A listing of web services published from the authoritative East Baton Rouge Parish Geographic Information System (EBRGIS) data repository. Services are offered in Esri REST, and the Open Geospatial Consortium (OGC) Web Mapping Service (WMS) or Web Feature Service (WFS) formats.

These are the results of the survey "GIS Support on Campus", which was announced via email on May 13, 2014 to Gis4lib, HIGHERED-L, and MAPS-L. I have received requests to view the survey results; however, there was no statement about redistribution in the original survey, other than a presentation at the Esri Education GIS Conference 2014. To ensure confidentiality for survey respondents, these results have been anonimized or aggregated where needed. The PDF of my presentation slides from the 2014 Esri Education GIS Conference can be accessed at http://proceedings.esri.com/library/userconf/educ14/index.html. Search for "Bringing It All Together: Rethinking GIS Support on Campus". If you have specific questions, feel free to email me at megan.slemons@emory.edu.

The coronavirus (COVID-19) is causing many universities and colleges to virtualize their classes. Schools that have not considered or postponed a decision to virtualize their GIS classes using ArcGIS Pro and ArcMap are revaluating their options. Those that have experimented with virtualizing ArcGIS Pro are seriously considering how to expand their virtualized offering._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

The global GIS Consulting Service market is expected to reach 1637 million by 2023, growing at a CAGR of 15% during the forecast period. Geospatial data analytics, predictive modeling, and situational awareness are key drivers of the market growth. The rising adoption of GIS in various industries, such as transportation, agriculture, energy, and government, is contributing to the market's expansion. The market is segmented based on type, application, and region. By type, the market is divided into custom mapping services, GIS mapping software development, and others. The custom mapping services segment is expected to hold the largest share of the market due to the increasing demand for customized maps for specific purposes. By application, the market is segmented into transportation, agriculture, energy, and others. The transportation segment is expected to witness the highest growth rate due to the growing use of GIS in traffic management, route optimization, and logistics. By region, the market is divided into North America, South America, Europe, Middle East & Africa, and Asia Pacific. North America is expected to hold the largest share of the market due to the presence of key players and the early adoption of GIS technology. Asia Pacific is expected to experience the highest growth rate due to the increasing infrastructure development and urbanization in the region.

The Digital Geologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (sahi_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (sahi_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (sahi_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (sahi_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (sahi_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (sahi_geology_metadata_faq.pdf). Please read the sahi_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (sahi_geology_metadata.txt or sahi_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

This layer (hosted feature layer) depicts the street sign support locations in the City of Canton, GA. This data set is maintained by the City of Canton's GIS division.For specific questions about this data or to provide feedback, please contact the City's GIS division: Alaina Ellis GIS Analyst alaina.ellis@cantonga.gov (770) 546-6780 Canton City Hall 110 Academy Street, Canton, GA 30114

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GIS In Utility Industry Market Size 2025-2029

The gis in utility industry market size is forecast to increase by USD 3.55 billion, at a CAGR of 19.8% between 2024 and 2029.

The utility industry's growing adoption of Geographic Information Systems (GIS) is driven by the increasing need for efficient and effective infrastructure management. GIS solutions enable utility companies to visualize, analyze, and manage their assets and networks more effectively, leading to improved operational efficiency and customer service. A notable trend in this market is the expanding application of GIS for water management, as utilities seek to optimize water distribution and reduce non-revenue water losses. However, the utility GIS market faces challenges from open-source GIS software, which can offer cost-effective alternatives to proprietary solutions. These open-source options may limit the functionality and support available to users, necessitating careful consideration when choosing a GIS solution. To capitalize on market opportunities and navigate these challenges, utility companies must assess their specific needs and evaluate the trade-offs between cost, functionality, and support when selecting a GIS provider. Effective strategic planning and operational execution will be crucial for success in this dynamic market.

What will be the Size of the GIS In Utility Industry Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe Global Utilities Industry Market for Geographic Information Systems (GIS) continues to evolve, driven by the increasing demand for advanced data management and analysis solutions. GIS services play a crucial role in utility infrastructure management, enabling asset management, data integration, project management, demand forecasting, data modeling, data analytics, grid modernization, data security, field data capture, outage management, and spatial analysis. These applications are not static but rather continuously unfolding, with new patterns emerging in areas such as energy efficiency, smart grid technologies, renewable energy integration, network optimization, and transmission lines. Spatial statistics, data privacy, geospatial databases, and remote sensing are integral components of this evolving landscape, ensuring the effective management of utility infrastructure. Moreover, the adoption of mobile GIS, infrastructure planning, customer service, asset lifecycle management, metering systems, regulatory compliance, GIS data management, route planning, environmental impact assessment, mapping software, GIS consulting, GIS training, smart metering, workforce management, location intelligence, aerial imagery, construction management, data visualization, operations and maintenance, GIS implementation, and IoT sensors is transforming the industry. The integration of these technologies and services facilitates efficient utility infrastructure management, enhancing network performance, improving customer service, and ensuring regulatory compliance. The ongoing evolution of the utilities industry market for GIS reflects the dynamic nature of the sector, with continuous innovation and adaptation to meet the changing needs of utility providers and consumers.

How is this GIS In Utility Industry Industry segmented?

The gis in utility industry industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ProductSoftwareDataServicesDeploymentOn-premisesCloudGeographyNorth AmericaUSCanadaEuropeFranceGermanyRussiaMiddle East and AfricaUAEAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW).

By Product Insights

The software segment is estimated to witness significant growth during the forecast period.In the utility industry, Geographic Information Systems (GIS) play a pivotal role in optimizing operations and managing infrastructure. Utilities, including electricity, gas, water, and telecommunications providers, utilize GIS software for asset management, infrastructure planning, network performance monitoring, and informed decision-making. The GIS software segment in the utility industry encompasses various solutions, starting with fundamental GIS software that manages and analyzes geographical data. Additionally, utility companies leverage specialized software for field data collection, energy efficiency, smart grid technologies, distribution grid design, renewable energy integration, network optimization, transmission lines, spatial statistics, data privacy, geospatial databases, GIS services, project management, demand forecasting, data modeling, data analytics, grid modernization, data security, field data capture, outage ma

PLSSQuarterQuarterSections_GCDB is the fourth level of a hierarchical break down of the Public Land Survey System Rectangular surveys. This data is Version 2.3 2020 of the Utah PLSS Fabric. This data set represents the GIS Version of the Public Land Survey System. Updates are expected annually as horizontal control positions from published sources and global positioning system (GPS) observations are added. 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. This data was orginally published on 1/3/2017. Updated 12/15/2020Updates were made to Quarter Quarter Sections in Utah County to add quarter-quarter sections to areas that were not broken down less than the Section level. These are labeled as SECDIVTYP = Z and SECDIVTXT = Unsurveyed Unprotracted. They were added using information from points collected by county surveyors, that is in the data and extrapolating information from adjoining sections wherever possible. They are still areas that could not be interpreted well enough and they were left empty, beyond the section level.

It is about updating to GIS information database, Decision Support Tool (DST) in collaboration with IWMI. With the support of the Fish for Livelihoods field team and IPs (MFF, BRAC Myanmar, PACT Myanmar, and KMSS) staff, collection of Global Positioning System GPS location data for year-1 (2019-20) 1,167 SSA farmer ponds, and year-2 (2020-21) 1,485 SSA farmer ponds were completed with different GPS mobile applications: My GPS Coordinates, GPS Status & Toolbox, GPS Essentials, Smart GPS Coordinates Locator and GPS Coordinates. The Soil and Water Assessment Tool (SWAT) model that integrates climate change analysis with water availability will provide an important tool informing decisions on scaling pond adoption. It can also contribute to a Decision Support Tool to better target pond scaling. GIS Data also contribute to identify the location point of the F4L SSA farmers ponds on the Myanmar Map by fiscal year from 1 to 5.

Contours were created by first generalizing a 30 meter digital elevation model with a focal filter. The output raster was then reclassified to group elevations into 200 foot intervals and finally converted into polygons. Contour polygons represent an approximate elevation.

ECM Community Support Services tables for a Quarterly Implementation Report. Including the County and Plan Details for both ECM and Community Support.This Medi-Cal Enhanced Care Management (ECM) and Community Supports Calendar Year Quarterly Implementation Report provides a comprehensive overview of ECM and Community Supports implementation in the programs' first year. It includes data at the state, county, and plan levels on total members served, utilization, and provider networks.ECM is a statewide MCP benefit that provides person-centered, community-based care management to the highest need members. The Department of Health Care Services (DHCS) and its MCP partners began implementing ECM in phases by Populations of Focus (POFs), with the first three POFs launching statewide in CY 2022.Community Supports are services that address members’ health-related social needs and help them avoid higher, costlier levels of care. Although it is optional for MCPs to offer these services, every Medi-Cal MCP offered Community Supports in 2022, and at least two Community Supports services were offered and available in every county by the end of the year.

The Digital Geologic-GIS Map of Mount Rainier National Park, Washington is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (mora_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (mora_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) this file (mora_geology.gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (mora_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (mora_geology_metadata_faq.pdf). Please read the mora_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: http://www.google.com/earth/index.html. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (mora_geology_metadata.txt or mora_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm). The GIS data projection is NAD83, UTM Zone 10N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth.

This data set represents the geologic contacts found in Utah as digitized by the Utah Geological Survey in 2000.

This data set represents forest facilities such as forest ranger stations and forest offices.Last Update: June, 2013

A Groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). The GW-NDST relies on several support models, including machine-learning models that require numerous GIS input files. This data release contains all GIS files required to run the GW-NDST and its machine-learning support models. The GIS files are packaged into three ZIP files (WI_County.zip, WT-ML.zip, and WI_Buff1km.zip) which are contained in this data release. Before running the GW-NDST, these ZIP files need to be downloaded and unzipped inside the "data_in/GIS/" subdirectory of the GW-NDST. The GW-NDST can be downloaded from the official software release on GitLab (https://doi.org/10.5066/P13ETB4Q). Further instructions for running the GW-NDST, and for acquiring requisite files, can be found in the software's readme file.

Cloud GIS Market Outlook

The global Cloud GIS market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.5% over the forecast period. The growth of the Cloud GIS market can be attributed to several factors, including the increasing demand for cloud-based geographic information systems (GIS) across various sectors, advancements in geospatial technologies, and rising investments in smart city projects.

One of the primary growth factors driving the Cloud GIS market is the increasing demand for real-time geospatial data and location-based services. As businesses and governments recognize the value of real-time data for decision-making, there has been a surge in the adoption of Cloud GIS solutions. These solutions offer scalable, flexible, and cost-effective ways to collect, store, analyze, and visualize geographic data, making them indispensable in sectors such as transportation, logistics, and urban planning.

Another significant growth driver is the rapid advancement in geospatial technologies, such as remote sensing, satellite imagery, and geographic data analytics. These technological advancements have expanded the capabilities of GIS systems, enabling more sophisticated data analysis and mapping solutions. The integration of AI and machine learning with GIS is further enhancing the ability to derive actionable insights from complex geospatial data, thus fueling the market growth.

Investments in smart city projects are also contributing to the growth of the Cloud GIS market. Governments and urban planners are increasingly leveraging Cloud GIS to manage and optimize urban infrastructure, transportation systems, and public services. Smart cities use geospatial data to improve resource management, enhance public safety, and provide better services to citizens. This trend is expected to continue, driving further demand for Cloud GIS solutions.

Regionally, North America is expected to hold the largest market share in the Cloud GIS market during the forecast period. The region's dominance can be attributed to the presence of leading technology companies, high adoption rates of advanced technologies, and substantial investments in infrastructure development. Additionally, Asia Pacific is anticipated to witness the highest growth rate due to rapid urbanization, increasing internet penetration, and government initiatives promoting digitalization and smart city projects.

Component Analysis

The Cloud GIS market is segmented by component into software and services. Within the software segment, cloud-based GIS solutions offer various functionalities, including data storage, data analysis, and visualization tools. These solutions are gaining traction due to their scalability, flexibility, and ability to integrate with other enterprise systems. Cloud GIS software allows organizations to access and analyze geographic data in real-time, facilitating better decision-making and strategic planning. As businesses and governments increasingly rely on geographic data, the demand for advanced GIS software solutions is expected to rise significantly.

On the other hand, the services segment encompasses various offerings such as consulting, integration, maintenance, and support services. These services are crucial for the successful implementation and operation of Cloud GIS systems. Consulting services help organizations understand their specific GIS needs and develop tailored solutions, while integration services ensure seamless integration of GIS with existing IT infrastructure. Maintenance and support services provide ongoing assistance to ensure the smooth functioning of GIS systems. The growing complexity of geospatial data and the need for specialized expertise are driving the demand for professional services in the Cloud GIS market.

Moreover, the shift towards cloud-based solutions has led to the emergence of new service models such as GIS-as-a-Service (GaaS). GaaS allows organizations to access GIS capabilities on a subscription basis, eliminating the need for significant upfront investments in hardware and software. This model is particularly beneficial for small and medium-sized enterprises (SMEs) that may not have the resources to invest in traditional GIS systems. As the adoption of GaaS increases, the services segment is expected to experience substantial growth.

In addition to these core services, many Cloud GIS providers offer value-added services such as data analytics, cus

Geographic Information Systems Platform Market Outlook

The global Geographic Information Systems (GIS) Platform Market size is projected to reach remarkable heights with an estimated value of USD 12 billion in 2023 and is expected to balloon to over USD 25 billion by 2032, reflecting a robust Compound Annual Growth Rate (CAGR) of 8%. This impressive growth trajectory is largely driven by the increasing demand for location-based services across various industries, including urban planning, transportation, and agriculture. As the world becomes increasingly interconnected, the necessity for real-time location data and advanced mapping solutions has never been more crucial, thereby fuelling the expansion of the GIS platform market.

One significant growth factor for the GIS platform market is the rapid urbanization occurring on a global scale. With more than half of the world's population now living in urban areas, cities are becoming larger and more complex. This trend necessitates sophisticated urban planning solutions that can effectively map, analyze, and visualize urban growth patterns. GIS platforms provide critical tools that enable urban planners to make informed decisions about land use, transportation networks, and infrastructure development. By integrating geographic data with socio-economic data, GIS applications help cities manage resources more efficiently and sustainably, thus driving the market forward.

Another driver of growth in the GIS platform market is the escalating need for effective disaster management solutions. Natural disasters such as hurricanes, earthquakes, and floods are becoming more frequent and severe, posing significant challenges for governments and emergency services worldwide. GIS platforms enable authorities to predict, prepare for, and respond to these disasters more effectively by providing detailed maps and models that can simulate potential scenarios and outcomes. The ability to integrate real-time data with historical records allows emergency response teams to optimize resource allocation and logistics, minimizing the impact of disasters on human lives and infrastructure.

The transportation and logistics sector is also a significant contributor to the growth of the GIS platform market. As global trade and e-commerce continue to grow, the demand for efficient and reliable transportation networks is increasing. GIS platforms provide valuable insights into route optimization, traffic management, and supply chain logistics. By enabling companies to analyze geographic data, GIS applications help to reduce transportation costs, improve delivery times, and enhance overall supply chain efficiency. As businesses increasingly look to leverage location-based data to gain a competitive advantage, the GIS platform market is set to experience sustained growth.

The role of a GIS Controller is becoming increasingly vital as the GIS platform market expands. A GIS Controller is responsible for overseeing the integration and management of geographic data within an organization, ensuring that the data is accurate, up-to-date, and accessible. This role involves coordinating with various departments to implement GIS solutions that align with organizational goals and enhance decision-making processes. As organizations across industries recognize the value of geographic data, the demand for skilled GIS Controllers is on the rise. These professionals play a crucial role in optimizing the use of GIS technology, enabling organizations to leverage location-based insights for strategic advantage.

Regionally, North America is anticipated to dominate the GIS platform market due to its advanced technological infrastructure and high adoption rates among various industries. The presence of leading GIS service providers in this region further bolsters its market position. Additionally, Asia Pacific is projected to witness the fastest growth over the forecast period, driven by rapid urbanization and increasing government initiatives to integrate GIS technology into urban planning and disaster management. The Middle East & Africa and Latin America are also expected to emerge as lucrative markets, as these regions look to harness the potential of GIS platforms to address their unique geographic challenges and drive economic development.

Component Analysis

The GIS platform market can be divided into three primary components: software, hardware, and services. Each of these segments plays a vital role in the overall functionality and adap

​Important Note: This item is in mature support as of April 2024 and will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This layer portrays 141 forest types across the contiguous United States and Alaska. This 250m raster was derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The purpose of this layer is to portray broad distribution patterns of forest cover in the United States and provide input to national scale modeling projects. Knowing where various forest types occur can be used to predict wildlife movements or design corridors, or to predict the effect of climate change on forest species.Dataset Summary The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center. The source format is 250-meter raster. This layer covers the entire United States.The original forest type layer is available from the USDA portal.What can you do with this layer?This layer has query, identify, and export image services available. The layer is restricted to a 24,000 x 24,000 pixel limit, which represents an area of nearly 450 miles on a side.This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

800+ GIS Engineers with 25+ years of experience in geospatial, We provide following as Advance Geospatial Services:

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The Digital Surficial Geologic-GIS Map of the Stroudsburg Quadrangle, New Jersey and Pennsylvania is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (stro_surficial_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (stro_surficial_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (stro_surficial_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (dewa_surficial_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (dewa_surficial_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (stro_surficial_geology_metadata_faq.pdf). Please read the dewa_surficial_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Pennsylvania Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (stro_surficial_geology_metadata.txt or stro_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).