Tagged image tiles as well as the Faster-RCNN framework for automatic extraction of road intersection points from USGS historical maps of the United States of America. The data and code have been prepared for the paper entitled "Automatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks" submitted to "International Journal of Geographic Information Science". The image tiles have been tagged manually. The Faster RCNN framework (see https://arxiv.org/abs/1611.10012) was captured from:https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md

This Innovative Technology Experiences for Students and Teachers (ITEST) project has developed, implemented, and evaluated a series of innovative Socio-Environmental Science Investigations (SESI) using a geospatial curriculum approach. It is targeted for economically disadvantaged 9th grade high school students in Allentown, PA, and involves hands-on geospatial technology to help develop STEM-related skills. SESI focuses on societal issues related to environmental science. These issues are multi-disciplinary, involve decision-making that is based on the analysis of merged scientific and sociological data, and have direct implications for the social agency and equity milieu faced by these and other school students. This project employed a design partnership between Lehigh University natural science, social science, and education professors, high school science and social studies teachers, and STEM professionals in the local community to develop geospatial investigations with Web-based Geographic Information Systems (GIS). These were designed to provide students with geospatial skills, career awareness, and motivation to pursue appropriate education pathways for STEM-related occupations, in addition to building a more geographically and scientifically literate citizenry. The learning activities provide opportunities for students to collaborate, seek evidence, problem-solve, master technology, develop geospatial thinking and reasoning skills, and practice communication skills that are essential for the STEM workplace and beyond. Despite the accelerating growth in geospatial industries and congruence across STEM, few school-based programs integrate geospatial technology within their curricula, and even fewer are designed to promote interest and aspiration in the STEM-related occupations that will maintain American prominence in science and technology. The SESI project is based on a transformative curriculum approach for geospatial learning using Web GIS to develop STEM-related skills and promote STEM-related career interest in students who are traditionally underrepresented in STEM-related fields. This project attends to a significant challenge in STEM education: the recognized deficiency in quality locally-based and relevant high school curriculum for under-represented students that focuses on local social issues related to the environment. Environmental issues have great societal relevance, and because many environmental problems have a disproportionate impact on underrepresented and disadvantaged groups, they provide a compelling subject of study for students from these groups in developing STEM-related skills. Once piloted in the relatively challenging environment of an urban school with many unengaged learners, the results will be readily transferable to any school district to enhance geospatial reasoning skills nationally.

MassGIS is working very closely with the State 911 Department in the state’s Executive Office of Public Safety and Security on the Next Generation 911 Emergency Call System. MassGIS developed and is maintaining the map and address information that are at the heart of this new system. Statewide deployment of this new 9-1-1 call routing system was completed in 2018.Address sources include the Voter Registration List from the Secretary of the Commonwealth, site addresses from municipal departments (primarily assessors), and customer address lists from utilities. Addresses from utilities were “anonymized” to protect customer privacy. The MAD was also validated for completeness using the Emergency Service List (a list of telephone land line addresses) from Verizon.The MAD contains both tabular and spatial data, with addresses being mapped as point features. At present, the MAD contains 3.2 million address records and 2.2 million address points. As the database is very dynamic with changes being made daily, the data available for download will be refreshed weekly.A Statewide Addressing Standard for Municipalities is another useful asset that has been created as part of this ongoing project. It is a best practices guide for the creation and storage of addresses for Massachusetts Municipalities.Points features with each point having an address to the building/floor/unit level, when that information is available. Where more than one address is located at a single location multiple points are included (i.e. "stacked points"). The points for the most part represent building centroids. Other points are located as assessor parcel centroids.Points will display at scales 1:75,000 and closer.MassGIS' service does not contain points for Boston; they may be accessed at https://data.boston.gov/dataset/live-street-address-management-sam-addresses/resource/873a7659-68b6-4ac0-98b7-6d8af762b6f1.More details about the MAD and Master Address Points.Map service also available.

The Department of Fish and Game - Division of Wildlife Conservation's game management units and subunits are the most requested of the Division's GIS data. Hunting and trapping regulations and other wildlife management issues often refer geographically to the effected Game Management Unit (GMU). This file gives the user access to the currently available digital representation of the GMU/UCUs. The purpose of the GMU and associated Subunits and Uniform coding units is to give a uniform, geographic based coding system for all State of Alaska wildlife population and habitat management and regulations. This data can be used for mapping or analysis purposes assuming it is used with comparable data.Uniform Coding UnitsPrior to 1982, Alaska Department of Fish and Game - Division of Wildlife Conservation (ADFG-DWC) had a variety of coding schemes (18) relating harvest and management information to geographical areas. This made it difficult when comparing statewide wildlife information gathered across the state. In 1982, a new standardized statewide, geographically-based, hierarchy system of coding was created called the Uniform Coding Unit or UCU system. Game management units (GMUs), Subunits, and uniform coding units (UCUs) are the underlying geographic foundation of the wildlife and habitat management and regulations for ADFG-DWC. The GMU/UCU system consists of five Regions which are divided into twenty-six (26) Game Management Units (GMUs). Many of the GMUs are divided into Subunits (e.g. GMU 15 has three (3) Subunits, 15A, 15B, and 15C). GMUs that are not divided into subunits have a "Z" designation for the subunit. GMUs and Subunits are further divided into Major Drainages, Minor Drainages and Specific Areas. The smallest of these areas (down to the "specific area") is referred to as a Uniform Coding Unit (UCU) and has a unique 10 character code associated with it. (NOTE: UCU layer is for internal and official use only, not for public use or distribution). The UCU code is used for geographically classifying harvest and management information. Data that cannot be tied to a specific code can be generalized to the next higher level of the hierarchy. For example:a location description that is within multiple "specific areas" within a "minor drainage" can be coded to the minor code with a "00" for the specific area. Unknown "minor drainages" can be coded to the "major drainage" level, etc. If the subunit is unknown or the area covers multiple subunits within a unit, the subunit can be specified as a "Z" code (e.g. an area within subunits 15A and 15B could be recorded as 15Z). If a geographic location covers multiple units or the unit is unknown, the most general code (statewide code) is recorded as 27Z-Z00. The original hardcopy master maps were drawn to portray the UCUs fairly accurately geographically, but were not necessarily precisely drawn (i.e. left vs. right bank of a river, or exact ridge line). Each UCU was represented by drawing boundaries on USGS 1:250,000 scale quadrangle maps with a thick magic marker. A list (database) of place-names and their corresponding UCU codes was created and is still used today to assign permit, harvest, and sealing information to one of these geographic areas. In 1988, the UCU boundaries were digitized (traced) from the original maps into a computerized Geographic Information System (ArcInfo). Minor changes were made in 1989. Effective July 1, 2006 - GMU 24 is now divided up into four subunit 24A, 24B, 24C, 24D. - GMU 21A and 21B - - boundary has been modified. Phase I2006-2008 - initial clean-up of boundaries for GMU 6, 9, 10, 12, 16, 19, 20, 25. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Jan 2009 - Priority has shifted to getting the bulk of the updates into the master. Verification and modifications based on the UCU list and the AB corrections will come at a later date. This shift is to attempt to get the master into a permanent SDE GDB, set it up with the GDB topology, make additional clean-up/edits using the GDB tools, set up versioning, make it easier to replicate to area offices, and to take advantage of the tools/features available thru ArcGIS Server with versioned GDBs. June 2009 - initial clean-up of boundaries for Southeast (GMU 1-5), GMU 17, and GMU 18. These have NOT been verified against the UCU master list or by area biologists. -ras July 1 2009 - initial clean-up of boundaries for GMU 7 and 8. Also some adjustments for 25D based on the NHD 2008 version and ArcHydro Tools "raindrop" feature. These have NOT been verified against the UCU master list or by area biologists. -ras Sept 17, 2009 - initial clean-up of boundaries for GMU 13. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Oct 21, 2009 - initial clean-up of boundaries for GMU 14 These modification have NOT been verified against the UCU master list or by area biologists. -rasNov 19, 2009 - initial clean-up of boundaries for GMU 15. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Dec 7, 2009 - initial clean-up of boundaries for GMU 22. These modification have NOT been verified against the UCU master list or by area biologists. -ras March 3, 2010 - initial clean-up of boundaries for GMU 23. These modification have NOT been verified against the UCU master list or by area biologists. -rasApril 10, 2010 - initial clean-up of boundaries for GMU 26. These modification have NOT been verified against the UCU master list or by area biologists. -ras May 2010 - This completes Phase I of refining the UCUs - bulk heads-up re-digitizing of all arcs. Phase II - Converting and establishing procedures for maintaining the master in an Enterprise GDB is underway. Effective July 1, 2010, Region II was split into Region 2 (GMU's 6, 7, 8, 14C, 15) and Region 4 (GMU's 9, 10, 11, 13, 14AB, 16, 17. This version was updated to reflect the change. An archive of the previous version (with Regions I, II, III, and V) is available on request as GMUMaster_063010. -ras2012-present - minor updates continue as needed and time allows, and as newer base maps are used.2014 minor updates continue as needed, including updates to domain listings (not affecting GIS geometry)Effective July 1, 2014- revision to GMU 18/19/21 boundary to clarify/correct previous insufficient boundary description. Passed during Spring 2014 Board of Game.2015 minor changes as needed

Uniform Coding UnitsPrior to 1982, Alaska Department of Fish and Game - Division of Wildlife Conservation (ADFG-DWC) had a variety of coding schemes (18) relating harvest and management information to geographical areas. This made it difficult when comparing statewide wildlife information gathered across the state. In 1982, a new standardized statewide, geographically-based, hierarchy system of coding was created called the Uniform Coding Unit or UCU system. Game management units (GMUs), Subunits, and uniform coding units (UCUs) are the underlying geographic foundation of the wildlife and habitat management and regulations for ADFG-DWC. The GMU/UCU system consists of five Regions which are divided into twenty-six (26) Game Management Units (GMUs). Many of the GMUs are divided into Subunits (e.g. GMU 15 has three (3) Subunits, 15A, 15B, and 15C). GMUs that are not divided into subunits have a "Z" designation for the subunit. GMUs and Subunits are further divided into Major Drainages, Minor Drainages and Specific Areas. The smallest of these areas (down to the "specific area") is referred to as a Uniform Coding Unit (UCU) and has a unique 10 character code associated with it. (NOTE: UCU layer is for internal and official use only, not for public use or distribution). The UCU code is used for geographically classifying harvest and management information. Data that cannot be tied to a specific code can be generalized to the next higher level of the hierarchy. For example:a location description that is within multiple "specific areas" within a "minor drainage" can be coded to the minor code with a "00" for the specific area. Unknown "minor drainages" can be coded to the "major drainage" level, etc. If the subunit is unknown or the area covers multiple subunits within a unit, the subunit can be specified as a "Z" code (e.g. an area within subunits 15A and 15B could be recorded as 15Z). If a geographic location covers multiple units or the unit is unknown, the most general code (statewide code) is recorded as 27Z-Z00. The original hardcopy master maps were drawn to portray the UCUs fairly accurately geographically, but were not necessarily precisely drawn (i.e. left vs. right bank of a river, or exact ridge line). Each UCU was represented by drawing boundaries on USGS 1:250,000 scale quadrangle maps with a thick magic marker. A list (database) of place-names and their corresponding UCU codes was created and is still used today to assign permit, harvest, and sealing information to one of these geographic areas. In 1988, the UCU boundaries were digitized (traced) from the original maps into a computerized Geographic Information System (ArcInfo). Minor changes were made in 1989. Effective July 1, 2006 - GMU 24 is now divided up into four subunit 24A, 24B, 24C, 24D. - GMU 21A and 21B - - boundary has been modified. Phase I2006-2008 - initial clean-up of boundaries for GMU 6, 9, 10, 12, 16, 19, 20, 25. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Jan 2009 - Priority has shifted to getting the bulk of the updates into the master. Verification and modifications based on the UCU list and the AB corrections will come at a later date. This shift is to attempt to get the master into a permanent SDE GDB, set it up with the GDB topology, make additional clean-up/edits using the GDB tools, set up versioning, make it easier to replicate to area offices, and to take advantage of the tools/features available thru ArcGIS Server with versioned GDBs. June 2009 - initial clean-up of boundaries for Southeast (GMU 1-5), GMU 17, and GMU 18. These have NOT been verified against the UCU master list or by area biologists. -ras July 1 2009 - initial clean-up of boundaries for GMU 7 and 8. Also some adjustments for 25D based on the NHD 2008 version and ArcHydro Tools "raindrop" feature. These have NOT been verified against the UCU master list or by area biologists. -ras Sept 17, 2009 - initial clean-up of boundaries for GMU 13. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Oct 21, 2009 - initial clean-up of boundaries for GMU 14 These modification have NOT been verified against the UCU master list or by area biologists. -rasNov 19, 2009 - initial clean-up of boundaries for GMU 15. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Dec 7, 2009 - initial clean-up of boundaries for GMU 22. These modification have NOT been verified against the UCU master list or by area biologists. -ras March 3, 2010 - initial clean-up of boundaries for GMU 23. These modification have NOT been verified against the UCU master list or by area biologists. -rasApril 10, 2010 - initial clean-up of boundaries for GMU 26. These modification have NOT been verified against the UCU master list or by area biologists. -ras May 2010 - This completes Phase I of refining the UCUs - bulk heads-up re-digitizing of all arcs. Phase II - Converting and establishing procedures for maintaining the master in an Enterprise GDB is underway. Effective July 1, 2010, Region II was split into Region 2 (GMU's 6, 7, 8, 14C, 15) and Region 4 (GMU's 9, 10, 11, 13, 14AB, 16, 17. This version was updated to reflect the change. An archive of the previous version (with Regions I, II, III, and V) is available on request as GMUMaster_063010. -ras2012-present - minor updates continue as needed and time allows, and as newer base maps are used.2014 minor updates continue as needed, including updates to domain listings (not affecting GIS geometry)Effective July 1, 2014- revision to GMU 18/19/21 boundary to clarify/correct previous insufficient boundary description. Passed during Spring 2014 Board of Game.

This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Geography With Emphasis In Geographic Information Systems. It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Geography With Emphasis In Geographic Information Systems. This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Geoinformatics (Geographic Information Systems). It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Geoinformatics (Geographic Information Systems). This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

Northeastern United States County Boundary data are intended for geographic display of state and county boundaries at statewide and regional levels. Use it to map and label counties on a map. These data are derived from Northeastern United States Political Boundary Master layer. This information should be displayed and analyzed at scales appropriate for 1:24,000-scale data. The State of Connecticut, Department of Environmental Protection (CTDEP) assembled this regional data layer using data from other states in order to create a single, seamless representation of political boundaries within the vicinity of Connecticut that could be easily incorporated into mapping applications as background information. More accurate and up-to-date information may be available from individual State government Geographic Information System (GIS) offices. Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.)

This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Geography/Geographic Information Science. It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Geography/Geographic Information Science. This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

A data collection campaign using the MODIS/ASTER airborne simulator (MASTER) was conducted in the greater Phoenix metropolitan area in July 2011 to collect visible through mid-infrared multispectral imagery. High resolution (7 m/pixel) land surface temperature products for day and night periods were calculated using the mid-infrared bands of data; surface reflectance, albedo, and Normalized Difference Vegetation Index (NDVI) products were calculated using the visible through shortwave infrared band data for 41 select neighborhoods. While the full MASTER dataset has been processed to at-sensor radiance, it did not include native geolocation data. As georeferencing the entire dataset was not possible with funds available, the processed data described above were extracted for the 41 spatially discrete Phoenix Area Social Survey neighborhoods within the MASTER flight boundary.

This is a geographic dataset of the Master Development Plans (MDP). A MDP is required for any development of two or more phases. The agreement includes the location and widths of proposed streets, lots, blocks, floodplains and easement information.

Connecticut and Vicinity Town Boundary data are intended for geographic display of state, county and town (municipal) boundaries at statewide and regional levels. Use it to map and label towns on a map. These data are derived from Northeastern United States Political Boundary Master layer. This information should be displayed and analyzed at scales appropriate for 1:24,000-scale data. The State of Connecticut, Department of Environmental Protection (CTDEP) assembled this regional data layer using data from other states in order to create a single, seamless representation of political boundaries within the vicinity of Connecticut that could be easily incorporated into mapping applications as background information. More accurate and up-to-date information may be available from individual State government Geographic Information System (GIS) offices. Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.)

Northeastern United States Town Boundary data are intended for geographic display of state, county and town (municipal) boundaries at statewide and regional levels. Use it to map and label towns on a map. These data are derived from Northeastern United States Political Boundary Master layer. This information should be displayed and analyzed at scales appropriate for 1:24,000-scale data. The State of Connecticut, Department of Environmental Protection (CTDEP) assembled this regional data layer using data from other states in order to create a single, seamless representation of political boundaries within the vicinity of Connecticut that could be easily incorporated into mapping applications as background information. More accurate and up-to-date information may be available from individual State government Geographic Information System (GIS) offices. Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.)

The United States State Boundaries database is a geographic database of state political boundaries. The database includes boundaries for all 50 states plus Puerto Rico, Washington D.C., American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands. In order for others to use the information in the Census MAF/TIGER database in a geographic information system (GIS) or for other geographic applications, the Census Bureau releases to the public extracts of the database in the form of TIGER/Line Shapefiles. State boundaries with shorelines cut in. The State Boundary with Detailed Shorelines database was created using TIGER/LINE 2011 shapefile data gathered from ESRI's Geography Network. The individual county shapefiles were processed into Arc/Info coverages and then appended together to create complete state coverages. OST-R/BTS Hydrographic data was integrated to create detailed shorelines. The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. States and equivalent entities are the primary governmental divisions of the United States. In addition to the fifty States, the Census Bureau treats the District of Columbia, Puerto Rico, and each of the Island Areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands) as the statistical equivalents of States for the purpose of data presentation.

Connecticut and Vicinity State Boundary data are intended for geographic display of state boundaries at statewide and regional levels. Use it to map and label states on a map. These data are derived from Northeastern United States Political Boundary Master layer. This information should be displayed and analyzed at scales appropriate for 1:24,000-scale data. The State of Connecticut, Department of Environmental Protection (CTDEP) assembled this regional data layer using data from other states in order to create a single, seamless representation of political boundaries within the vicinity of Connecticut that could be easily incorporated into mapping applications as background information. More accurate and up-to-date information may be available from individual State government Geographic Information System (GIS) offices. Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.)

In order for others to use the information in the Census MAF/TIGER database in a geographic information system (GIS) or for other geographic applications, the Census Bureau releases to the public extracts of the database in the form of TIGER/Line Shapefiles.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2010 Census blocks nest within every other 2010 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

The US Census TIGER/Line Geodatabases are spatial extracts from the Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System, designed for use with Geographic Information Systems (GIS) software. They allow users to visualize and analyze geographic features.These geodatabases are derived from the MAF/TIGER system, a comprehensive geographic database for the United States. They contain data on geographic boundaries and features, including roads, railroads, rivers, lakes, and political boundaries (state, county, city). They also include Census statistical boundaries like census blocks, block groups, and census tracts.While TIGER/Line Geodatabases do not contain demographic data, they have geographic entity codes that can be linked to demographic data available on data.census.gov. This allows users to combine geographic features with demographic statistics for analysis and mapping.Further details of the geographic boundaries and features can be found in the TIGER/Line Shapefiles technical documentation.TIGER/Line Geodatabaseshttps://www.census.gov/geographies/mapping-files/time-series/geo/tiger-geodatabase-file.htmlTIGER/Line Geodatabase Documentationhttps://www.census.gov/programs-surveys/geography/technical-documentation/complete-technical-documentation/tiger-geodatabase-file.htmlTIGER/Line Shapefiles and TIGER/Line Files Technical Documentationhttps://www.census.gov/programs-surveys/geography/technical-documentation/complete-technical-documentation/tiger-geo-line.htmlTIGERweb REST Serviceshttps://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_restmapservice.htmlTIGERweb WMS Serviceshttps://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_wms.html

The global geospatial analytics market is predicted to expand significantly, with a projected CAGR of 11.28% from 2025 to 2033. Valued at 89.23 billion USD in 2025, the market is expected to reach new heights during the forecast period. Key drivers fueling this growth include increasing adoption of GIS (Geographic Information Systems) and GPS (Global Positioning Systems), rising demand for location-based services, and growing awareness of the benefits of geospatial data in decision-making. Additionally, advancements in cloud computing, artificial intelligence, and machine learning further contribute to the market's expansion. Key segments in the geospatial analytics market include services, types, technologies, and regions. Consulting, integration and deployment, support and maintenance are prominent services offered in the market. Surface and field analytics, network and location analytics, geovisualization, and other types are also significant segments. Remote sensing GIS GPS, other technologies, and their applications across various regions, including North America, Europe, Asia Pacific, Middle East & Africa, and South America, shape the market dynamics. Recent developments include: Sept 2022 Sanborn Map Company Inc., a provider of geospatial solutions for government and commercial clients, has acquired Applied Geographics, Inc., which helped numerous organisations in finding the most effective GIS, location intelligence, and geospatial solutions., January 2022 With the help of integrated and improved data, ideal site analysis and path planning, and customized customer experiences, Blueprint Technologies and Precisely have announced a partnership to help businesses gain a competitive edge., Geospatial analytics is being used by telecom companies like T-Mobile to optimise coverage and quality of service while planning deployments. While organising service deployments and coverage, telecommunications providers must consider a wide range of criteria. They must take into account the varying usage patterns, service demands, and the dynamic nature of the areas they serve., According to industry analysts, the abundance of geospatial data accessible is outpacing people's capacity to comprehend it as government and business deploy more satellites, drones, and sensors than ever before. Artificial intelligence, according to Mark Munsell, Deputy Director for Data and Digital Innovation at the National Geospatial-Intelligence Agency., Geospatial intelligence experts Orbital Insight and Carahsoft Technologies Corp. have joined forces. Carahsoft will act as Orbital Insight's Master Government Aggregator in accordance with the agreement. Through Carahsoft's reseller partners, Information Technology Enterprise Solutions - Software 2 (ITES-SW2), NASA Solutions for Enterprise-Wide Procurement (SEWP) V, National Association of State Procurement Officials (NASPO), ValuePoint, National Cooperative Purchasing Alliance (NCPA), and OMNIA Partners contracts, the company's AI-powered geospatial data analytics are now accessible to the public sector.. Potential restraints include: High Initial Investment Cost.

Northeastern United States State Boundary data are intended for geographic display of state boundaries at statewide and regional levels. Use it to map and label states on a map. These data are derived from Northeastern United States Political Boundary Master layer. This information should be displayed and analyzed at scales appropriate for 1:24,000-scale data. The State of Connecticut, Department of Environmental Protection (CTDEP) assembled this regional data layer using data from other states in order to create a single, seamless representation of political boundaries within the vicinity of Connecticut that could be easily incorporated into mapping applications as background information. More accurate and up-to-date information may be available from individual State government Geographic Information System (GIS) offices. Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.)

Analysis of ‘Northeast State Lines’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/c289af13-58b6-49b2-a1ff-f344e657ca0a on 27 January 2022.

--- Dataset description provided by original source is as follows ---

Northeastern United States State Boundary data are intended for geographic display of state boundaries at statewide and regional levels. Use it to map and label states on a map. These data are derived from Northeastern United States Political Boundary Master layer. This information should be displayed and analyzed at scales appropriate for 1:24,000-scale data. The State of Connecticut, Department of Environmental Protection (CTDEP) assembled this regional data layer using data from other states in order to create a single, seamless representation of political boundaries within the vicinity of Connecticut that could be easily incorporated into mapping applications as background information. More accurate and up-to-date information may be available from individual State government Geographic Information System (GIS) offices. Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.)

--- Original source retains full ownership of the source dataset ---