The Ministry for Primary Industries (MPI) generates and acquires geospatial data. To maintain trust and confidence in the accuracy of this data, and the ability to reuse MPI has developed standards for both internal staff and external contractors. At the conclusion of any project or contract involving MPI, all data created should be provided to MPI. All data supplied to MPI must be well structured and managed to a high standard. The data must be in a format compatible with ESRI software, with all datasets named logically and clearly. If a deviation is required from the data standards please contact the contract manager.

The purpose of the Virginia Administrative Boundary Geospatial Data Standard is to implement, as a Commonwealth ITRM Standard, the data file naming conventions, geometry, map projection system, common set of attributes, dataset type and specifications, and level of precision for the Virginia Administrative Boundaries Dataset, which will be the data source of record at the state level for administrative boundary spatial features within the Commonwealth of Virginia.

SDI | Data | Data Governance | News |NGA releases new data strategy to navigate digital, GEOINT revolution SPRINGFIELD, Virginia — The National Geospatial-Intelligence Agency published the agency’s data strategy Oct. 6, outlining its plans to transform and improve the way data is created, managed and shared in order to maintain dominance in the delivery of geospatial intelligence. “It is essential that we take all actions necessary to sustain our advantage in GEOINT — and that includes managing our data as a key strategic asset,’’ stated NGA Director Vice Adm. Robert Sharp in the data strategy. “With the holistic enterprise approach mapped out within this new data strategy, NGA sets forth a path for leading the way and staying ahead of our competitors.’’ The NGA Data Strategy 2021, a 28-page public document, includes both strategic goals and courses of action for the agency as it continues to chart a secure and innovative path forward while facing increasing amounts of data, risk and competition. Aligned to the agency’s Moonshot effort to “deliver trusted GEOINT with the speed, accuracy and precision required,’’ the strategy calls for the accelerated, shared and trusted use of data to help NGA better deliver on its mandates and show the way. The plan, created as a companion document to the NGA Technology Strategy published in 2020, already has played an integral role in the agency’s recent adoption of a new data governance structure to provide a coordinated framework for data policies and stewardship. The data strategy, combined with the established collaborative data governance program, guides the agency’s push to close the gap between current and future capabilities by accelerating developments in four significant focus areas: making data easily accessible, improving data reusability, improving cross-domain efficiencies and enabling next-generation GEOINT. The strategy describes four key goals being pursued by NGA to meet its mission and business needs. To achieve its desired results, the agency seeks to: — Manage data as a strategic asset: Deploy a federated enterprise data governance framework that ensures data is proactively, strategically and consistently managed while enabling agility, flexibility and innovation. Relationship to SDI'sThis reference resource provides a reference resource for SDI related activities in the intelligence community.The National Geospatial Intelligence Agency is a Federal participating organization in the Federal Geographic Data Committee. A Senior NGA Representative is a member of the FGDC Executive Committee A Senior NGA Representative is appointed by the Secretary of Interior to the National Geospatial Advisory Committee established in the Geospatial Data Act of 2018 "The head of each covered agency and the Director of the National Geospatial-Intelligence Agency shall each designate a representative of their respective agency to serve as a member of the Committee."The Geospatial Data Act of 2018 U.S.C 2804 Geospatial Standards, requires FGDC to "shall include universal data standards that shall be acceptable for the purposes of declassified intelligence community data"Additional ResourcesFederal Geographic Data CommitteeNational Geospatial Advisory CommitteeNational Geospatial Intelligence Agency National Geospatial Intelligence Agency Products and ServicesFGDC Standards

Metadata & Projection Standards, Data Development Methods, State Engineer's Office E-Permit Instructions, Permit conversion Tool (Version 2, 2019)

Data Model Schema, Feature Attributes, Relationship Classes, Field Domains (Version 2, 2019)

From April 29 through May 2, 2022, researchers from the U.S. Geological Survey (USGS) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterizing stratigraphy near Seven Mile Island, New Jersey (NJ). The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. The goal of this study included the investigation of nearshore geologic controls on surface morphology and assessing barrier island resilience after Hurricane Sandy (U.S. landfall was October 29, 2012). This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation files, geographic information system (GIS) data, and formal Federal Geographic Data Committee (FGDC) Content Standard for Digital Geospatial Metadata (CSDGM). Processed subbottom profile images are also provided. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y revision 0 format (Barry and others, 1975). In addition to this data release, the SEG-Y files can be downloaded from the USGS Coastal and Marine Geoscience Data System (CMGDS) at, https://cmgds.marine.usgs.gov.

Overview of the Water Development GIS Standards.

This project contains:One map containing the City of Vancouver City Limits layer for use in populating sample templates600x400 pixel formatted templates for generating thumbnails for Applications, Web Maps/Maps/Packages, Layers, and items to be deprecatedTemplates for print layouts at 8.5x11", landscape and portrait sizesStyle file containing correct fonts and colors in alignment with City of Vancouver brandingExample text should be replaced as necessary, and it is recommended you save any applicable changes as a copy of this package for your use.

The USDA Long-Term Agroecosystem Research was established to develop national strategies for sustainable intensification of agricultural production. As part of the Agricultural Research Service, the LTAR Network incorporates numerous geographies consisting of experimental areas and locations where data are being gathered. Starting in early 2019, two working groups of the LTAR Network (Remote Sensing and GIS, and Data Management) set a major goal to jointly develop a geodatabase of LTAR Standard GIS Data Layers. The purpose of the geodatabase was to enhance the Network's ability to utilize coordinated, harmonized datasets and reduce redundancy and potential errors associated with multiple copies of similar datasets. Project organizers met at least twice with each of the 18 LTAR sites from September 2019 through December 2020, compiling and editing a set of detailed geospatial data layers comprising a geodatabase, describing essential data collection areas within the LTAR Network. The LTAR Standard GIS Data Layers geodatabase consists of geospatial data that represent locations and areas associated with the LTAR Network as of late 2020, including LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This geodatabase was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. The creation of the geodatabase began with initial requests to LTAR site leads and data managers for geospatial data, followed by meetings with each LTAR site to review the initial draft. Edits were documented, and the final draft was again reviewed and certified by LTAR site leads or their delegates. Revisions to this geodatabase will occur biennially, with the next revision scheduled to be published in 2023. Resources in this dataset:Resource Title: LTAR Standard GIS Data Layers, 2020 version, File Geodatabase. File Name: LTAR_Standard_GIS_Layers_v2020.zipResource Description: This file geodatabase consists of authoritative GIS data layers of the Long-Term Agroecosystem Research Network. Data layers include: LTAR site locations, LTAR site points of contact and street addresses, LTAR experimental boundaries, LTAR site "legacy region" boundaries, LTAR eddy flux tower locations, and LTAR phenocam locations.Resource Software Recommended: ArcGIS,url: esri.com Resource Title: LTAR Standard GIS Data Layers, 2020 version, GeoJSON files. File Name: LTAR_Standard_GIS_Layers_v2020_GeoJSON_ADC.zipResource Description: The contents of the LTAR Standard GIS Data Layers includes geospatial data that represent locations and areas associated with the LTAR Network as of late 2020. This collection of geojson files includes spatial data describing LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This dataset was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. Resource Software Recommended: QGIS,url: https://qgis.org/en/site/

From June 2 through 9, 2021, researchers from the U.S. Geological Survey (USGS) conducted an inshore and offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Pensacola Beach, Florida (FL). The Coastal Resource Evaluation for Management Applications (CREMA) project objective includes the investigation of nearshore geologic controls on surface morphology. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation files, geographic information system (GIS) data, and formal Federal Geographic Data Committee (FGDC) Content Standard for Digital Geospatial Metadata (CSDGM). Processed subbottom profile images are also provided. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y revision 0 format (Barry and others, 1975). In addition to this data release, the SEG-Y files can be downloaded from the USGS Coastal and Marine Geoscience Data System (CMGDS) at, https://cmgds.marine.usgs.gov. Coastal multibeam bathymetry data were also collected for this project offshore of the Santa Rosa Island coast (during USGS Field Activity Number 2019-326-FA) and are provided in another data release (Farmer and others, 2020).

U.S. National GridThis feature layer, utilizing data from the Federal Geographic Data Committee (FGDC), displays the U.S. National Grid (USNG). The FGDC provides standards for a National Grid. Per the FGDC, "The objective of this standard is to create a more favorable environment for developing location-based services within the United States and to increase the interoperability of location services appliances with printed map products by establishing a nationally consistent grid reference system as the preferred grid for National Spatial Data Infrastructure (NSDI) applications. This standard defines the US National Grid. The U.S. National Grid is based on universally defined coordinate and grid systems and can, therefore, be easily extended for use world-wide as a universal grid reference system."Note: popups can be viewed for the USNG 1000m and USNG 100m layers.Note: the USNG 100m layer is only displayed for certain cities. To view those places, please select a row in the attribute table and then center (zoom) on selection.U.S. National Grid - Grid Zone DesignationsTop: 100,000-meter and 10,000-meter Square IdentificationsBottom: 1,000-meter and 100-meter Square IdentificationsData downloaded: October, 2011Data modifications: The Percent Complete field was removed from all layers. The following fields were added to the original data for layers:USNG 1000m - UTM ZoneUSNG 100m - Place; RegionFor more information:Standard for a U.S. National GridUnited States National GridHow to read a United States National Grid (USNG) spatial addressFor feedback, please contact: ArcGIScomNationalMaps@esri.comFederal Geographic Data Committee (FGDC)Per the FGDC, "The Federal Geographic Data Committee (FGDC) is an organized structure of Federal geospatial professionals and constituents that provide executive, managerial, and advisory direction and oversight for geospatial decisions and initiatives across the Federal government. In accordance with Office of Management and Budget (OMB) Circular A-16, the FGDC is chaired by the Secretary of the Interior with the Deputy Director for Management, OMB as Vice-Chair."

CAP Geofences: Precision & Accuracy for Business Success

Unmatched Geofencing Accuracy

CAP geofences are meticulously hand-drawn to provide superior accuracy, surpassing automated, machine-generated polygons that only cover building footprints. Our approach considers the entire shopping center ecosystem, including parking lots, out -parcels, and surrounding structures, ensuring a more comprehensive and precise representation.

Commitment to Accuracy

Unlike conventional geofencing solutions, CAP continuously refines its geofences through ground-truthing, eliminating inaccuracies such as drift and leakage. While this process takes longer than automated methods, it results in the highest level of reliability, minimizing errors and maximizing actionable insights.

Enhancing Business Operations

CAP geofences empower businesses by offering deep insights into foot traffic patterns. Instead of just counting visitors, businesses can track movement across different areas, such as parking lots, walkways, and specific stores. This level of granularity helps optimize operations, refine marketing strategies, and better understand customer behavior.

Precision in Mobile Advertising

For advertisers, CAP’s geofences enable accurate location-based targeting, ensuring messages reach the right audience without the risk of geofence drift or leakage. This precision leads to higher engagement rates, improved ROI, and more effective campaigns.

Setting a New Standard

By prioritizing accuracy over speed, CAP geofences redefine industry standards, providing reliable data that businesses can trust. Whether for analyzing foot traffic, optimizing ad strategies, or understanding consumer behavior, CAP delivers results that drive success.

The Vegetation Technical Working Group (VTWG) of the Alaska Geospatial Council developed the Standards for Mapping Vegetation in Alaska Version 1.1 (August 2022) to promote consistency among independently produced local, regional, and statewide vegetation maps for Alaska.

As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey at the nearshore ledge offshore of Boca Chica Key, Florida (FL) November 8-13, 2022. The objective of the project was to collect bathymetric maps and conduct a geologic assessment of the nearshore ledge off Boca Chica Key in support of efforts to construct an artificial coral reef offshore of Naval Air Station Key West. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation files, geographic information system (GIS) data, and formal Federal Geographic Data Committee (FGDC) Content Standard for Digital Geospatial Metadata (CSDGM). Processed subbottom profile images are also provided. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y revision 0 format (Barry and others, 1975). In addition to this data release, the SEG-Y files can be downloaded from the USGS Coastal and Marine Geoscience Data System (CMGDS) at, https://cmgds.marine.usgs.gov.

Location Intelligence Market size was valued at USD 18.5 Billion in 2023 and is projected to reach USD 63.15 Billion by 2030, growing at a CAGR of 15.63% during the forecasted period 2024 to 2030.

Global Location Intelligence Market Drivers

The growth and development of the Location Intelligence Market drivers. These factors have a big impact on how Location Intelligence are demanded and adopted in different sectors. Several of the major market forces are as follows:

Proliferation of Spatial Data: A rich source of data for location intelligence and analytics is made possible by the exponential increase of spatial data produced by sources including GPS-enabled devices, Internet of Things sensors, and geographic information systems (GIS). In order to extract meaningful insights, there is a growing need for sophisticated tools and technologies due to the volume and diversity of spatial data.

Location-Based Services (LBS) are Growing: The demand for location intelligence and analytics solutions is fueled by the widespread use of location-based services including ride-sharing services, navigation apps, and location-based marketing. Companies use location data to target services based on local context, optimize operations, and improve customer experiences.

Need for Real-time information: To make wise judgments swiftly in the hectic business world of today, businesses need to have real-time access to location-based information. Businesses may increase agility and responsiveness by using location intelligence and analytics solutions to monitor events, identify patterns, and react to changes in real-time.

The amalgamation of location: intelligence and analytics with nascent technologies such as artificial intelligence (AI) and the Internet of Things (IoT) amplifies their potential and value proposition. Through the integration of sensor data, AI algorithms, and location data, enterprises may gain more profound understanding, anticipate future patterns, and streamline their decision-making procedures.

Urbanization and Smart City Initiatives: The use of location intelligence and analytics solutions is fueled by the global trend toward urbanization and the growth of smart city initiatives. These technologies help municipalities, urban planners, and government agencies create sustainable and effective urban environments by optimizing infrastructure development, city planning, and service delivery.

Cross-Industry Applications: Location analytics and intelligence are useful in a variety of industries, such as banking, logistics, healthcare, and retail. Businesses use location-based data to increase risk management, streamline supply chains, target customers more effectively, and increase operational efficiency across a range of company operations.

Regulatory Compliance and Risk Management: The use of location intelligence and analytics solutions for regulatory compliance and risk management is influenced by compliance requirements relating to location-based data, such as privacy laws and geospatial standards. These products are purchased by organizations to guarantee data governance, reduce risks, and prove compliance with legal and regulatory obligations.

The need for location-based: marketing is growing as companies use location analytics and intelligence to create more focused advertising and marketing campaigns. Organizations may increase customer engagement and conversion rates by providing tailored offers, promotions, and content depending on the geographic context of their customers by evaluating location data and consumer activity patterns.

Emergence of Digital Twin Technology: This technology opens up new possibilities for location intelligence and analytics by building virtual versions of real assets or environments. Organizations can improve decision-making processes in a variety of fields, such as manufacturing, infrastructure management, and urban planning, by incorporating location data into digital twin models and simulating scenarios.

Background, Decision Support, Data Gap Analysis, Implementation, and Steering Committee Recommendations

The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making. BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions. Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself. For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise. Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery. See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt

The Vegetation Technical Working Group (VTWG) of the Alaska Geospatial Council developed Standards for Production of Alaska Vegetation Map Version 1.1 (August 2022) to set technical goals for the production of a vegetation map that consistently covers all of Alaska with high spatial and ecological resolution. We compared vegetation maps and mapping frameworks with statewide coverage to the standards to determine the most appropriate map to select as the implementation of a statewide map and found that the AKVEG Map is the only map or mapping framework that fulfills all VTWG goals.

From September 27 through October 5, 2019, researchers from the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate shoreface morphology and geology near the Rockaway Peninsula, New York. The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation files, geographic information system (GIS) data, and formal Federal Geographic Data Committee (FGDC) Content Standard for Digital Geospatial Metadata (CSDGM). Processed subbottom profile images are also provided. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y revision 0 format (Barry and others, 1975). In addition to this data release, the SEG-Y files can be downloaded from the USGS Coastal and Marine Geoscience Data System (CMGDS) at, https://cmgds.marine.usgs.gov. Bathymetry and backscatter data were also collected during this survey and are available in Stalk and others (2020).

This dataset represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific 'production' or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys), and the Bureau of Census 2015 Cartographic State Boundaries. The Entity-Attribute section of this metadata describes these components in greater detail. Please note that the data on this site, although published at regular intervals, may not be the most current PLSS data that is available from the BLM. Updates to the PLSS data at the BLM State Offices may have occurred since this data was published. To ensure users have the most current data, please contact the BLM PLSS Data Set Manager.