cc1-187596fa9c0c - World_AIMS_Marine-satellite-imagery

Data Location: This dataset is filed in the eAtlas enduring data repository at: data\custodian\2020-2029-AIMS\TS_AIMS_Torres-Strait-Sentinel-2-regional-maps. On the eAtlas server it is stored at eAtlas GeoServer\data\2020-2029-AIMS.

Please note this dataset is the most recent version of the Administrative Boundaries (AB). For previous versions of the AB please go to this url: https://data.gov.au/dataset/ds-dga-b4ad5702-ea2b-4f04-833c-d0229bfd689e/details?q=previous

Geoscape Administrative Boundaries is Australia’s most comprehensive national collection of boundaries, including government, statistical and electoral boundaries. It is built and maintained by Geoscape Australia using authoritative government data. Further information about contributors to Administrative Boundaries is available here.

This dataset comprises seven Geoscape products:

• Localities
• Local Government Areas (LGAs)
• Wards
• Australian Bureau of Statistics (ABS) Boundaries
• Electoral Boundaries
• State Boundaries and
• Town Points

Updated versions of Administrative Boundaries are published on a quarterly basis.

Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.

Notable changes in the February 2025 release

• There have been spatial changes (area) greater than 1 km2 to the localities ‘Koombooloomba’, ‘Isisford’, ‘Ilfracombe’ and ‘Glen Ruth’ in Queensland.

  • There have been spatial changes (area) greater than 1 km2 to the localities ‘Birdwood’ and ‘Forreston’ in South Australia.

• Three new wards ‘Central Ward’, ’East Ward’ and ’West Ward’ have been added in Northern Territory.

  • ‘Anindilyakwa Ward’ has been retired in Northern Territory.

IMPORTANT NOTE: correction of issues with the 22 November 2022 release

• On 28 November 2022, the Administrative Boundaries dataset originally released on 22 November 2022 was amended and re-uploaded after Geoscape identified some issues with the original data for 'Electoral Boundaries'.
• As a result of the error, some shapefiles were published in 3D rather than 2D, which may affect some users when importing data into GIS applications.
• The error affected the Electoral Boundaries dataset, specifically the Commonwealth boundary data for Victoria and Western Australia, including 'All States'.
• Only the ESRI Shapefile formats were affected (both GDA94 and GDA2020). The MapInfo TAB format was not affected.
• Because the datasets are zipped into a single file, once the error was fixed by Geoscape all of Administrative Boundaries shapefiles had to be re-uploaded, rather than only the affected files.
• If you downloaded either of the two Administrative Boundary ESRI Shapefiles between 22 November and 28 November 2022 and plan to use the Electoral Boundary component, you are advised to download the revised version dated 28 November 2022. Apologies for any inconvenience.

Further information on Administrative Boundaries, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on Administrative Boundaries, including software solutions, consultancy and support.

Note: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.

The Australian Government has negotiated the release of Administrative Boundaries to the whole economy under an open CCBY 4.0 licence.

Users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).

Users must also note the following attribution requirements:

Preferred attribution for the Licensed Material:

Administrative Boundaries © Geoscape Australia licensed by the Commonwealth of Australia under Creative Commons Attribution 4.0 International license (CC BY 4.0).

Preferred attribution for Adapted Material:

Incorporates or developed using Administrative Boundaries © Geoscape Australia licensed by the Commonwealth of Australia under Creative Commons Attribution 4.0 International licence (CC BY 4.0).

What to Expect When You Download Administrative Boundaries

Administrative Boundaries is large dataset (around 1.5GB unpacked), made up of seven themes each containing multiple layers.

Users are advised to read the technical documentation including the product change notices and the individual product descriptions before downloading and using the product.

Please note this dataset is the most recent version of the Administrative Boundaries (AB). For previous versions of the AB please go to this url: https://data.gov.au/dataset/ds-dga-b4ad5702-ea2b-4f04-833c-d0229bfd689e/details?q=previous

License Information

A dataset describing exposed bedrock and surficial geology of Antarctica constructed by the GeoMAP Action Group of SCAR (The Scientific Committee on Antarctic Research) and GNS Science, New Zealand. Legacy geological map data have been captured into a geographic information system (GIS), refining its spatial reliability, harmonising classification, then improving representation of glacial sequences and geomorphology. A total 99,080 polygons have been unified for depicting geology at 1:250,000 scale, but locally there are some areas with higher spatial precision. Geological definition in GeoMAP v.2022-08 is founded on a mixed chronostratigraphic- and lithostratigraphic-based classification. Description of rock and moraine polygons employs international GeoSciML data protocols to provide attribute-rich and queriable data; including bibliographic links to 589 source maps and scientific literature. Data are provided under CC-BY License as zipped ArcGIS geodatabase, QGIS geopackage or GoogleEarth kmz files. GeoMAP is the first detailed geological dataset covering all of Antarctica. GeoMAP depicts 'known geology' of rock exposures rather than 'interpreted' sub-ice features and is suitable for continent-wide perspectives and cross-discipline interrogation.

The Local Government Transparency Code 2015 was published by the Department for Communities and Local Government in February 2015. The Code sets out key principles for local authorities in creating greater transparency through the publication of public data.This data is published under The Open Government Licence. This is a free open licence for public sector bodies to license the use and re-use of their information and data easily. If you are intending to use or re-use any of our data please note the conditions of the licence.The Government's transparency agenda encourages local authorities to make public data openly available, as part of this items of spending via our Purchase Cards can be seen by financial year.Certain data may be redacted to comply with the Freedom of Information and Data Protection Acts

This feature contains the spatial representation of public fishing piers, jetties and breakwaters defined in Section 1.88 of Title 14, California Code of Regulations (CCR). Public piers must be connected to the shoreline, allow for free, unrestricted public access, and have been built or currently function for the primary purpose of fishing.Publicly owned jetties and breakwaters may also be "public piers" but, in addition, must form the most seaward protective boundary of an ocean harbor. Jetties and other structures that are not the most seaward boundary are not public piers.Even though a fishing license is not required on a public pier, all other regulations (including minimum size, bag limits, report cards, and seasons) apply while fishing from a public pier. Additionally, only two rods and lines, handlines, or nets, traps, or other appliances used to take crabs may be used per person on a public pier (CCR Title 14, Section 28.65(b)).PLEASE NOTE: CDFW cannot guarantee that individual piers, jetties, or breakwaters will be open to the public. The landowner may close these areas for safety, maintenance, or other reasons at any time.Attributes: Pier: Common name/identifier of public fishing location. County: County where fishing location is located. Lat_ddm: Latitude of fishing location in degrees decimal minutes Long_ddm: Longitude of fishing location in degrees decimal minutes. Notes: Any special considerations or closures associated with the fishing location.

Fire Stations in New Hampshire Any location where fire fighters are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Fire Departments not having a permanent location are included, in which case their location has been depicted at the city/town hall or at the center of their service area if a city/town hall does not exist. This dataset includes those locations primarily engaged in forest or grasslands fire fighting, including fire lookout towers if the towers are in current use for fire protection purposes. This dataset includes both private and governmental entities. Fire fighting training academies are also included. This dataset is comprised completely of license free data. The Fire Station dataset and the EMS dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 01/07/2005 and the newest record dates from 07/14/2008.

The information was extracted from the Driver Licence Register (DLR) and is current as at 1 July 2023.The data is a distinct count of individuals.An snapshot of licence holders is taken every year covering the annual period of 1st July to 30th June which covers Waka Kotahi's financial year. The data is limited to current licence holders with the following licence classes:Class 1 Motor Cars and Light Motor Vehicles - learner, restricted or fullClass 6 Motorcycles, Moped or ATV - learner, restricted or full.An individual licence holder will be included in more than one count if both class 1 and class 6 are held.A licence holder must hold a full Class 1 (Car) licence before they can apply for a heavy vehicle licence.The data is also limited to current licence holders issued with a photo driver licence (PDL).Region is determined by the physical town or suburb recorded for the driver. It may not reflect the driver's current address.We added low-population regions into a 'Misc' grouping. These regions are Gisborne, Tasman and West Coast.We have not included license holders under 16, because the legal age to get a learner's license increased from from 15 to 16 on 1 August 2011.Data quality statement: Address fields are free text and may contain errors which lead to incorrect coding.Addresses in the driver licence register can often be out of date. It’s therefore difficult to establish what proportion of licence holders are actually still based in a certain location.Address fields are updated when we receive notification of a change of address from the licence holder.Notifications for a change of address may come:directly from the licence holder (for example, the licence holder calling the contact centre and updating their address)as an outcome of a transaction against the licence holder on the DLR (including the processing of an application at a driver licensing outlet with an address update).Data quality caveats: See data quality statement.A legacy Excel file is available here (current to 1 July 2023) but will not be updated in future.

Lesson: Use distributed raster analysis to analyze burn severity, slope and landcover.Wildfires make the landscape more susceptible to landslides when rainstorms pass through an area after wildfires. Post-fire debris flows are particularly hazardous because they can occur with little warning, can exert great impulsive loads on objects in their paths, and can strip vegetation, block drainage ways, damage structures, and endanger human life. Often there is not enough time between a fire and a rainstorm to implement an effective emergency response plan. However, various post-fire debris-flow hazard assessment models have been developed to estimate the probability and volume of debris flows that may occur in response to a storm.For more detailed information on hazard assessment, review the following resources:Emergency Assessment of Post-Fire Debris-Flow HazardsPost-fire debris-flow modelsUSDA/USFS site for burn area emergency responseIn this lesson, you will use ArcGIS Enterpriseconfigured for distributed raster analysis using ArcGIS Image Server. In the steps, you will create a landslide risk map to kick off more advanced debris-flow hazard assessment modeling. Creating the landslide risk map uses raster function chains to derive a burn severity map, topographic slope map, and a land-cover index map, which are combined into one processing chain for ArcGIS Enterprise to execute.The use of distributed raster analysis for this workflow demonstrates how ArcGIS Enterprise can be deployed in a rapid way to process large volumes of data across a widely affected area. However, when using raster and image analysis tools in ArcGIS Pro, a similar workflow may be developed and deployed without the benefit of distributed raster analysis. In addition, functionality in ArcGIS Image for ArcGIS Online may also be used to achieve similar results.This lesson was last tested on January 31, 2021, using ArcGIS Pro 2.9. If you're using a different version of ArcGIS Pro, you may encounter different functionality and results.View final resultRequirementsArcGIS Pro (get a free trial)ArcGIS Enterprise 10.6.1 or later: base deployment with a dedicated ArcGIS Image ServerArcGIS Image Server license for ArcGIS EnterpriseLesson Plan1. Configure the image serverSet up ArcGIS Enterprise to perform distributed raster processing.20 minutes2. Create a landslide risk mapUse raster function templates to create a map that summarizes landslide risk by watershed.1 hour3. Share a web appConfigure a web app to share your findings with your ArcGIS Enterprise account.10 minutes

This web map references the live tiled map service from the OpenStreetMap (OSM) project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: https://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in ESRI products under a Creative Commons Attribution-ShareAlike license. Tip: This service is one of the basemaps used in the ArcGIS.com map viewer. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10. Tip: Here are some well known locations as they appear in this web map, accessed by launching the web map with a URL that contains location parameters: Athens, Cairo, Jakarta, Moscow, Mumbai, Nairobi, Paris, Rio De Janeiro, Shanghai

Voting Precincts in Macon-Bibb County. Elections in the county are managed by the Macon-Bibb County Board of Elections.

Voters who cast their votes in person must show one of six forms of photo identification. If the voter votes BY MAIL, they DO NOT need a photo ID. Photo ID rules ONLY APPLY to IN-PERSON voting by absentee, advance voting or at the polling place on Election Day.

· A current or expired Georgia driver’s license (or Department of Driver Services identification card);

· A valid United States military photo identification card;

· A valid photo identification card issued by any branch, department agency, or entity of the United States, Georgia, or any other state authorized by law to issue personal identification, including a FREE Georgia Voter Identification Card;

· A valid employee photo identification card issued by any branch, department, agency, or entity of the United States, Georgia, or any county, municipality, board, authority of other entity of Georgia;

· A valid United States passport; or

· A valid tribal photo identification card.

Any elector who registered for the first time in Georgia by mail, and did not provide identification at the time of registering may provide one of the six (6) items of photo identification listed above, or for the electors first time voting, may provide one of the following forms of identification: copy of a current utility bill, bank statement, government check, paycheck, or other government document that shows the name and address of elector.IF ELECTOR CANNOT PROVIDE ANY OF THE ABOVE LISTED ID’S THEY MAY VOTE A PROVISIONAL BALLOT IN ACCORDANCE WITH O.C.G.A. 21-2-220 and 21-2-417.

If the voter does not have a Georgia driver’s license, or other qualified ID, they can obtain either a FREE Georgia Identification Card from the Department of Driver Services or a FREE Georgia Voter Identification Card at their county registrar’s office. Just contact the Macon-Bibb County Board of Elections located at 2525 Pio Nono Ave., Ste 1200, Macon, GA 31206. Office hours are from 8:30 a.m. to 5:30 p.m. Monday thru Friday. For more information call 478-621-6622 or go to www.gaphotoid.com.

In order to get a FREE Georgia Voter Identification Card, a voter will need to provide the following:

A photo identity document, or a non-photo identity document (must include voter’s full legal name and date of birth); and

· Documentation showing the voter’s date of birth; and

· Evidence that voter is registered to vote in Georgia; and

· Documentation showing the voter’s name and address of principal residence.

The voter may use the same document to satisfy more than one of the above requirements. For additional information, please visit the Secretary of State’s web page at www.sos.state.ga.us.

Any location where fire fighters are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Fire Departments not having a permanent location are included, in which case their location has been depicted at the city/town hall or at the center of their service area if a city/town hall does not exist. This dataset includes those locations primarily engaged in forest or grasslands fire fighting, including fire lookout towers if the towers are in current use for fire protection purposes. This dataset includes both private and governmental entities. Fire fighting training academies are also included. This dataset is comprised completely of license free data. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 08/31/2005 and the newest record dates from 05/30/2008. Purpose Homeland Security Use Cases: Use cases describe how the data may be used and help to define and clarify requirements. 1. An assessment of whether or not the total fire fighting capability in a given area is adequate. 2. A list of resources to draw upon by surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can determine those entities that are able to respond the quickest. 3. A resource for Emergency Management planning purposes. 4. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster. 5. A resource for situational awareness planning and response for Federal Government events.

EMS Locations in New Hampshire The EMS stations dataset consists of any location where emergency medical services (EMS) personnel are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Ambulance services are included even if they only provide transportation services, but not if they are located at, and operated by, a hospital. If an independent ambulance service or EMS provider happens to be collocated with a hospital, it will be included in this dataset. The dataset includes both private and governmental entities. This dataset is comprised completely of license free data. The Fire Station dataset and the EMS dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 01/07/2005 and the newest record dates from 08/12/2008

Fire Stations in Oregon Any location where fire fighters are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Fire Departments not having a permanent location are included, in which case their location has been depicted at the city/town hall or at the center of their service area if a city/town hall does not exist. This dataset includes those locations primarily engaged in forest or grasslands fire fighting, including fire lookout towers if the towers are in current use for fire protection purposes. This dataset includes both private and governmental entities. Fire fighting training academies are also included. This dataset is comprised completely of license free data. The Fire Station dataset and the EMS dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 07/11/2006 and the newest record dates from 06/02/2008.