Geospatial data can provide valuable visualization and analytical abilities to Facility and Resource Managers in regards to maintained landscapes throughout the NPS. Maintained landscapes are records in the Facility Management Software System (FMSS) and can include battlefields, ornamental gardens, picnic areas, and other types. To map a maintained area and the features within it at the enterprise level, a geospatial data service is needed to ensure consistency, accuracy, and thorough documentation of data lineage. The Maintained Landscape Spatial Data Service will structure maintained landscape data into a common format that will enable GIS data to be easily integrated, traced, analyzed and shared across the park. Such a structure will increase users’ ability to discern the quality and accuracy of the data enabling the user to make better data driven decisions. This schema is designed to match the structure and hierarchy of FMSS so that should this system become spatially enabled this data could be utilized. Within the FMSS database, features are organized in locations records and assets records. A location record could be thought of as a bin, within which component assets records are stored. Park Facilities Management Division(PFMD) Employees of the National Park Service are tasked with managing facilities such as roads, trails, buildings, and landscapes. To properly manage these assets PFMD must make management decisions based on spatial and non-spatial data. This service allows the accurate geographic representation of maintained landscapes in a common service-wide schema. Furthermore, the establishment of a maintained landscapes spatial data service will allow for the integration of several NPS managed databases. These include (but are not limited to) the Facilities Management Software System (FMSS), the Cultural Resources Enterprise Geographic Information System (CRGIS), the Cultural Landscapes Inventory (CLI), and the List of Classified Structures (LCS). The Cultural Resource Enterprise GIS dataset contains the cultural landscapes inventory spatial data, list of classified structures spatial data, National Register spatial data and links to all of these databases, as well as other partner programs

The Spatiotemporal Big Data Store Tutorial introduces you the the capabilities of the spatiotemporal big data store in ArcGIS Data Store, available with ArcGIS Enterprise. Observation data can be moving objects, changing attributes of stationary sensors, or both. The spatiotemporal big data store enables archival of high volume observation data, sustains high velocity write throughput, and can run across multiple machines (nodes). Adding additional machines adds capacity, enabling you to store more data, implement longer retention policies of your data, and support higher data write throughput.

After completing this tutorial you will:

Understand the concepts and best practices for working with the spatiotemporal big data store available with ArcGIS Data Store. Have configured the appropriate security settings and certificates on a enterprise server, real-time server, and a data server which are necessary for working with the spatiotemporal big data store. Have learned how to process and archive large amounts of observational data in the spatiotemporal big data store. Have learned how to visualize the observational data that is stored in the spatiotemporal big data store.

Releases

Each release contains a tutorial compatible with the version of GeoEvent Server listed. The release of the component you deploy does not have to match your version of ArcGIS GeoEvent Server, so long as the release of the component is compatible with the version of GeoEvent Server you are using. For example, if the release contains a tutorial for version 10.6; this tutorial is compatible with ArcGIS GeoEvent Server 10.6 and later. Each release contains a Release History document with a compatibility table that illustrates which versions of ArcGIS GeoEvent Server the component is compatible with.

NOTE: The release strategy for ArcGIS GeoEvent Server components delivered in the ArcGIS GeoEvent Server Gallery has been updated. Going forward, a new release will only be created when

  a component has an issue,
  is being enhanced with new capabilities,
  or is not compatible with newer versions of ArcGIS GeoEvent Server.

This strategy makes upgrades of these custom
components easier since you will not have to
upgrade them for every version of ArcGIS GeoEvent Server
unless there is a new release of
the component. The documentation for the
latest release has been
updated and includes instructions for updating
your configuration to align with this strategy.

Latest

Release 4 - February 2, 2017 - Compatible with ArcGIS GeoEvent Server 10.5 and later.

Previous

Release 3 - July 7, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.

Release 2 - May 17, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.

Release 1 - March 18, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.

Esri ArcGIS Online Hosted, View Feature Layer which provides access to the Maryland MyCoast Report Locations data product.Maryland MyCoast Reports data consists of point geometric features which represent the geographic locations of MyCoast reports that have been documented throughout the State of Maryland. MyCoast Reports are created to document on-the-ground impacts of flooding & damage during storm events. MyCoast: Maryland is in collaboration with, and directly supported by, the Maryland Department of Natural Resources (DNR). Maryland MyCoast Reports data has been downloaded & spatially enabled by the MDOT SHA OIT Enterprise Information Services - GIS Team by using the 'Download Reports' functionality of the MyCoast website. The resulting data is spatially enabled via Lat/Long values and is now available as a Hosted View Feature Layer on ArcGIS Online (AGOL) for Maryland. This data product is updated on a monthly routine basis to include new reports from the previous month.Maryland MyCoast Report data is owned by the Maryland Department of Natural Resources (DNR).For more information, contact MDOT SHA OIT Enterprise Information Services:Email: GIS@mdot.maryland.gov

Link to landing page referenced by identifier. Service Protocol: Link to landing page referenced by identifier. Link Function: information-- dc:identifier.

GIS Data Management Market Outlook

The global GIS Data Management market size is projected to grow from USD 12.5 billion in 2023 to USD 25.6 billion by 2032, exhibiting a CAGR of 8.4% during the forecast period. This impressive growth is driven by the increasing adoption of geographic information systems (GIS) across various sectors such as urban planning, disaster management, and agriculture. The rising need for effective data management systems to handle the vast amounts of spatial data generated daily also significantly contributes to the market's expansion.

One of the primary growth factors for the GIS Data Management market is the burgeoning demand for spatial data analytics. Businesses and governments are increasingly leveraging GIS data to make informed decisions and strategize operational efficiencies. With the rapid urbanization and industrialization worldwide, there's an unprecedented need to manage and analyze geographic data to plan infrastructure, monitor environmental changes, and optimize resource allocation. Consequently, the integration of GIS with advanced technologies like artificial intelligence and machine learning is becoming more prominent, further fueling market growth.

Another significant factor propelling the market is the advancement in GIS technology itself. The development of sophisticated software and hardware solutions for GIS data management is making it easier for organizations to capture, store, analyze, and visualize geographic data. Innovations such as 3D GIS, real-time data processing, and cloud-based GIS solutions are transforming the landscape of geographic data management. These advancements are not only enhancing the capabilities of GIS systems but also making them more accessible to a broader range of users, from small enterprises to large governmental agencies.

The growing implementation of GIS in disaster management and emergency response activities is also a critical factor driving market growth. GIS systems play a crucial role in disaster preparedness, response, and recovery by providing accurate and timely geographic data. This data helps in assessing risks, coordinating response activities, and planning resource deployment. With the increasing frequency and intensity of natural disasters, the reliance on GIS data management systems is expected to grow, resulting in higher demand for GIS solutions across the globe.

Geospatial Solutions are becoming increasingly integral to the GIS Data Management landscape, offering enhanced capabilities for spatial data analysis and visualization. These solutions provide a comprehensive framework for integrating various data sources, enabling users to gain deeper insights into geographic patterns and trends. As organizations strive to optimize their operations and decision-making processes, the demand for robust geospatial solutions is on the rise. These solutions not only facilitate the efficient management of spatial data but also support advanced analytics and real-time data processing. By leveraging geospatial solutions, businesses and governments can improve their strategic planning, resource allocation, and environmental monitoring efforts, thereby driving the overall growth of the GIS Data Management market.

Regionally, North America holds a significant share of the GIS Data Management market, driven by high technology adoption rates and substantial investments in GIS technologies by government and private sectors. However, Asia Pacific is anticipated to witness the highest growth rate during the forecast period. The rapid urbanization, economic development, and increasing adoption of advanced technologies in countries like China and India are major contributors to this growth. Governments in this region are also focusing on smart city projects and infrastructure development, which further boosts the demand for GIS data management solutions.

Component Analysis

The GIS Data Management market is segmented by component into software, hardware, and services. The software segment is the largest and fastest-growing segment, driven by the continuous advancements in GIS software capabilities. GIS software applications enable users to analyze spatial data, create maps, and manage geographic information efficiently. The integration of GIS software with other enterprise systems and the development of user-friendly interfaces are key factors propelling the growth of this segment. Furthermore, the rise of mobile GIS applications, which allow field data collectio

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

This map displays the Quantitative Precipitation Forecast (QPF) for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.qpf.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

This is a demonstration layer implementing INSPIRE Protected Sites (PS) - Nature Conservation (Surface) data according to the INSPIRE default data model. It is provided as a courtesy and should not be used for any purpose other than demonstration.DEMONSTRATION NOTE: This dataset uses the default INSPIRE data model (rather than flattened/streamlined Alternative Encoding). It is published from ArcGIS Pro to ArcGIS Enterprise with OGC map services enabled (WMS and WFS), then INSPIRE-specific custom capabilities are manually added to the INSPIRE View Service (WMS). This web service is then registered in ArcGIS Online and shared via the ArcGIS Hub catalog.About Protected SitesA protected site is an area designated or managed within a framework of international, Community and Member States' legislation to achieve specific conservation objectives. According to IUCN and adopted for the INSPIRE context a protected site is: An area of land and/or sea especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means.

Protected sites may be located in terrestrial, aquatic and/or marine environments, and may be under either public or private ownership. Learn more

Digital Map Service Market Outlook

The global digital map service market size is projected to grow significantly, from approximately $18.9 billion in 2023 to an estimated $53.1 billion by 2032, reflecting a compelling Compound Annual Growth Rate (CAGR) of 12.5%. This robust growth is driven by the increasing adoption of digital mapping technologies across diverse industries and the rising demand for real-time geographic and navigation data in both consumer and enterprise applications.

One of the primary growth factors for the digital map service market is the expanding use of digital maps in the automotive sector, particularly in the development of Advanced Driver Assistance Systems (ADAS) and autonomous vehicles. These technologies rely heavily on precise and up-to-date mapping data for navigation, obstacle detection, and other functionalities, making digital maps indispensable. Additionally, the proliferation of mobile devices and the integration of mapping services in applications such as ride-sharing, logistics, and local search have significantly contributed to market expansion.

Another significant driver is the increasing reliance on Geographic Information Systems (GIS) across various industries. GIS technology enables organizations to analyze spatial information, improve decision-making processes, and enhance operational efficiencies. Industries such as government, defense, agriculture, and urban planning utilize GIS for land use planning, disaster management, and resource allocation, among other applications. The continuous advancements in GIS technology and the integration of artificial intelligence (AI) and machine learning (ML) are expected to further propel market growth.

The rising demand for real-time location data is also a crucial factor fueling the growth of the digital map service market. Real-time location data is essential for applications such as fleet management, asset tracking, and public safety. Businesses leverage this data to optimize routes, monitor assets, and enhance customer service. The increasing implementation of Internet of Things (IoT) devices and the growing importance of location-based services are likely to sustain the demand for real-time mapping solutions in the coming years.

Regionally, North America leads the digital map service market, driven by the high adoption rate of advanced technologies and the presence of major players in the region. However, the Asia Pacific region is expected to witness the fastest growth, attributed to rapid urbanization, increasing smartphone penetration, and government initiatives to develop smart cities. Europe, Latin America, and the Middle East & Africa are also anticipated to experience substantial growth, fueled by the rising demand for digital mapping solutions across various sectors.

Service Type Analysis

In the digital map service market, the service type segment includes mapping and navigation, geographic information systems (GIS), real-time location data, and others. Mapping and navigation services hold a significant share in the market, primarily due to their extensive use in personal and commercial navigation systems. These services provide detailed road maps, traffic updates, and route planning, which are essential for everyday commuting and logistics operations. The continuous advancements in navigation technologies, such as integration with AI and ML for predictive analytics, are expected to enhance the accuracy and functionality of these services.

Geographic Information Systems (GIS) represent another critical segment within the digital map service market. GIS technology is widely used in various applications, including urban planning, environmental management, and disaster response. The ability to analyze and visualize spatial data in multiple layers allows organizations to make informed decisions and optimize resource allocation. The integration of GIS with other emerging technologies, such as drones and remote sensing, is further expanding its application scope and driving market growth.

Real-time location data services are gaining traction due to their importance in applications like fleet management, asset tracking, and location-based services. These services provide up-to-the-minute information on the geographical position of assets, vehicles, or individuals, enabling businesses to improve operational efficiency and customer satisfaction. The growing adoption of IoT devices and the increasing need for real-time visibility in supply chain operations are expected to bolster the demand for real-time location data services.</p&

AFRAA Data Upgrade & Transition Plan for 2025 Fire Season

Given the mission-critical nature of AFRAA dataset and federal mandates, the FS Enterprise Data Warehouse (EDW) and AFRAA data stewards will fully support the legacy map services throughout the 2025 fire season before retirement. The latest 2025 data, approved by Forest Service Regional Forester and GIS Coordinators, has been integrated into legacy schemas, ensuring authoritative data while maintaining backward compatibility for applications relying on legacy endpoints.

What You Need to KnowWhere is the New Data

Most users will use the new map image service REST endpoints:

https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_AerialFireRetardantAvoidanceAreas_Aquatic_01/MapServer https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_AerialFireRetardantAvoidanceAreas_Terrestrial_01/MapServer

Metadata is available in these ArcGIS items that reference the new map services:

Fire_AerialFireRetardantAvoidanceAreas_Aquatic (Landing Page) Fire_AerialFireRetardantAvoidanceAreas_Terrestrial (Landing Page)

Sync Enable ArcGIS Online Hosted Feature Services:

Aquatic Hosted Feature Service Terrestrial Hosted Feature Service

Internal FS users can make direct SDE connections (see detailed instructions on the AFRAA SharePoint ). Downloadable Data from the FS GeoData Clearinghouse:

Fire_AerialFireRetardantAvoidanceAreas_Aquatic.gdb.zip Fire_AerialFireRetardantAvoidanceAreas_Terrestrial.gdb.zip

When Will the Legacy Product Be Retired?

March 14, 2025 – New terrestrial map service available, and a deprecation watermark is added to the legacy service. March 14, 2025 - Region 3 approved 2025 aquatic data via the legacy service endpoint. April 1, 2025 – All 2025 approved data loaded into both new and legacy services. April 1, 2025 – New aquatic service published, and a deprecation watermark is added to the legacy service. April 1, 2025 – Legacy download products removed from the Clearinghouse and replaced with the new versions. April 7, 2025 – Sync enabled Hosted Feature Services published to ArcGIS Online October 1, 2025 – Legacy services stopped. Fire personnel can contact SM.FS.afraa@usda.gov during regular business hours if unknown dependencies are discovered. The services will be restarted if needed. November 1, 2025 – Unless an extension is requested, legacy services will be deleted, and all feature classes will be removed from EDW, making the data inaccessible.

What Products Are Being Deprecated?

Terrestrial Map Services & Associated Feature ClassesLegacy Terrestrial:

https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_AerialFireRetardantAvoidanceAreas_01/MapServerS_USA.AerialFireRetardantAvoidance

New Authoritative Terrestrial:

https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_AerialFireRetardantAvoidanceAreas_Terrestrial_01/MapServerS_USA.Fire_AerialFireRetardantAvoidanceAreas_Terrestrial

Aquatic Map Services & Associated Feature Classes

Legacy Aquatic:

https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_AerialFireRetardantHydrographicAvoidanceAreas_01/MapServer

S_R01.AFRAA_Hydro S_R02.AFRAA_Hydro S_R03.AFRAA_Hydro S_R04.AFRAA_Hydro S_R05.AFRAA_Hydro S_R06.AFRAA_Hydro S_R08.AFRAA_Hydro S_R09.AFRAA_Hydro S_R10.AFRAA_Hydro

New Authoritative Aquatic Map Service and Feature Class:

https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_AerialFireRetardantAvoidanceAreas_Aquatic_01/MapServerS_USA.Fire_AerialFireRetardantAvoidanceAreas_AquaticThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

Visit the FEMA Community Disaster Resilinece Zones Homepage for more information and the Application to see the Zones.To download GIS data, users must be logged into any ArcGIS Online or Enterprise account. For users who require tabular data (.csv format only) or do not have an ArcGIS Online or Enterprise account, click here to download.A law signed by President Biden on Dec. 20, 2022— the Community Disaster Resilience Zones Act—will build disaster resilience across the nation by creating and designating resilience zones which identifies disadvantaged communities most at-risk to natural hazards.This new law amends the Robert T. Stafford Disaster Relief and Emergency Assistance Act and applies FEMA’s National Risk Index to identify communities that are most vulnerable to natural hazards.These designated zones will receive targeted support to access federal funding to plan for resilience projects that will help them reduce impacts caused by climate change and natural hazards. It will also enable communities to work across a range of federal and private sector partners to maximize funding and provide technical assistance, strengthening community resilience.Designated zones will receive targeted federal support, such as increased federal cost-share for the Building Resilient Infrastructure and Communities program, lessening the financial burden on communities to perform resilience-related activities. This layer allows users to identify the FEMA Community Disaster Resilience Zones, which target Census tracts identified as disadvantage communities most at-risk to natural hazards as a part of the Community Disaster Resilience Zones Act. The data methodology is available on the "Designation Methodology" page of the related FEMA Community Disaster Resilience Zones product.

GIS Controller Market Outlook

The GIS Controller market size was valued at $8.3 billion in 2023 and is projected to reach $15.6 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.2% during the forecast period. This significant growth factor can be attributed primarily to increasing urbanization, the rising need for efficient spatial data management, and technological advancements in geospatial analytics.

One of the prime growth factors driving the GIS Controller market is the escalating demand for smart city solutions. As urbanization continues to rise globally, governments and municipalities are increasingly investing in smart city initiatives to improve urban planning, public safety, and resource management. GIS controllers play a crucial role in these initiatives by providing accurate spatial data, which is essential for efficient infrastructure development, traffic management, and environmental monitoring. Furthermore, the integration of GIS with other technologies such as IoT and AI is opening new avenues for real-time data analysis and decision-making, further propelling market growth.

The agriculture sector is another significant contributor to the growth of the GIS Controller market. Precision farming techniques that leverage GIS technology are gaining traction for their ability to enhance crop yield and optimize resource usage. By providing detailed insights into soil conditions, weather patterns, and crop health, GIS controllers enable farmers to make data-driven decisions, thereby improving operational efficiency and reducing costs. Additionally, government initiatives aimed at promoting sustainable farming practices are further fueling the adoption of GIS technology in the agricultural sector.

Disaster management is another critical application area where GIS controllers are making a substantial impact. The increasing frequency of natural disasters such as hurricanes, floods, and earthquakes necessitates advanced planning and real-time response capabilities. GIS controllers help in mapping disaster-prone areas, predicting the impact of natural calamities, and coordinating emergency response efforts. This capability is invaluable for minimizing damage and saving lives. The growing focus on disaster preparedness and management is expected to drive the demand for GIS controllers in the coming years.

Regionally, North America holds a significant share of the GIS Controller market, driven by the high adoption rate of advanced technologies and substantial investments in smart city projects. The Asia Pacific region is expected to witness the highest growth rate, fueled by rapid urbanization, infrastructural development, and increasing government initiatives for digital transformation. Europe also presents substantial growth opportunities due to the rising focus on environmental sustainability and smart transportation systems.

Component Analysis

The GIS Controller market is segmented into three primary components: Hardware, Software, and Services. The hardware segment includes devices and equipment necessary for capturing and processing geospatial data, such as GPS units, sensors, and data collection devices. This segment is witnessing steady growth due to the increasing need for advanced and accurate data collection tools. The integration of AI and IoT with GIS hardware is further enhancing the capabilities of these devices, making them indispensable for various applications such as urban planning, agriculture, and disaster management.

In terms of software, GIS Controllers are equipped with specialized software for data analysis, mapping, and modeling. This segment is experiencing rapid growth due to the increasing demand for sophisticated analytical tools that can handle large datasets and provide real-time insights. Advanced GIS software solutions are being developed to offer more user-friendly interfaces and better integration with other enterprise systems, thereby enhancing their usability and effectiveness across different sectors. The rise of cloud-based GIS software is also contributing to the growth of this segment by offering scalable and cost-effective solutions.

The services segment comprises consultancy, implementation, and maintenance services essential for the effective deployment and utilization of GIS Controllers. As organizations increasingly adopt GIS technology, the demand for specialized services that can ensure smooth integration and optimal performance is rising. Professional services providers are offering customized solutions to meet the specific needs of different industries

This map displays the expected total accumulation of new snow over the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative snowfall data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the amount by time (incremental) or accumulation by time (cumulative) layers to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces gridded forecasts of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.snow.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

The dataset is a feature class showing the boundaries of 517 groundwater basins and subbasins as defined by the California Department of Water Resources as last modified by the Basin Boundary Emergency Regulation adopted on October 21, 2015. The file is in ESRI geodatabase format and is intended for use with compatible GIS software. Groundwater basins are represented as polygon features and designated on the basis of geological and hydrological conditions - usually the occurrence of alluvial or unconsolidated deposits. When practical, large basins are also subdivided by political boundaries, as in the Central Valley. Basins are named and numbered per the convention of the Department of Water Resources. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR GIS Spatial Data Standards. DWR makes no warranties or guarantees, either expressed or implied, as to the completeness, accuracy or correctness of the data, nor accepts or assumes any liability arising from or for any incorrect, incomplete or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov.

Location Intelligence Analytics Market Outlook

The global location intelligence analytics market size is projected to grow from USD 14.2 billion in 2023 to USD 31.7 billion by 2032, exhibiting a CAGR of approximately 9.4% during the forecast period. This robust growth is primarily driven by the increasing demand for spatial data and analytical tools across various industries to enhance decision-making processes and optimize business operations. As organizations increasingly recognize the value of location-based insights, they are investing in sophisticated analytics solutions that leverage geographic data to drive business outcomes and gain competitive advantages.

One of the primary growth factors for the location intelligence analytics market is the proliferation of IoT devices and the consequent surge in location-based data generation. With billions of connected devices expected to be operational in the coming years, the volume of location-specific data is set to explode. Businesses across industries are eager to harness this data to gain insights into consumer behavior, improve operational efficiency, and develop targeted marketing strategies. Moreover, advancements in AI and machine learning are enabling more sophisticated analysis of location data, providing deeper insights and predictive capabilities that are invaluable to enterprises.

Another significant driver for market growth is the growing adoption of smart city initiatives across the globe. Governments and municipalities are increasingly implementing location intelligence solutions to enhance urban planning, traffic management, and public safety. By leveraging location-based analytics, cities can optimize resource allocation, improve citizen services, and drive sustainable development. Furthermore, the integration of real-time data from various sources, such as sensors and social media, with geographic information systems (GIS) is facilitating more dynamic and responsive urban management systems, thus propelling the demand for location intelligence analytics.

The increasing emphasis on business intelligence and data-driven decision-making is also fueling the demand for location intelligence analytics. In today's competitive landscape, organizations are seeking to leverage every bit of data to gain actionable insights and stay ahead. Location intelligence provides a unique perspective by overlaying geographic data on traditional business data, offering a holistic view of trends and patterns. This capability is particularly valuable in sectors such as retail, transportation, and logistics, where location-based insights can directly impact revenue generation, cost savings, and customer satisfaction.

Regionally, North America is expected to hold the largest share of the location intelligence analytics market, driven by the presence of major technology companies and the rapid adoption of advanced analytics solutions across industries. The region's commitment to innovation and technological advancement is further supported by substantial investments in R&D activities. Additionally, Europe is anticipated to witness significant growth, influenced by stringent regulatory frameworks and a heightened focus on data privacy and security. In contrast, the Asia Pacific region is projected to demonstrate the highest growth rate, attributed to the rapid digital transformation and increasing investments in smart city projects across emerging economies like India and China.

Component Analysis

The location intelligence analytics market is broadly segmented into software and services. Software solutions are a critical component of this market, offering the necessary tools and platforms for collecting, analyzing, and visualizing geographic data. These software solutions are designed to process large volumes of spatial data, integrate various data sources, and provide users with intuitive and interactive interfaces for data exploration. The advancements in cloud computing and the increasing adoption of Software as a Service (SaaS) models are further driving the demand for location intelligence software, as they offer greater scalability, flexibility, and cost-effectiveness to organizations of all sizes.

Within the software segment, Geographic Information System (GIS) solutions are particularly prominent. GIS technology enables the mapping and analysis of spatial data, allowing users to visualize relationships, patterns, and trends in complex datasets. The ability to integrate GIS with other enterprise systems, such as Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP), enhances its ut

Archived on 20161130 and the name was change from i08_B118_CA_GroundwaterBasins to i08_B118_CA_GWaterBasins20161130. The dataset is a feature class showing the boundaries of 515 groundwater basins and subbasins as defined by the California Department of Water Resources (Bulletin 118, 2003). The file is in ESRI geodatabase format and is intended for use with compatible GIS software. Groundwater basins are represented as polygon features and designated on the basis of geological and hydrological conditions - usually the occurrence of alluvial or unconsolidated deposits. When practical, large basins are also subdivided by political boundaries, as in the Central Valley. Basins are named and numbered per the convention of the Department of Water Resources. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR GIS Spatial Data Standards. DWR makes no warranties or guarantees, either expressed or implied, as to the completeness, accuracy or correctness of the data, nor accepts or assumes any liability arising from or for any incorrect, incomplete or misleading subject data. The official DWR GIS Data Steward for this dataset is Brett Wyckoff, who may be contacted at 916-651-9283, or at brett.wyckoff@water.ca.gov. Comments, problems, improvements, updates, or suggestions should be forwarded to the official GIS Data Steward as available and appropriate.

We are applying Geographic Information Systems (GIS) to new orbital data sets for lunar resource assessment and the identification of past habitable environments on Mars. GIS has not previously been used for planetary resource assessment and its applicability to martian habitability is in its infancy. NASA has recognized the interest in this technology with the recent establishment of a NASA-wide Enterprise Agreement with ESRI, the developers of ArcGIS. Lunar resource assessment is recognized as a key to future exploration and sustainability. The recognition of martian habitable environments is a top priority goal of NASA's Mars Program.

This is a one-year project to apply a GIS analysis tool to new orbital data for lunar resource assessment and martian habitability identification. We used ArcGIS, the state-of-the-art software for mapping, integrating, and analysis of spatial data. We focused on the assessment of several regional lunar pyroclastic deposits and habitability analysis in the Chryse-Acidalia portion of the martian lowlands. This work expands upon a previous 3-year project enabled through IRD funds. As a direct result of this project three scientific papers have been published: Allen, C.C., Greenhagen, B.T., Donaldson Hanna, K.L., and Paige, D.P. (2012) Analysis of lunar pyroclastic deposit FeO abundances by LRO Diviner, Journal of Geophysical Research, 117, E00H28, doi:10.1029/2011JE003982. Oehler, D.Z. and Allen, C.C. (2012) Giant polygons and mounds in the lowlands of Mars: signatures of an ancient ocean ?, Astrobiology, 12, 1-15. Oehler, D.Z. and Allen, C.C. (2012) Focusing the search for biosignatures on Mars: Facies prediction with an example from Acidalia Planitia, in Sedimentary Geology of Mars (J.P. Grotzinger and R.E. Milliken, eds.), SEPM Special Publication No. 102, 183-194.

This is a collection of aerial digital orthophotos covering selected U.S. Forest Service and adjoining lands in the Southwest Region, encompassing Arizona and New Mexico. The data are presented in a time-enabled format, allowing the end-user to view available data year-by-year, or all available years at once, within a GIS system. The data encompass varying years from 2000 to the present, varying resolutions, and varying geographic extents, dependent upon available imagery as provided by the region. The data contains four bands, representing red, green, blue, and near-infrared wavelengths, making the data suitable for analysis using either a true-color band combination (red, green, blue) or using a false-color band combination (eg. near-infrared, red, green).The data contains an attribute table. Notable attributes that may be of interest to an end-user are:lowps: the pixel size of the source raster, given in meters.highps: the pixel size of the top-most pyramid for the raster, given in meters.beginyear: the first year of data acquisition for an individual dataset.endyear: the final year of data acquisition for an individual dataset.dataset_name: the name of the individual dataset within the collection.metadata: A URL link to a file on IIPP's Portal containing metadata pertaining to an individual dataset within the image service.resolution: The pixel size of the source raster, given in meters.A digital orthophoto is a georeferenced image prepared from aerial imagery, or other remotely-sensed data in which the displacement within the image due to sensor orientation and terrain relief has been removed. Orthophotos combine the characteristics of an image with the geometric qualities of a map. Orthoimages show ground features such as roads, buildings, and streams in their proper positions, without the distortion characteristic of unrectified aerial imagery. Digital orthoimages produced and used within the Forest Service are developed from imagery acquired through various national and regional image acquisition programs. The resulting orthoimages, also known as orthomaps, can be directly applied in remote sensing, GIS and mapping applications. They serve a variety of purposes, from interim maps to references for earth science investigations and analysis. Because of the orthographic property, an orthoimage can be used like a map for measurement of distances, angles, and areas with scale being constant everywhere. Also, they can be used as map layers in GIS or other computer-based manipulation, overlaying, and analysis. An orthoimage differs from a map in a manner of depiction of detail; on a map only selected detail is shown by conventional symbols, whereas on an orthoimage all details appear just as in original aerial or satellite imagery.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

Time Aware is a configurable app template that enables you visualize time enabled layers in a web map using a time slider. This is useful for displaying changes in data over time. Use CasesBuild a stand alone app that presents data changing through time.Build a time aware app and embed it within a story map journal or story map series to include time animation within your story.Configurable OptionsChoose a title, logo, and color scheme.Configure the ability for feature and location search.Customize the color and date time format of the time slider.Enable a legend, scalebar, share dialog, or about window.Supported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.Data RequirementsThis requires time aware data, to learn more see the configure time help topic. An existing time aware feature service can be consumed from this application, however in order to create your own time aware feature service you will either need ArcGIS Enterprise or an ArcGIS Online subscription.Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a map and choose to Create a Web AppOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.

Archived on 20161130 and the name was change from i08_B118_CA_GroundwaterBasins to i08_B118_CA_GWaterBasins20161130. The dataset is a feature class showing the boundaries of 515 groundwater basins and subbasins as defined by the California Department of Water Resources (Bulletin 118, 2003). The file is in ESRI geodatabase format and is intended for use with compatible GIS software. Groundwater basins are represented as polygon features and designated on the basis of geological and hydrological conditions - usually the occurrence of alluvial or unconsolidated deposits. When practical, large basins are also subdivided by political boundaries, as in the Central Valley. Basins are named and numbered per the convention of the Department of Water Resources. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR GIS Spatial Data Standards. DWR makes no warranties or guarantees, either expressed or implied, as to the completeness, accuracy or correctness of the data, nor accepts or assumes any liability arising from or for any incorrect, incomplete or misleading subject data. The official DWR GIS Data Steward for this dataset is Brett Wyckoff, who may be contacted at 916-651-9283, or at brett.wyckoff@water.ca.gov. Comments, problems, improvements, updates, or suggestions should be forwarded to the official GIS Data Steward as available and appropriate.