Detroit Street View (DSV) is an urban remote sensing program run by the Enterprise Geographic Information Systems (EGIS) Team within the Department of Innovation and Technology at the City of Detroit. The mission of Detroit Street View is ‘To continuously observe and document Detroit’s changing physical environment through remote sensing, resulting in freely available foundational data that empowers effective city operations, informed decision making, awareness, and innovation.’ LiDAR (as well as panoramic imagery) is collected using a vehicle-mounted mobile mapping system.
Due to variations in processing, index lines are not currently available for all existing LiDAR datasets, including all data collected before September 2020. Index lines represent the approximate path of the vehicle within the time extent of the given LiDAR file. The actual geographic extent of the LiDAR point cloud varies dependent on line-of-sight.
Compressed (LAZ format) point cloud files may be requested by emailing gis@detroitmi.gov with a description of the desired geographic area, any specific dates/file names, and an explanation of interest and/or intended use. Requests will be filled at the discretion and availability of the Enterprise GIS Team. Deliverable file size limitations may apply and requestors may be asked to provide their own online location or physical media for transfer.
LiDAR was collected using an uncalibrated Trimble MX2 mobile mapping system. The data is not quality controlled, and no accuracy assessment is provided or implied. Results are known to vary significantly. Users should exercise caution and conduct their own comprehensive suitability assessments before requesting and applying this data.
Sample Dataset: https://detroitmi.maps.arcgis.com/home/item.html?id=69853441d944442f9e79199b57f26fe3
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
These data provide an accurate high-resolution shoreline compiled from imagery of PORT OF MOBILE, AL . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Cleaned dataset for the Pharos application 2023-2024 data collection period (May 2023-March 2024). This dataset includes the full recurring network measurement (RNM), landmark (LM) datasets, as well as the county geographies used for the study catchment area. Also included in this dataset are a text document containing the necessary requirements, as well as python script to clean and visualize the collected data replicating the methods used in our published analysis.
See the KDOT Mobile LiDAR Project Data Portal Home Page or the 2023 Approaches Home Page for more details about the project and the delivered data.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This open data site is for exploring, accessing and downloading Kentucky-specific GIS data and discovering mapping apps. It provides simple access to information and tools that allow users to understand geospatial data. You can analyze and combine datasets using maps, as well as develop new web and mobile applications. Explore data by category, interact with web mapping applications, use Story Maps, or access our services directly. All data on the site is fed from a variety of authoritative sources.DO NOT DELETE OR MODIFY THIS ITEM. This item is managed by the ArcGIS Hub application. To make changes to this site, please visit https://hub.arcgis.com/admin/
This map presents transportation data, including highways, roads, railroads, and airports for the world.
The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.
You can add this layer on top of any imagery, such as the Esri World Imagery map service, to provide a useful reference overlay that also includes street labels at the largest scales. (At the largest scales, the line symbols representing the streets and roads are automatically hidden and only the labels showing the names of streets and roads are shown). Imagery With Labels basemap in the basemap dropdown in the ArcGIS web and mobile clients does not include this World Transportation map. If you use the Imagery With Labels basemap in your map and you want to have road and street names, simply add this World Transportation layer into your map. It is designed to be drawn underneath the labels in the Imagery With Labels basemap, and that is how it will be drawn if you manually add it into your web map.
These data were automated to provide an accurate high-resolution composite shoreline of GRAND BAY TO PENSACOLA MOBILE BAY, AL suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies. This metadata describes information for both the line and point shapefiles...
By Homeland Infrastructure Foundation [source]
The Mobile Home Parks Inventory dataset provides a comprehensive list of mobile home parks across the United States. This dataset is crucial for emergency preparedness and evacuation planning, as mobile home parks are inhabited by a vulnerable population that is particularly susceptible to natural disasters such as hurricanes, tornadoes, and flooding.
The dataset includes detailed information about each mobile home park, including its location coordinates (longitude and latitude), address details (street address, city, state, ZIP code), and additional address information if available. It also provides contact details such as telephone numbers and websites for further information about each park.
Furthermore, the dataset contains essential attributes related to the characteristics of mobile home parks. These attributes include the number of units (mobile homes) within each park, allowing authorities to assess capacity during emergency situations. Additionally, it categorizes the type of each park (e.g., recreational vehicle parks), its status (e.g., operational or closed), and its size classification.
To ensure data accuracy and reliability, various validation methods have been implemented. The validation process includes verifying the data sources from where this information was obtained along with dates when data was sourced or validated.
Moreover, this comprehensive inventory incorporates geographical references with FIPS codes for counties in which these mobile home parks are located. Furthermore,the NAICS code provides an additional industry classification system describing these facilities in greater detail.
Lastly,this Mobile Home Parks Inventory recognizes that reverse geocoding has been employed for gathering precise spatial coordinates.Because vulnerability differs across regions,state boundaries have also been included to facilitate analysis at a higher level.Alongside state boundaries,this dataset acknowledges country-level variations which could be valuable while comparing international mobile homes inventories .
By utilizing this extensive collection of accurate and up-to-date information on mobile home parks in the United States policymakers,government agencies,and emergency responders can effectively plan evacuation strategies,mobile resource allocation,and disaster response efforts for ensuring public safety during natural calamities.This valuable knowledge will ultimately enhance disaster mitigation and the overall resilience of these vulnerable communities
Understanding the Columns:
- X and Y: These columns represent the longitude and latitude coordinates of each mobile home park. They can be used for geographical analysis and mapping purposes.
- NAME: This column provides the name of each mobile home park. It is useful for identifying specific parks.
- ADDRESS: The street address where each mobile home park is located.
- ADDRESS2: Additional address information (if available) for each mobile home park.
- CITY: The city where each mobile home park is situated.
- STATE: The state where each mobile home park is located.
- ZIP and ZIP4: These columns contain the ZIP code information for each mobile home park, including additional ZIP code details if available.
- TELEPHONE: The contact telephone number for each mobile home park, which can be useful for making inquiries or gathering more information directly from them.
- TYPE: This column indicates the type of the mobile home park (e.g., permanent residential, seasonal).
- STATUS: The status of a particular mobile home park (e.g., open, closed).
- COUNTY and COUNTYFIPS:The county where each mobile h0me_1park is situated along with its associated FIPS code.
Analyzing Park Characteristics: UNITS & SIZE columns provide insights into various aspects: UNITS represents the number of individual dwelling units within a given Mobile Home Park SIZE describes its physical size.
Demographic Analysis: By referring to NAICS_CODE & NAICS_DESC columns ,you'll get an idea about the associated industries and business activities in the vicinity of each park.
Geographical Analysis: The LATITUDE and LONGITUDE coordinates allow you to map out mobile home parks on various GIS (Geographic Information System) platforms. You can analyze the distribution of mobile home parks across different states, cities, or counties.
Emergency Preparedness: ...
See the KDOT Mobile LiDAR Project Data Portal Home Page or the 2023 Lanes and Counts Home Page for more details about the project and the delivered data.
Description Cellphone tower extract is a copy of the data found at https://ised-isde.canada.ca/site/spectrum-management-system/en/spectrum-management-system-data. Data is organized into a point layer of tower locations grouped by provider. All the providers transmitters are located in a table related by a unique TowerID.Dataset Usage General data layer for use when needed, for example to identify shortfalls in cell service for field work.Data Source Modified version of Innovation, Science and Economic Development Canada datasetData Criticality 1Sensitive Data NoCurator Greg SpiridonovCurator Job Title GIS SpecialistCurator Email greg.spiridonov@grey.caCurator Department IT / GISCurator Responsibilities Maintain,Oversight_Control_AccessMaintenance and Update Frequency MonthlyUpdate History New ZIP downloaded Nov 14 2023Published Map Service(s) https://gis.grey.ca/portal/home/item.html?id=718f08a731924856827f85178bb649cbPublicly Available Publicly availableOpen Data Published to Open DataOffline (sync) Not sure at this timeOther Comments Dataset relates to table GC_CellTower_TransmittersPermissionsAssign permissions to map service if published.Group PermissionsCurator Department ViewGrey County Staff ViewPublic View
Point geometry with attributes displaying mobile home parks in East Baton Rouge Parish, Louisiana.Metadata
These data provide an accurate high-resolution shoreline compiled from imagery of WESTERN MOBILE BAY, AL . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribu...
Von der GNSS-basierten Datenerfassung bis zu Mobile Mapping
These data provide an accurate high-resolution shoreline compiled from imagery of Upper Mobile and Tensaw Rivers, AL . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Ob...
See the KDOT Mobile LiDAR Project Data Portal Home Page or the 2023 Billboard Faces Home Page for more details about the project and the delivered data.
DCGIS is an interactive map that provides increased functionality for advanced users as well as access to about 150 layers of GIS data, including parcel information, contour lines, aerial photography, county park amenities, park trails, bikeways, county road construction, roundabouts, floodplains and more. It allows you to create a map at any scale you wish.
The Interactive GIS Map is intended for use on any device - mobile or desktop - with high speed access.
These data provide an accurate high-resolution shoreline compiled from imagery of MOBILE BAY, BON SECOUR BAY TO FAIRHOPE, AL . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808
See the KDOT Mobile LiDAR Project Data Portal Home Page or the 2023 Guardrails Home Page for more details about the project and the delivered data.
See the KDOT Mobile LiDAR Project Data Portal Home Page or the 2023 Lanes and Counts Home Page for more details about the project and the delivered data.
See the KDOT Mobile LiDAR Project Data Portal Home Page or the 2023 Sidewalks Home Page for more details about the project and the delivered data.
Detroit Street View (DSV) is an urban remote sensing program run by the Enterprise Geographic Information Systems (EGIS) Team within the Department of Innovation and Technology at the City of Detroit. The mission of Detroit Street View is ‘To continuously observe and document Detroit’s changing physical environment through remote sensing, resulting in freely available foundational data that empowers effective city operations, informed decision making, awareness, and innovation.’ LiDAR (as well as panoramic imagery) is collected using a vehicle-mounted mobile mapping system.
Due to variations in processing, index lines are not currently available for all existing LiDAR datasets, including all data collected before September 2020. Index lines represent the approximate path of the vehicle within the time extent of the given LiDAR file. The actual geographic extent of the LiDAR point cloud varies dependent on line-of-sight.
Compressed (LAZ format) point cloud files may be requested by emailing gis@detroitmi.gov with a description of the desired geographic area, any specific dates/file names, and an explanation of interest and/or intended use. Requests will be filled at the discretion and availability of the Enterprise GIS Team. Deliverable file size limitations may apply and requestors may be asked to provide their own online location or physical media for transfer.
LiDAR was collected using an uncalibrated Trimble MX2 mobile mapping system. The data is not quality controlled, and no accuracy assessment is provided or implied. Results are known to vary significantly. Users should exercise caution and conduct their own comprehensive suitability assessments before requesting and applying this data.
Sample Dataset: https://detroitmi.maps.arcgis.com/home/item.html?id=69853441d944442f9e79199b57f26fe3