https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/
Geospatial Solutions Market size was valued at USD 282.75 Billion in 2024 and is projected to reach USD 650.14 Billion by 2032, growing at a CAGR of 12.10% during the forecast period 2026-2032.
Geospatial Solutions Market: Definition/ Overview
Geospatial solutions are applications and technologies that use spatial data to address geography, location, and Earth's surface problems. They use tools like GIS, remote sensing, GPS, satellite imagery analysis, and spatial modelling. These solutions enable informed decision-making, resource allocation optimization, asset management, environmental monitoring, infrastructure planning, and addressing challenges in sectors like urban planning, agriculture, transportation, disaster management, and natural resource management. They empower users to harness spatial information for better understanding and decision-making in various contexts.
Geospatial solutions are technologies and methodologies used to analyze and visualize spatial data, ranging from urban planning to agriculture. They use GIS, remote sensing, and GNSS to gather, process, and interpret data. These solutions help users make informed decisions, solve complex problems, optimize resource allocation, and enhance situational awareness. They are crucial in addressing challenges and unlocking opportunities in today's interconnected world, such as mapping land use patterns, monitoring ecosystem changes, and real-time asset tracking.
Some of the highest grade uranium (U) deposits in the United States are hosted by solution-collapse breccia pipes in the Grand Canyon region of northern Arizona. These structures are named for their vertical, pipe-like shape and the broken rock (breccia) that fills them. Hundreds, perhaps thousands, of these structures exist. Not all of the breccia pipes are mineralized; only a small percentage of the identified breccia pipes are known to contain an economic uranium deposit. An unresolved question is how many undiscovered U-bearing breccia pipes of this type exist in northern Arizona, in the region sometimes referred to as the “Arizona Strip”. Two principal questions remain regarding the breccia pipe U deposits of northern Arizona are: (1) What processes combined to form these unusual structures and their U deposits? and (2) How many undiscovered U deposits hosted by breccia pipes exist in the region? A piece of information required to answer these questions is to define the area where these types of deposits could exist based on available geologic information. In order to determine the regional processes that led to their formation, the regional distribution of U-bearing breccia pipes must be considered. These geospatial datasets were assembled in support of this goal.
The Wildland Fire Interagency Geospatial Services (WFIGS) Group provides authoritative geospatial data products under the interagency Wildland Fire Data Program. Hosted in the National Interagency Fire Center ArcGIS Online Organization (The NIFC Org), WFIGS provides both internal and public facing data, accessible in a variety of formats.This service includes perimeters for wildland fire incidents that meet the following criteria:
Categorized in the IRWIN (Integrated Reporting of Wildland Fire Information) integration service as a valid Wildfire (WF), Prescribed Fire (RX), or Incident Complex (CX) record with a Fire Discovery Date in the year 2021
Is not "quarantined" in IRWIN due to potential conflicts with other records
Attribution of the source polygon is set to a Feature Access of Public, a Feature Status of Approved, and an Is Visible setting of Yes
Perimeters are not available for every incident. For a complete set of features that meet the same IRWIN criteria, see the 2021 Wildland Fire Locations to Date service.
No "fall-off" rules are applied to this service.
Criteria were determined by an NWCG Geospatial Subcommittee task group.
Data are refreshed every 5 minutes. Changes in the perimeter source may take up to 15 minutes to display.
Perimeters are pulled from multiple sources with rules in place to ensure the most current or most authoritative shape is used.Warning: Please refrain from repeatedly querying the service using a relative date range. This includes using the “(not) in the last” operators in a Web Map filter and any reference to CURRENT_TIMESTAMP. This type of query puts undue load on the service and may render it temporarily unavailable.
Attributes and their definitions can be found below. More detail about the NWCG Wildland Fire Event Polygon standard can be found here.
Attributes:
Incident Name (Polygon)
The Incident Name from the source polygon.
Feature Category
Type of wildland fire perimeter set for the source polygon.
Map Method
Controlled vocabulary to define how the source polygon was derived. Map Method may help define data quality.
GIS Acres
User-calculated acreage on the source polygon.
Polygon Create Date
System field. Time stamp for the source polygon feature creation.
Polygon Modified Date
System field. Time stamp for the most recent edit to the source polygon feature.
Polygon Collection Date Time
Date time for the source polygon feature collection.
Acres Auto Calculated
Automated calculation of the source polygon acreage.
Polygon Source
Data source of the perimeter geometry.{Year} NIFS: Annual National Incident Feature ServiceFFP: Final Fire Perimeter Service (Certified Perimeters)
ABCD Misc
A FireCode used by USDA FS to track and compile cost information for emergency initial attack fire suppression expenditures. for A, B, C & D size class fires on FS lands.
ADS Permission State
Indicates the permission hierarchy that is currently being applied when a system utilizes the UpdateIncident operation.
IRWIN Archived On
A date set by IRWIN that indicates when an incident's data has met the rules defined for the record to become part of the historical fire records rather than an operational incident record. The value will be set the current date/time if any of the following criteria are met: 1. ContainmentDataTime or ControlDateTime or FireOutDateTime or ModifiedOnDateTime > 12 months from the current DateTime2. FinalFireReportDate is not null and ADSPermissionState is 'certified'.
Calculated Acres
A measure of acres calculated (i.e., infrared) from a geospatial perimeter of a fire. More specifically, the number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands. The minimum size must be 0.1.
Containment Date Time
The date and time a wildfire was declared contained.
Control Date Time
The date and time a wildfire was declared under control.
Created By System
ArcGIS Server Username of system that created the IRWIN Incident record.
IRWIN Created On Date Time
Date/time that the IRWIN Incident record was created.
IRWIN Daily Acres
A measure of acres reported for a fire. More specifically, the number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands. The minimum size must be 0.1.
Discovery Acres
An estimate of acres burning upon the discovery of the fire. More specifically when the fire is first reported by the first person that calls in the fire. The estimate should include number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands.
Dispatch Center ID
A unique identifier for a dispatch center responsible for supporting the incident.
Final Fire Report Approved By Title
The title of the person that approved the final fire report for the incident.
Final Fire Report Approved By Unit
NWCG Unit ID associated with the individual who approved the final report for the incident.
Final Fire Report Approved Date
The date that the final fire report was approved for the incident.
Fire Behavior General
A general category describing the manner in which the fire is currently reacting to the influences of fuel, weather, and topography.
Fire Behavior General 1
A more specific category further describing the general fire behavior (manner in which the fire is currently reacting to the influences of fuel, weather, and topography).
Fire Behavior General 2
A more specific category further describing the general fire behavior (manner in which the fire is currently reacting to the influences of fuel, weather, and topography).
Fire Behavior General 3
A more specific category further describing the general fire behavior (manner in which the fire is currently reacting to the influences of fuel, weather, and topography).
Fire Cause
Broad classification of the reason the fire occurred identified as human, natural or unknown.
Fire Cause General
Agency or circumstance which started a fire or set the stage for its occurrence; source of a fire's ignition. For statistical purposes, fire causes are further broken into specific causes.
Fire Cause Specific
A further categorization of each General Fire Cause to indicate more specifically the agency or circumstance which started a fire or set the stage for its occurrence; source of a fire's ignition.
Fire Code
A code used within the interagency wildland fire community to track and compile cost information for emergency fire suppression expenditures for the incident.
Fire Department ID
The U.S. Fire Administration (USFA) has created a national database of Fire Departments. Most Fire Departments do not have an NWCG Unit ID and so it is the intent of the IRWIN team to create a new field that includes this data element to assist the National Association of State Foresters (NASF) with data collection.
Fire Discovery Date Time
The date and time a fire was reported as discovered or confirmed to exist. May also be the start date for reporting purposes.
Fire Mgmt Complexity
The highest management level utilized to manage a wildland fire event.
Fire Out Date Time
The date and time when a fire is declared out.
Fire Strategy Confine Percent
Indicates the percentage of the incident area where the fire suppression strategy of "Confine" is being implemented.
Fire Strategy Full Supp Percent
Indicates the percentage of the incident area where the fire suppression strategy of "Full Suppression" is being implemented.
Fire Strategy Monitor Percent
Indicates the percentage of the incident area where the fire suppression strategy of "Monitor" is being implemented.
Fire Strategy Point Zone Percent
Indicates the percentage of the incident area where the fire suppression strategy of "Point Zone Protection" is being implemented.
FS Job Code
A code use to indicate the Forest Service job accounting code for the incident. This is specific to the Forest Service. Usually displayed as 2 char prefix on FireCode.
FS Override Code
A code used to indicate the Forest Service override code for the incident. This is specific to the Forest Service. Usually displayed as a 4 char suffix on FireCode. For example, if the FS is assisting DOI, an override of 1502 will be used.
GACC
A code that identifies one of the wildland fire geographic area coordination center at the point of origin for the incident.A geographic area coordination center is a facility that is used for the coordination of agency or jurisdictional resources in support of one or more incidents within a geographic coordination area.
ICS 209 Report Date Time
The date and time of the latest approved ICS-209 report.
ICS 209 Report For Time Period From
The date and time of the beginning of the time period for the current ICS-209 submission.
ICS 209 Report For Time Period To
The date and time of the end of the time period for the current ICS-209 submission.
ICS 209 Report Status
The version of the ICS-209 report (initial, update, or final). There should never be more than one initial report, but there can be numerous updates, and even multiple finals (as determined by business rules).
Incident Management Organization
The
The Wildland Fire Interagency Geospatial Services (WFIGS) Group provides authoritative geospatial data products under the interagency Wildland Fire Data Program. Hosted in the NIFC Open Data Site, WFIGS provides both internal and public facing data, accessible in a variety of formats.This service includes perimeters for wildland fire incidents that meet the following criteria:Categorized in the IRWIN (Integrated Reporting of Wildland Fire Information) integration service as a valid Wildfire (WF), Prescribed Fire (RX), or Incident Complex (CX) record.Is not "quarantined" in IRWIN due to potential conflicts with other recordsAttribution of the source polygon is set to a Feature Access of Public, a Feature Status of Approved, and an Is Visible setting of YesPerimeters are not available for every incident. For a complete set of features that meet the same IRWIN criteria, see the 2021 Wildland Fire Locations to Date service.No "fall-off" rules are applied to this service. Criteria were determined by an NWCG Geospatial Subcommittee task group. Data are refreshed every 5 minutes. Changes in the perimeter source may take up to 15 minutes to display.Perimeters are pulled from multiple sources with rules in place to ensure the most current or most authoritative shape is used.Warning: Please refrain from repeatedly querying the service using a relative date range. This includes using the “(not) in the last” operators in a Web Map filter and any reference to CURRENT_TIMESTAMP. This type of query puts undue load on the service and may render it temporarily unavailable.Attributes and their definitions can be found below. More detail about the NWCG Wildland Fire Event Polygon standard can be found here.Attributes:Incident Name (Polygon)The Incident Name from the source polygon.Feature CategoryType of wildland fire perimeter set for the source polygon.Map MethodControlled vocabulary to define how the source polygon was derived. Map Method may help define data quality.GIS AcresUser-calculated acreage on the source polygon.Polygon Create DateSystem field. Time stamp for the source polygon feature creation.Polygon Modified DateSystem field. Time stamp for the most recent edit to the source polygon feature.Polygon Collection Date TimeDate time for the source polygon feature collection.Acres Auto CalculatedAutomated calculation of the source polygon acreage.Polygon SourceData source of the perimeter geometry.{Year} NIFS: Annual National Incident Feature ServiceFFP: Final Fire Perimeter Service (Certified Perimeters)ABCD MiscA FireCode used by USDA FS to track and compile cost information for emergency initial attack fire suppression expenditures. for A, B, C & D size class fires on FS lands.ADS Permission StateIndicates the permission hierarchy that is currently being applied when a system utilizes the UpdateIncident operation.IRWIN Archived OnA date set by IRWIN that indicates when an incident's data has met the rules defined for the record to become part of the historical fire records rather than an operational incident record. The value will be set the current date/time if any of the following criteria are met: 1. ContainmentDataTime or ControlDateTime or FireOutDateTime or ModifiedOnDateTime > 12 months from the current DateTime2. FinalFireReportDate is not null and ADSPermissionState is 'certified'.Calculated AcresA measure of acres calculated (i.e., infrared) from a geospatial perimeter of a fire. More specifically, the number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands. The minimum size must be 0.1.Containment Date TimeThe date and time a wildfire was declared contained. Control Date TimeThe date and time a wildfire was declared under control.Created By SystemArcGIS Server Username of system that created the IRWIN Incident record.IRWIN Created On Date TimeDate/time that the IRWIN Incident record was created.IRWIN Daily AcresA measure of acres reported for a fire. More specifically, the number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands. The minimum size must be 0.1.Discovery AcresAn estimate of acres burning upon the discovery of the fire. More specifically when the fire is first reported by the first person that calls in the fire. The estimate should include number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands.Dispatch Center IDA unique identifier for a dispatch center responsible for supporting the incident.Final Fire Report Approved By TitleThe title of the person that approved the final fire report for the incident.Final Fire Report Approved By UnitNWCG Unit ID associated with the individual who approved the final report for the incident.Final Fire Report Approved DateThe date that the final fire report was approved for the incident.Fire Behavior GeneralA general category describing the manner in which the fire is currently reacting to the influences of fuel, weather, and topography. Fire Behavior General 1A more specific category further describing the general fire behavior (manner in which the fire is currently reacting to the influences of fuel, weather, and topography). Fire Behavior General 2A more specific category further describing the general fire behavior (manner in which the fire is currently reacting to the influences of fuel, weather, and topography). Fire Behavior General 3A more specific category further describing the general fire behavior (manner in which the fire is currently reacting to the influences of fuel, weather, and topography). Fire CauseBroad classification of the reason the fire occurred identified as human, natural or unknown. Fire Cause GeneralAgency or circumstance which started a fire or set the stage for its occurrence; source of a fire's ignition. For statistical purposes, fire causes are further broken into specific causes. Fire Cause SpecificA further categorization of each General Fire Cause to indicate more specifically the agency or circumstance which started a fire or set the stage for its occurrence; source of a fire's ignition. Fire CodeA code used within the interagency wildland fire community to track and compile cost information for emergency fire suppression expenditures for the incident. Fire Department IDThe U.S. Fire Administration (USFA) has created a national database of Fire Departments. Most Fire Departments do not have an NWCG Unit ID and so it is the intent of the IRWIN team to create a new field that includes this data element to assist the National Association of State Foresters (NASF) with data collection.Fire Discovery Date TimeThe date and time a fire was reported as discovered or confirmed to exist. May also be the start date for reporting purposes.Fire Mgmt ComplexityThe highest management level utilized to manage a wildland fire event. Fire Out Date TimeThe date and time when a fire is declared out. Fire Strategy Confine PercentIndicates the percentage of the incident area where the fire suppression strategy of "Confine" is being implemented.Fire Strategy Full Supp PercentIndicates the percentage of the incident area where the fire suppression strategy of "Full Suppression" is being implemented.Fire Strategy Monitor PercentIndicates the percentage of the incident area where the fire suppression strategy of "Monitor" is being implemented.Fire Strategy Point Zone PercentIndicates the percentage of the incident area where the fire suppression strategy of "Point Zone Protection" is being implemented.FS Job CodeA code use to indicate the Forest Service job accounting code for the incident. This is specific to the Forest Service. Usually displayed as 2 char prefix on FireCode.FS Override CodeA code used to indicate the Forest Service override code for the incident. This is specific to the Forest Service. Usually displayed as a 4 char suffix on FireCode. For example, if the FS is assisting DOI, an override of 1502 will be used.GACCA code that identifies one of the wildland fire geographic area coordination center at the point of origin for the incident.A geographic area coordination center is a facility that is used for the coordination of agency or jurisdictional resources in support of one or more incidents within a geographic coordination area.ICS 209 Report Date TimeThe date and time of the latest approved ICS-209 report.ICS 209 Report For Time Period FromThe date and time of the beginning of the time period for the current ICS-209 submission.ICS 209 Report For Time Period ToThe date and time of the end of the time period for the current ICS-209 submission. ICS 209 Report StatusThe version of the ICS-209 report (initial, update, or final). There should never be more than one initial report, but there can be numerous updates, and even multiple finals (as determined by business rules).Incident Management OrganizationThe incident management organization for the incident, which may be a Type 1, 2, or 3 Incident Management Team (IMT), a Unified Command, a Unified Command with an IMT, National Incident Management Organization (NIMO), etc. This field is null if no team is assigned.Incident NameThe name assigned to an incident.Incident Short DescriptionGeneral descriptive location of the incident such as the number of miles from an identifiable town. Incident Type CategoryThe Event Category is a sub-group of the Event Kind code and description. The Event Category further breaks down the Event Kind into more specific event categories.Incident Type KindA general, high-level code and description of the types of incidents and planned events to which the interagency wildland fire community responds.Initial LatitudeThe latitude location of the initial reported point of origin specified in decimal degrees.Initial LongitudeThe longitude location of the initial reported point of origin specified in decimal degrees.Initial Response AcresAn
Historical FiresLast updated on 06/17/2022OverviewThe national fire history perimeter data layer of conglomerated Agency Authoratative perimeters was developed in support of the WFDSS application and wildfire decision support for the 2021 fire season. The layer encompasses the final fire perimeter datasets of the USDA Forest Service, US Department of Interior Bureau of Land Management, Bureau of Indian Affairs, Fish and Wildlife Service, and National Park Service, the Alaska Interagency Fire Center, CalFire, and WFIGS History. Perimeters are included thru the 2021 fire season. Requirements for fire perimeter inclusion, such as minimum acreage requirements, are set by the contributing agencies. WFIGS, NPS and CALFIRE data now include Prescribed Burns. Data InputSeveral data sources were used in the development of this layer:Alaska fire history USDA FS Regional Fire History Data BLM Fire Planning and Fuels National Park Service - Includes Prescribed Burns Fish and Wildlife ServiceBureau of Indian AffairsCalFire FRAS - Includes Prescribed BurnsWFIGS - BLM & BIA and other S&LData LimitationsFire perimeter data are often collected at the local level, and fire management agencies have differing guidelines for submitting fire perimeter data. Often data are collected by agencies only once annually. If you do not see your fire perimeters in this layer, they were not present in the sources used to create the layer at the time the data were submitted. A companion service for perimeters entered into the WFDSS application is also available, if a perimeter is found in the WFDSS service that is missing in this Agency Authoratative service or a perimeter is missing in both services, please contact the appropriate agency Fire GIS Contact listed in the table below.AttributesThis dataset implements the NWCG Wildland Fire Perimeters (polygon) data standard.https://www.nwcg.gov/sites/default/files/stds/WildlandFirePerimeters_definition.pdfIRWINID - Primary key for linking to the IRWIN Incident dataset. The origin of this GUID is the wildland fire locations point data layer. (This unique identifier may NOT replace the GeometryID core attribute)INCIDENT - The name assigned to an incident; assigned by responsible land management unit. (IRWIN required). Officially recorded name.FIRE_YEAR (Alias) - Calendar year in which the fire started. Example: 2013. Value is of type integer (FIRE_YEAR_INT).AGENCY - Agency assigned for this fire - should be based on jurisdiction at origin.SOURCE - System/agency source of record from which the perimeter came.DATE_CUR - The last edit, update, or other valid date of this GIS Record. Example: mm/dd/yyyy.MAP_METHOD - Controlled vocabulary to define how the geospatial feature was derived. Map method may help define data quality.GPS-Driven; GPS-Flight; GPS-Walked; GPS-Walked/Driven; GPS-Unknown Travel Method; Hand Sketch; Digitized-Image; Digitized-Topo; Digitized-Other; Image Interpretation; Infrared Image; Modeled; Mixed Methods; Remote Sensing Derived; Survey/GCDB/Cadastral; Vector; OtherGIS_ACRES - GIS calculated acres within the fire perimeter. Not adjusted for unburned areas within the fire perimeter. Total should include 1 decimal place. (ArcGIS: Precision=10; Scale=1). Example: 23.9UNQE_FIRE_ - Unique fire identifier is the Year-Unit Identifier-Local Incident Identifier (yyyy-SSXXX-xxxxxx). SS = State Code or International Code, XXX or XXXX = A code assigned to an organizational unit, xxxxx = Alphanumeric with hyphens or periods. The unit identifier portion corresponds to the POINT OF ORIGIN RESPONSIBLE AGENCY UNIT IDENTIFIER (POOResonsibleUnit) from the responsible unit’s corresponding fire report. Example: 2013-CORMP-000001LOCAL_NUM - Local incident identifier (dispatch number). A number or code that uniquely identifies an incident for a particular local fire management organization within a particular calendar year. Field is string to allow for leading zeros when the local incident identifier is less than 6 characters. (IRWIN required). Example: 123456.UNIT_ID - NWCG Unit Identifier of landowner/jurisdictional agency unit at the point of origin of a fire. (NFIRS ID should be used only when no NWCG Unit Identifier exists). Example: CORMPCOMMENTS - Additional information describing the feature. Free Text.FEATURE_CA - Type of wildland fire polygon: Wildfire (represents final fire perimeter or last daily fire perimeter available) or Prescribed Fire or UnknownGEO_ID - Primary key for linking geospatial objects with other database systems. Required for every feature. This field may be renamed for each standard to fit the feature. Globally Unique Identifier (GUID).Cross-Walk from sources (GeoID) and other processing notesAK: GEOID = OBJECT ID of provided file geodatabase (4580 Records thru 2021), other federal sources for AK data removed. CA: GEOID = OBJECT ID of downloaded file geodatabase (12776 Records, federal fires removed, includes RX)FWS: GEOID = OBJECTID of service download combined history 2005-2021 (2052 Records). Handful of WFIGS (11) fires added that were not in FWS record.BIA: GEOID = "FireID" 2017/2018 data (416 records) provided or WFDSS PID (415 records). An additional 917 fires from WFIGS were added, GEOID=GLOBALID in source.NPS: GEOID = EVENT ID (IRWINID or FRM_ID from FOD), 29,943 records includes RX.BLM: GEOID = GUID from BLM FPER and GLOBALID from WFIGS. Date Current = best available modify_date, create_date, fire_cntrl_dt or fire_dscvr_dt to reduce the number of 9999 entries in FireYear. Source FPER (25,389 features), WFIGS (5357 features)USFS: GEOID=GLOBALID in source, 46,574 features. Also fixed Date Current to best available date from perimeterdatetime, revdate, discoverydatetime, dbsourcedate to reduce number of 1899 entries in FireYear.Relevant Websites and ReferencesAlaska Fire Service: https://afs.ak.blm.gov/CALFIRE: https://frap.fire.ca.gov/mapping/gis-dataBIA - data prior to 2017 from WFDSS, 2017-2018 Agency Provided, 2019 and after WFIGSBLM: https://gis.blm.gov/arcgis/rest/services/fire/BLM_Natl_FirePerimeter/MapServerNPS: New data set provided from NPS Fire & Aviation GIS. cross checked against WFIGS for any missing perimeters in 2021.https://nifc.maps.arcgis.com/home/item.html?id=098ebc8e561143389ca3d42be3707caaFWS -https://services.arcgis.com/QVENGdaPbd4LUkLV/arcgis/rest/services/USFWS_Wildfire_History_gdb/FeatureServerUSFS - https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceAndPerimeter_01/MapServerAgency Fire GIS ContactsRD&A Data ManagerVACANTSusan McClendonWFM RD&A GIS Specialist208-258-4244send emailJill KuenziUSFS-NIFC208.387.5283send email Joseph KafkaBIA-NIFC208.387.5572send emailCameron TongierUSFWS-NIFC208.387.5712send emailSkip EdelNPS-NIFC303.969.2947send emailJulie OsterkampBLM-NIFC208.258.0083send email Jennifer L. Jenkins Alaska Fire Service 907.356.5587 send email
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
NSW Coastline data is linear feature class defining the line of contact between a body of water and the land. In particular, the line delineating the interface between land, internal waters and the “Territorial Sea” as defined by the Seas and Submerged Lands Act - No. 161 of 1973.\r \r The coastline defining Mean High Water Mark (MHWM) does not include MHWM within estuaries.\r Features within coastline feature class include: mean high water mark and mean low water mark.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This is an experimental dataset for the bicycle trips recorded using and geo-game called "Cyclist Geo-C". It contains the geometry of the trips recorded by 60 participants from three European Cities: Münster, Germany; Castelló, Spain; Valletta, Malta. This dataset was collected and analysed for the PhD Thesis "Mobile Services for Green Living" part of the European Joint Doctorate in Geoinformatics and the Geo-C Project.
The dataset is composed of three subsets.
In addition to the experimental dataset recorded by participants, our analysis used a secondary dataset to define a comparable framework for the three cities. The secondary dataset consisted of the existing bicycle paths in the cities of Münster and Castelló as well as the planned bicycle paths around Valletta. For the city of Münster, the source of the bicycle paths was the OpenStreetMap (we downloaded the line elements with the tags “bicycle=yes” and "cycleway=yes”). For the city of Castelló, we obtained the bicycle paths from the city transport authority, including the city of Valletta, we created a digital version of the national bicycle network plan.
We estimated the number of trips "bikepaths_trips.geojson" and the number of segments "bikepaths_segments.geojson" at each bike path. Also, we provide the areas where participants faced frictions during the experiment which corresponded to low cycling speeds "frictions.geojson".
Finally, we provide a visual reference of the dataset in "frictions_cities.pdf".
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Medical Emergency Response StructuresThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Geological Survey, displays hospitals, medical centers, ambulance services, fire stations and EMS stations in the U.S. Per the USGS, "Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations."Greendale Fire DepartmentData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Medical & Emergency Response) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 135 (USGS National Structures Dataset - USGS National Map Downloadable Data Collection)OGC API Features Link: (Medical Emergency Response Structures - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: The National MapFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Theme CommunityThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets
The dataspatial extension for CKAN enhances the platform's ability to handle and search geospatial data stored in the datastore. It equips CKAN with capabilities to perform geospatial searches within datasets, determine the spatial extent of searches, and integrate with PostGIS and Solr for spatial data management, it is important to note the extension is not currently maintained and may require syntax updates to work with current CKAN versions. While unmaintained, it provides valuable geospatial functionalities. Key Features: Geospatial Searching: Enables users to search datastore data based on geospatial criteria defined by a Well-Known Text (WKT) string, supporting POLYGON or MULTIPOLYGON geometries. Spatial Extent Calculation: Allows determining the geospatial extent (bounding box) of search results, providing a summary of the geographic area covered by the data. PostGIS Integration: Supports storing and querying geospatial data using PostGIS, a spatial database extension for PostgreSQL. Requires creating specific PostGIS columns on resources. Solr Integration: If ckanext-datasolr is also installed, enables indexing and searching geospatial data using Solr, a search platform. Requires configuring Solr to index spatial data. Solr support is enabled via the ckanext-datasolr extension. creategeomcolumns Action: Creates the necessary PostGIS columns on a specified resource, populating them and creating an index if desired. updategeomcolumns Action: Updates the geospatial column for a resource, enabling continual synchronization between the column and data rows. Technical Integration: The dataspatial extension integrates with CKAN by adding plugins that enable geospatial searching and extent calculations. It requires configuration settings in the CKAN .ini file to define the backend (PostGIS or Solr), specify the names of spatial fields, and configure the PostGIS and Solr settings, including required extensions. Commands like create-columns, create-index, and populate-columns manage PostGIS columns. The datastore_search action is extended to support geospatial filters. Benefits & Impact: By implementing the dataspatial extension, organizations can make their datastore data spatially aware, leading to richer discovery and utilization of data based on geographic location. It supports use cases such as environmental monitoring, urban planning, and location-based services by allowing users to find, analyze, and visualize datasets tied to specific geographic areas. Geospatial awareness increases the ability to discover and utilize data effectively.
This medium-scale (nominally 1:24,000) dataset represents the boundaries of cities, townships, and unorganized territories (CTUs) in Minnesota. The Minnesota Geospatial Information Office created the initial CTU dataset by updating a municipal boundary file maintained by the Minnesota Department of Transportation (MnDOT). Update information was gathered primarily from boundary adjustment records maintained by the Office of Administrative Hearings, Municipal Boundary Adjustment Unit. MnDOT has maintained the file since 2014.
Note: Cities and Townships represented in this dataset are political (civil) townships as recognized by the State of MN, not congressional or public land survey townships. Unorganized territory subdivisions are those defined by the U.S. Bureau of the Census, which often differ from those defined by a county.
Check other metadata records in this package for more information on CTUInformation.
Link to ESRI Feature Service:
City, Township, and Unorganized Territory in Minnesota: City, Township, and Unorganized Territory
Version InformationThe data is updated annually with fire perimeters from the previous calendar year.Firep23_1 was released in May 2024. Two hundred eighty four fires from the 2023 fire season were added to the database (21 from BLM, 102 from CAL FIRE, 72 from Contract Counties, 19 from LRA, 9 from NPS, 57 from USFS and 4 from USFW). The 2020 Cottonwood fire, 2021 Lone Rock and Union fires, as well as the 2022 Lost Lake fire were added. USFW submitted a higher accuracy perimeter to replace the 2022 River perimeter. A duplicate 2020 Erbes fire was removed. Additionally, 48 perimeters were digitized from an historical map included in a publication from Weeks, d. et al. The Utilization of El Dorado County Land. May 1934, Bulletin 572. University of California, Berkeley. There were 2,132 perimeters that received updated attribution, the bulk of which had IRWIN IDs added. The following fires were identified as meeting our collection criteria, but are not included in this version and will hopefully be added in the next update: Big Hill #2 (2023-CAHIA-001020). YEAR_ field changed to a short integer type. San Diego CAL FIRE UNIT_ID changed to SDU (the former code MVU is maintained in the UNIT_ID domains). COMPLEX_INCNUM renamed to COMPLEX_ID and is in process of transitioning from local incident number to the complex IRWIN ID. Perimeters managed in a complex in 2023 are added with the complex IRWIN ID. Those previously added will transition to complex IRWIN IDs in a future update.If you would like a full briefing on these adjustments, please contact the data steward, Kim Wallin (kimberly.wallin@fire.ca.gov), CAL FIRE FRAP._CAL FIRE (including contract counties), USDA Forest Service Region 5, USDI Bureau of Land Management & National Park Service, and other agencies jointly maintain a fire perimeter GIS layer for public and private lands throughout the state. The data covers fires back to 1878. Current criteria for data collection are as follows:CAL FIRE (including contract counties) submit perimeters ≥10 acres in timber, ≥50 acres in brush, or ≥300 acres in grass, and/or ≥3 damaged/ destroyed residential or commercial structures, and/or caused ≥1 fatality.All cooperating agencies submit perimeters ≥10 acres._Discrepancies between wildfire perimeter data and CAL FIRE Redbook Large Damaging FiresLarge Damaging fires in California were first defined by the CAL FIRE Redbook, and has changed over time, and differs from the definition initially used to define wildfires required to be submitted for the initial compilation of this digital fire perimeter data. In contrast, the definition of fires whose perimeter should be collected has changed once in the approximately 30 years the data has been in existence. Below are descriptions of changes in data collection criteria used when compiling these two datasets. To facilitate comparison, this metadata includes a summary, by year, of fires in the Redbook, that do not appear in this fire perimeter dataset. It is followed by an enumeration of each “Redbook” fire missing from the spatial data. Wildfire Perimeter criteria:~1991: 10 acres timber, 30 acres brush, 300 acres grass, damages or destroys three residence or one commercial structure or does $300,000 worth of damage 2002: 10 acres timber, 50 acres brush, 300 acres grass, damages or destroys three or more structures, or does $300,000 worth of damage~2010: 10 acres timber, 30 acres brush, 300 acres grass, damages or destroys three or more structures (doesn’t include out building, sheds, chicken coops, etc.)Large and Damaging Redbook Fire data criteria:1979: Fires of a minimum of 300 acres that burn at least: 30 acres timber or 300 acres brush, or 1500 acres woodland or grass1981: 1979 criteria plus fires that took ,3000 hours of California Department of Forestry and Fire Protection personnel time to suppress1992: 1981 criteria plus 1500 acres agricultural products, or destroys three residence or one commercial structure or does $300,000 damage1993: 1992 criteria but “three or more structures destroyed” replaces “destroys three residence or one commercial structure” and the 3,000 hours of California Department of Forestry personnel time to suppress is removed2006: 300 acres or larger and burned at least: 30 acres of timber, or 300 acres of brush, or 1,500 acres of woodland, or 1,500 acres of grass, or 1,500 acres of agricultural products, or 3 or more structures destroyed, or $300,000 or more dollar damage loss.2008: 300 acres and largerYear# of Missing Large and Damaging Redbook Fires197922198013198115198261983319842019855219861219875619882319898199091991219921619931719942219959199615199791998101999720004200152002162003520042200512006112007320084320093201022011020124201322014720151020162201711201862019220203202102022020230Total488Enumeration of fires in the Redbook that are missing from Fire Perimeter data. Three letter unit code follows fire name.1979-Sylvandale (HUU), Kiefer (AEU), Taylor(TUU), Parker#2(TCU), PGE#10, Crocker(SLU), Silver Spur (SLU), Parkhill (SLU), Tar Springs #2 (SLU), Langdon (SCU), Truelson (RRU), Bautista (RRU), Crocker (SLU), Spanish Ranch (SLU), Parkhill (SLU), Oak Springs(BDU), Ruddell (BDF), Santa Ana (BDU), Asst. #61 (MVU), Bernardo (MVU), Otay #20 1980– Lightning series (SKU), Lavida (RRU), Mission Creek (RRU), Horse (RRU), Providence (RRU), Almond (BDU), Dam (BDU), Jones (BDU), Sycamore (BDU), Lightning (MVU), Assist 73, 85, 138 (MVU)1981– Basalt (LNU), Lightning #25(LMU), Likely (MNF), USFS#5 (SNF), Round Valley (TUU), St. Elmo (KRN), Buchanan (TCU), Murietta (RRU), Goetz (RRU), Morongo #29 (RRU), Rancho (RRU), Euclid (BDU), Oat Mt. (LAC & VNC), Outside Origin #1 (MVU), Moreno (MVU)1982- Duzen (SRF), Rave (LMU), Sheep’s trail (KRN), Jury (KRN), Village (RRU), Yuma (BDF)1983- Lightning #4 (FKU), Kern Co. #13, #18 (KRN)1984-Bidwell (BTU), BLM D 284,337, PNF #115, Mill Creek (TGU), China hat (MMU), fey ranch, Kern Co #10, 25,26,27, Woodrow (KRN), Salt springs, Quartz (TCU), Bonanza (BEU), Pasquel (SBC), Orco asst. (ORC), Canel (local), Rattlesnake (BDF)1985- Hidden Valley, Magic (LNU), Bald Mt. (LNU), Iron Peak (MEU), Murrer (LMU), Rock Creek (BTU), USFS #29, 33, Bluenose, Amador, 8 mile (AEU), Backbone, Panoche, Los Gatos series, Panoche (FKU), Stan #7, Falls #2 (MMU), USFS #5 (TUU), Grizzley, Gann (TCU), Bumb, Piney Creek, HUNTER LIGGETT ASST#2, Pine, Lowes, Seco, Gorda-rat, Cherry (BEU), Las pilitas, Hwy 58 #2 (SLO), Lexington, Finley (SCU), Onions, Owens (BDU), Cabazon, Gavalin, Orco, Skinner, Shell, Pala (RRU), South Mt., Wheeler, Black Mt., Ferndale, (VNC), Archibald, Parsons, Pioneer (BDU), Decker, Gleason(LAC), Gopher, Roblar, Assist #38 (MVU)1986– Knopki (SRF), USFS #10 (NEU), Galvin (RRU), Powerline (RRU), Scout, Inscription (BDU), Intake (BDF), Assist #42 (MVU), Lightning series (FKU), Yosemite #1 (YNP), USFS Asst. (BEU), Dutch Kern #30 (KRN)1987- Peach (RRU), Ave 32 (TUU), Conover (RRU), Eagle #1 (LNU), State 767 aka Bull (RRU), Denny (TUU), Dog Bar (NEU), Crank (LMU), White Deer (FKU), Briceburg (LMU), Post (RRU), Antelope (RRU), Cougar-I (SKU), Pilitas (SLU) Freaner (SHU), Fouts Complex (LNU), Slides (TGU), French (BTU), Clark (PNF), Fay/Top (SQF), Under, Flume, Bear Wallow, Gulch, Bear-1, Trinity, Jessie, friendly, Cold, Tule, Strause, China/Chance, Bear, Backbone, Doe, (SHF) Travis Complex, Blake, Longwood (SRF), River-II, Jarrell, Stanislaus Complex 14k (STF), Big, Palmer, Indian (TNF) Branham (BLM), Paul, Snag (NPS), Sycamore, Trail, Stallion Spring, Middle (KRN), SLU-864 1988- Hwy 175 (LNU), Rumsey (LNU), Shell Creek (MEU), PG&E #19 (LNU), Fields (BTU), BLM 4516, 417 (LMU), Campbell (LNF), Burney (SHF), USFS #41 (SHF), Trinity (USFS #32), State #837 (RRU), State (RRU), State (350 acres), RRU), State #1807, Orange Co. Asst (RRU), State #1825 (RRU), State #2025, Spoor (BDU), State (MVU), Tonzi (AEU), Kern co #7,9 (KRN), Stent (TCU), 1989– Rock (Plumas), Feather (LMU), Olivas (BDU), State 1116 (RRU), Concorida (RRU), Prado (RRU), Black Mt. (MVU), Vail (CNF)1990– Shipman (HUU), Lightning 379 (LMU), Mud, Dye (TGU), State 914 (RRU), Shultz (Yorba) (BDU), Bingo Rincon #3 (MVU), Dehesa #2 (MVU), SLU 1626 (SLU)1991- Church (HUU), Kutras (SHF)1992– Lincoln, Fawn (NEU), Clover, fountain (SHU), state, state 891, state, state (RRU), Aberdeen (BDU), Wildcat, Rincon (MVU), Cleveland (AEU), Dry Creek (MMU), Arroyo Seco, Slick Rock (BEU), STF #135 (TCU)1993– Hoisington (HUU), PG&E #27 (with an undetermined cause, lol), Hall (TGU), state, assist, local (RRU), Stoddard, Opal Mt., Mill Creek (BDU), Otay #18, Assist/ Old coach (MVU), Eagle (CNF), Chevron USA, Sycamore (FKU), Guerrero, Duck1994– Schindel Escape (SHU), blank (PNF), lightning #58 (LMU), Bridge (NEU), Barkley (BTU), Lightning #66 (LMU), Local (RRU), Assist #22 & #79 (SLU), Branch (SLO), Piute (BDU), Assist/ Opal#2 (BDU), Local, State, State (RRU), Gilman fire 7/24 (RRU), Highway #74 (RRU), San Felipe, Assist #42, Scissors #2 (MVU), Assist/ Opal#2 (BDU), Complex (BDF), Spanish (SBC)1995-State 1983 acres, Lost Lake, State # 1030, State (1335 acres), State (5000 acres), Jenny, City (BDU), Marron #4, Asist #51 (SLO/VNC)1996- Modoc NF 707 (Ambrose), Borrego (MVU), Assist #16 (SLU), Deep Creek (BDU), Weber (BDU), State (Wesley) 500 acres (RRU), Weaver (MMU), Wasioja (SBC/LPF), Gale (FKU), FKU 15832 (FKU), State (Wesley) 500 acres, Cabazon (RRU), State Assist (aka Bee) (RRU), Borrego, Otay #269 (MVU), Slaughter house (MVU), Oak Flat (TUU)1997- Lightning #70 (LMU), Jackrabbit (RRU), Fernandez (TUU), Assist 84 (Military AFV) (SLU), Metz #4 (BEU), Copperhead (BEU), Millstream, Correia (MMU), Fernandez (TUU)1998- Worden, Swift, PG&E 39 (MMU), Chariot, Featherstone, Wildcat, Emery, Deluz (MVU), Cajalco Santiago (RRU)1999- Musty #2,3 (BTU), Border # 95 (MVU), Andrews,
Interagency Wildland Fire Perimeter History (IFPH)OverviewThis national fire history perimeter data layer of conglomerated agency perimeters was developed in support of the WFDSS application and wildfire decision support. The layer encompasses the fire perimeter datasets of the USDA Forest Service, US Department of Interior Bureau of Land Management, Bureau of Indian Affairs, Fish and Wildlife Service, and National Park Service, the Alaska Interagency Fire Center, CalFire, and WFIGS History. Perimeters are included thru the 2023 fire season. Requirements for fire perimeter inclusion, such as minimum acreage requirements, are set by the contributing agencies. WFIGS, NPS and CALFIRE data now include Prescribed Burns. Data InputSeveral data sources were used in the development of this layer, links are provided where possible below. In addition, many agencies are now using WFIGS as their authoritative source, beginning in mid-2020.Alaska fire history USDA FS Regional Fire History Data BLM Fire Planning and Fuels National Park Service - Includes Prescribed Burns Fish and Wildlife ServiceBureau of Indian AffairsCalFire FRAS - Includes Prescribed BurnsWFIGS - BLM & BIA and other S&LData LimitationsFire perimeter data are often collected at the local level, and fire management agencies have differing guidelines for submitting fire perimeter data. Often data are collected by agencies only once annually. If you do not see your fire perimeters in this layer, they were not present in the sources used to create the layer at the time the data were submitted. A companion service for perimeters entered into the WFDSS application is also available, if a perimeter is found in the WFDSS service that is missing in this Agency Authoritative service or a perimeter is missing in both services, please contact the appropriate agency Fire GIS Contact listed in the table below.AttributesThis dataset implements the NWCG Wildland Fire Perimeters (polygon) data standard.https://www.nwcg.gov/sites/default/files/stds/WildlandFirePerimeters_definition.pdfIRWINID - Primary key for linking to the IRWIN Incident dataset. The origin of this GUID is the wildland fire locations point data layer. (This unique identifier may NOT replace the GeometryID core attribute)INCIDENT - The name assigned to an incident; assigned by responsible land management unit. (IRWIN required). Officially recorded name.FIRE_YEAR (Alias) - Calendar year in which the fire started. Example: 2013. Value is of type integer (FIRE_YEAR_INT).AGENCY - Agency assigned for this fire - should be based on jurisdiction at origin.SOURCE - System/agency source of record from which the perimeter came.DATE_CUR - The last edit, update, or other valid date of this GIS Record. Example: mm/dd/yyyy.MAP_METHOD - Controlled vocabulary to define how the geospatial feature was derived. Map method may help define data quality.GPS-Driven; GPS-Flight; GPS-Walked; GPS-Walked/Driven; GPS-Unknown Travel Method; Hand Sketch; Digitized-Image; Digitized-Topo; Digitized-Other; Image Interpretation; Infrared Image; Modeled; Mixed Methods; Remote Sensing Derived; Survey/GCDB/Cadastral; Vector; OtherGIS_ACRES - GIS calculated acres within the fire perimeter. Not adjusted for unburned areas within the fire perimeter. Total should include 1 decimal place. (ArcGIS: Precision=10; Scale=1). Example: 23.9UNQE_FIRE_ - Unique fire identifier is the Year-Unit Identifier-Local Incident Identifier (yyyy-SSXXX-xxxxxx). SS = State Code or International Code, XXX or XXXX = A code assigned to an organizational unit, xxxxx = Alphanumeric with hyphens or periods. The unit identifier portion corresponds to the POINT OF ORIGIN RESPONSIBLE AGENCY UNIT IDENTIFIER (POOResonsibleUnit) from the responsible unit’s corresponding fire report. Example: 2013-CORMP-000001LOCAL_NUM - Local incident identifier (dispatch number). A number or code that uniquely identifies an incident for a particular local fire management organization within a particular calendar year. Field is string to allow for leading zeros when the local incident identifier is less than 6 characters. (IRWIN required). Example: 123456.UNIT_ID - NWCG Unit Identifier of landowner/jurisdictional agency unit at the point of origin of a fire. (NFIRS ID should be used only when no NWCG Unit Identifier exists). Example: CORMPCOMMENTS - Additional information describing the feature. Free Text.FEATURE_CA - Type of wildland fire polygon: Wildfire (represents final fire perimeter or last daily fire perimeter available) or Prescribed Fire or UnknownGEO_ID - Primary key for linking geospatial objects with other database systems. Required for every feature. This field may be renamed for each standard to fit the feature. Globally Unique Identifier (GUID).Cross-Walk from sources (GeoID) and other processing notesAK: GEOID = OBJECT ID of provided file geodatabase (4580 Records thru 2021), other federal sources for AK data removed. CA: GEOID = OBJECT ID of downloaded file geodatabase (12776 Records, federal fires removed, includes RX)FWS: GEOID = OBJECTID of service download combined history 2005-2021 (2052 Records). Handful of WFIGS (11) fires added that were not in FWS record.BIA: GEOID = "FireID" 2017/2018 data (416 records) provided or WFDSS PID (415 records). An additional 917 fires from WFIGS were added, GEOID=GLOBALID in source.NPS: GEOID = EVENT ID (IRWINID or FRM_ID from FOD), 29,943 records includes RX.BLM: GEOID = GUID from BLM FPER and GLOBALID from WFIGS. Date Current = best available modify_date, create_date, fire_cntrl_dt or fire_dscvr_dt to reduce the number of 9999 entries in FireYear. Source FPER (25,389 features), WFIGS (5357 features)USFS: GEOID=GLOBALID in source, 46,574 features. Also fixed Date Current to best available date from perimeterdatetime, revdate, discoverydatetime, dbsourcedate to reduce number of 1899 entries in FireYear.Relevant Websites and ReferencesAlaska Fire Service: https://afs.ak.blm.gov/CALFIRE: https://frap.fire.ca.gov/mapping/gis-dataBIA - data prior to 2017 from WFDSS, 2017-2018 Agency Provided, 2019 and after WFIGSBLM: https://gis.blm.gov/arcgis/rest/services/fire/BLM_Natl_FirePerimeter/MapServerNPS: New data set provided from NPS Fire & Aviation GIS. cross checked against WFIGS for any missing perimetersFWS -https://services.arcgis.com/QVENGdaPbd4LUkLV/arcgis/rest/services/USFWS_Wildfire_History_gdb/FeatureServerUSFS - https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_FireOccurrenceAndPerimeter_01/MapServer
The purpose of the American Indian and Alaska Native Land Area Representation (AIAN-LAR) Geographic Information System (GIS) dataset is to depict the external extent of federal Indian reservations and the external extent of associated land held in “trust” by the United States, “restricted fee” or “mixed ownership” status for federally recognized tribes and individual Indians. This dataset includes other land area types such as Public Domain Allotments, Dependent Indian Communities and Homesteads. This GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes. No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is to be used solely for illustrative, reference and statistical purposes and may be used for government to government Tribal consultation. Reservation boundary data is limited in authority to those areas where there has been settled Congressional definition or final judicial interpretation of the boundary. Absent settled Congressional definition or final judicial interpretation of a reservation boundary, the BIA recommends consultation with the appropriate Tribe and then the BIA to obtain interpretations of the reservation boundary. The land areas and their representations are compilations defined by the official land title records of the Bureau of Indian Affairs (BIA) which include treaties, statutes, Acts of Congress, agreements, executive orders, proclamations, deeds and other land title documents. The trust, restricted, and mixed ownership land area shown here, are suitable only for general spatial reference and do not represent the federal government’s position on the jurisdictional status of Indian country. Ownership and jurisdictional status is subject to change and must be verified with plat books, patents, and deeds in the appropriate federal and state offices. Included in this dataset are the exterior extent of off reservation trust, restricted fee tracts and mixed tracts of land including Public Domain allotments, Dependent Indian Communities, Homesteads and government administered lands and those set aside for schools and dormitories. There are also land areas where there is more than one tribe having an interest in or authority over a tract of land but this information is not specified in the AIAN-LAR dataset. The dataset includes both surface and subsurface tracts of land (tribal and individually held) “off reservation” tracts and not simply off reservation “allotments” as land has in many cases been subsequently acquired in trust. These data are public information and may be used by various organizations, agencies, units of government (i.e., Federal, state, county, and city), and other entities according to the restrictions on appropriate use. It is strongly recommended that these data be acquired directly from the BIA and not indirectly through some other source, which may have altered or integrated the data for another purpose for which they may not have been intended. Integrating land areas into another dataset and attempting to resolve boundary differences between other entities may produce inaccurate results. It is also strongly recommended that careful attention be paid to the content of the metadata file associated with these data. Users are cautioned that digital enlargement of these data to scales greater than those at which they were originally mapped can cause misinterpretation. The BIA AIAN-LAR dataset’s spatial accuracy and attribute information are continuously being updated, improved and is used as the single authoritative land area boundary data for the BIA mission. These data are available through the Bureau of Indian Affairs, Office of Trust Services, Division of Land Titles and Records, Branch of Geospatial Support.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Means, standard deviations, t-tests, and significance levels of perceived climate threat.
Publication Date: November 2017. This file only contains parcel data for NYS State-owned tax parcels. Parcel geometry was incorporated as received from County Real Property Departments. No attempt was made to edge-match parcels along adjacent counties. County attribute values were populated using 2016 Assessment Roll tabular data the NYS GIS Program Office (GPO) obtained from the NYS Department of Tax and Finance’s Office of Real Property Tax Services (ORPTS). This tabular data was joined to the county provided parcel geometry using the SWIS & SBL or SWIS & PRINT KEY unique identifier for each parcel. New York City attribute data comes from NYC MapPluto (https://www1.nyc.gov/site/planning/data-maps/open-data/dwn-pluto-mappluto.page). Parcel polygons range from 2014 to 2017.
The State-owned tax parcel polygons in this file are the result of a best effort selection based on the Primary Owner and Additional Owner fields in the NYS Statewide Tax Parcels file, GPO data, State agency data, and online research. These same data and information are also the basis for a best effort assignment of a NYS agency name (listed in the NYS Name field) to most tax parcel polygons where the Owner Type field value is State. The NYS Name Source field consists of a code that describes how the State-owned designation and agency name were determined, if this was verified, and the means of verification, if applicable. Additional metadata, including field descriptions, can be found at the NYS GIS Clearinghouse: http://gis.ny.gov/gisdata/inventories/details.cfm?DSID=1300.
© Contributing counties, NYS Office of Information Technology Services GIS Program Office (GPO) and NYS Department of Taxation and Finance’s Office of Real Property Tax Services (ORPTS).
This is series-level metadata for the USGS Protected Areas Database of the United States (PAD-US) data released by the United States Geological Survey (USGS). PAD-US is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas. Starting with version 1.4 PAD-US was identified as an A-16 National Geospatial Data Asset in the Cadastre Theme ( https://ngda-cadastre-geoplatform.hub.arcgis.com/ ). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all open space public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, permanent and long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of U.S. public land and other protected areas, compiling "best available" data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas using thirty-six attributes and five separate feature classes representing the U.S. protected areas network: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. An additional Combined feature class includes the full PAD-US inventory to support data management, queries, web mapping services, and analyses. The Feature Class (FeatClass) field in the Combined layer allows users to extract data types as needed. A Federal Data Reference file geodatabase lookup table facilitates the extraction of authoritative federal data provided or recommended by managing agencies from the Combined PAD-US inventory. For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas/. For more information about data aggregation please review the PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . A version history of PAD-US updates is summarized below (See https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-history for more information): - Current Version - January 2022 (Version 3.0) https://doi.org/10.5066/P9Q9LQ4B - Revised - September 2020 (Version 2.1) https://doi.org/10.5066/P92QM3NT - Revised - September 2018 (Version 2.0) https://doi.org/10.5066/P955KPLE - Revised - May 2016 (Version 1.4) https://doi.org/10.5066/F7G73BSZ - Revised - November 2012 (Version 1.3) https://doi.org/10.5066/F79Z92XD - Revised - April 2011 (Version 1.2 - available from the PAD-US: Team pad-us@usgs.gov) - Revised - May 2010 (Version 1.1 - available from the PAD-US: Team pad-us@usgs.gov) - First posted - April 2009 (Version 1.0 - available from the PAD-US: Team pad-us@usgs.gov) Comparing protected area trends between PAD-US versions is not recommended without consultation with USGS as many changes reflect improvements to agency and organization GIS systems, or conservation and recreation measure classification, rather than actual changes in protected area acquisition on the ground.
Cropland Index The Cropland Index evaluates lands used to produce crops based on the following input datasets: Revised Storie Index, California Important Farmland data, Electrical Conductivity (EC), and Sodium Adsorption Ratio (SAR). Together, these input layers were used in a suitability model to generate this raster. High values are associated with better CroplandsCalifornia Important Farmland data – statistical data used for analyzing impacts on California’s agricultural resources from the Farmland Mapping and Monitoring Program. Agricultural land is rated according to soil quality and irrigation status. The maps are updated every two years (on even numbered years) with the use of a computer mapping system, aerial imagery, public review, and field reconnaissance. Cropland Index Mask - This is a constructed data set used to define the model domain. Its footprint is defined by combining the extent of the California Important Farmland data (2018) classifications listed above and the area defined by California Statewide Crop Mapping for the state of California.Prime Farmland – farmland with the best combination of physical and chemical features able to sustain long term agricultural production. This land has the soil quality, growing season, and moisture supply needed to produce sustained high yields. Land must have been used for irrigated agricultural production at some time during the four years prior to the mapping date.Farmland of Statewide Importance – farmland similar to Prime Farmland but with minor shortcomings, such as greater slopes or less ability to store soil moisture. Land must have been used for irrigated agricultural production at some time during the four years prior to the mapping date. Unique Farmland – farmland of lesser quality soils used for the production of the state’s leading agricultural crops. This land is usually irrigated but may include Non irrigated orchards or vineyards as found in some climatic zones in California. Land must have been cropped at some time during the four years prior to the mapping date. Gridded Soil Survey Geographic Database (gSSURGO) – a database containing information about soil as collected by the National Cooperative Soil Survey over the course of a century. The information can be displayed in tables or as maps and is available for most areas in the United States and the Territories, Commonwealths, and Island Nations served by the USDA-NRCS. The information was gathered by walking over the land and observing the soil. Many soil samples were analyzed in laboratories. California Revised Storie Index - is a soil rating based on soil properties that govern a soil’s potential for cultivated agriculture in California. The Revised Storie Index assesses the productivity of a soil from the following four characteristics: Factor A, degree of soil profile development; factor B, texture of the surface layer; factor C, slope; and factor X, manageable features, including drainage, microrelief, fertility, acidity, erosion, and salt content. A score ranging from 0 to 100 percent is determined for each factor, and the scores are then multiplied together to derive an index rating.Electrical Conductivity - is the electrolytic conductivity of an extract from saturated soil paste, expressed as Deci siemens per meter at 25 degrees C. Electrical conductivity is a measure of the concentration of water-soluble salts in soils. It is used to indicate saline soils. High concentrations of neutral salts, such as sodium chloride and sodium sulfate, may interfere with the adsorption of water by plants because the osmotic pressure in the soil solution is nearly as high as or higher than that in the plant cells. Sodium Adsorption Ratio - is a measure of the amount of sodium (Na) relative to calcium (Ca) and magnesium (Mg) in the water extract from saturated soil paste. It is the ratio of the Na concentration divided by the square root of one-half of the Ca + Mg concentration. Soils that have SAR values of 13 or more may be characterized by an increased dispersion of organic matter and clay particles, reduced saturated hydraulic conductivity (Ksat) and aeration, and a general degradation of soil structure.
Basemap natural color RGB image.Produced from ESA’s Sentinel-2 A/B imagery, 10 meter resolution Satellite Derive Bathymetry (SDB) is a highly accurate, extremely cost effective bathymetry product that can be produced in clear shallow water regions. The surface in this web scene was calibrated and validated using nautical charts as a survey planning surface to demonstrate shoal points and "no-go" areas.TCarta is a leading global provider of innovative hydrospatial products and Earth observation analysis services. TCarta GIS professionals, hydrographers, and developers provide solutions for onshore and offshore geospatial applications from engineering to environmental monitoring and beyond.TCarta’s primary focus is on providing affordability and accessibility of data and analytics utilizing cutting edge technology and approaches to best serve our clients where traditional methods fail with proven integrity of services and professional practices in a changing and dynamic world.USES: Satellite Derived Bathymetry (SDB) is a lower cost alternative to marine surveys and much higher resolution than ETOPO and GEBCO datasets. Coastal Engineering: Floating Solar Facilities: Suitability Analysis - Location siting using modern and accurate bathymetryWave modeling for construction planningMooring design & Cable routing to shore Offshore Wind Farms:Planning and AppraisalEnvironmental Impact assessmentsMooring design & Cable routingSite characterization Fiber Optic Cable Route Planning:Protecting marine life sanctuariesDecrease distance Aquaculture:Site selectionMonitoringFlow prediction Dredging:Measuring materialMonitoring Water Quality Monitoring:Chlorophyll IndexSediment flowNatural Disasters:Inundation modellingEnvironmental Compliance monitoring.TOOLS: ArcGIS PRO add-in and toolboxDELIVERABLES: GIS ready raster and vector formats, typically as GeoTiff, ASCII data with xyzu(where u represents Uncertainty of Z value) files in map projection coordinates (WGS84) with metadata. Other formats are available upon request like geodatabases, KML/KMZ, HDF, NetCDF
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Core Based Statistical AreasThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau, depicts Core Based Statistical Areas (CBSA). Per the USCB, "Metropolitan and Micropolitan Statistical Areas are together termed CBSAs and are defined by the Office of Management and Budget (OMB) and consist of the county or counties or equivalent entities associated with at least one urban core of at least 10,000 population, plus adjacent counties having a high degree of social and economic integration with the core as measured through commuting ties with the counties containing the core. Categories of CBSAs are: Metropolitan Statistical Areas, based on urban areas of 50,000 or more population; and Micropolitan Statistical Areas, based on urban areas of at least 10,000 population but less than 50,000 population."Kill Devil Hills, NC (Micro Area)Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal sources (Metropolitan Statistical Areas & Micropolitan Statistical Areas) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 84 (Series Information for Core-Based Statistical Areas National TIGER/Line Shapefiles, Current)OGC API Features Link: (Core Based Statistical Areas - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: Delineation FilesFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets
This GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes.No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is to be used solely for illustrative, reference and statistical purposes and may be used for government to government Tribal consultation. Reservation boundary data is limited in authority to those areas where there has been settled Congressional definition or final judicial interpretation of the boundary. Absent settled Congressional definition or final judicial interpretation of a reservation boundary, the BIA recommends consultation with the appropriate Tribe and then the BIA to obtain interpretations of the reservation boundary.The land areas and their representations are compilations defined by the official land title records of the Bureau of Indian Affairs (BIA) which include treaties, statutes, Acts of Congress, agreements, executive orders, proclamations, deeds and other land title documents. The trust, restricted, and mixed ownership land area shown here, are suitable only for general spatial reference and do not represent the federal government’s position on the jurisdictional status of Indian country. Ownership and jurisdictional status is subject to change and must be verified with plat books, patents, and deeds in the appropriate federal and state offices.Included in this dataset are the exterior extent of off reservation trust, restricted fee tracts and mixed tracts of land including Public Domain allotments, Dependent Indian Communities, Homesteads and government administered lands and those set aside for schools and dormitories. There are also land areas where there is more than one tribe having an interest in or authority over a tract of land but this information is not specified in the AIAN-LAR dataset. The dataset includes both surface and subsurface tracts of land (tribal and individually held) “off reservation” tracts and not simply off reservation “allotments” as land has in many cases been subsequently acquired in trust.These data are public information and may be used by various organizations, agencies, units of government (i.e., Federal, state, county, and city), and other entities according to the restrictions on appropriate use. It is strongly recommended that these data be acquired directly from the BIA and not indirectly through some other source, which may have altered or integrated the data for another purpose for which they may not have been intended. Integrating land areas into another dataset and attempting to resolve boundary differences between other entities may produce inaccurate results. It is also strongly recommended that careful attention be paid to the content of the metadata file associated with these data. Users are cautioned that digital enlargement of these data to scales greater than those at which they were originally mapped can cause misinterpretation.The BIA AIAN-LAR dataset’s spatial accuracy and attribute information are continuously being updated, improved and is used as the single authoritative land area boundary data for the BIA mission. These data are available through the Bureau of Indian Affairs, Office of Trust Services, Division of Land Titles and Records, Branch of Geospatial Support.These data have been made publicly available from an authoritative source other than this Atlas and data should be obtained directly from that source for any re-use. See the original metadata from the authoritative source for more information about these data and use limitations. The authoritative source of these data can be found at the following location: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2021.html#list-tab-790442341The BIA Indian Lands dataset’s spatial accuracy and attribute information are continuously being updated, improved and is used as the single authoritative land area boundary data for the BIA mission. This data are available through the Bureau of Indian Affairs, Office of Trust Services, Division of Land Titles and Records, Branch of Geospatial Support. Please feel free to contact us at 1-877-293-9494 geospatial@bia.gov
https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/
Geospatial Solutions Market size was valued at USD 282.75 Billion in 2024 and is projected to reach USD 650.14 Billion by 2032, growing at a CAGR of 12.10% during the forecast period 2026-2032.
Geospatial Solutions Market: Definition/ Overview
Geospatial solutions are applications and technologies that use spatial data to address geography, location, and Earth's surface problems. They use tools like GIS, remote sensing, GPS, satellite imagery analysis, and spatial modelling. These solutions enable informed decision-making, resource allocation optimization, asset management, environmental monitoring, infrastructure planning, and addressing challenges in sectors like urban planning, agriculture, transportation, disaster management, and natural resource management. They empower users to harness spatial information for better understanding and decision-making in various contexts.
Geospatial solutions are technologies and methodologies used to analyze and visualize spatial data, ranging from urban planning to agriculture. They use GIS, remote sensing, and GNSS to gather, process, and interpret data. These solutions help users make informed decisions, solve complex problems, optimize resource allocation, and enhance situational awareness. They are crucial in addressing challenges and unlocking opportunities in today's interconnected world, such as mapping land use patterns, monitoring ecosystem changes, and real-time asset tracking.