This 3D basemap presents OpenStreetMap (OSM) data and other data sources and is hosted by Esri using the OpenStreetMap style.Esri created the Places and Labels, Trees, and OpenStreetMap layers from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this new scene available to the OSM, GIS, and Developer communities.The Buildings layer (beta) presents open buildings data that has been processed and hosted by Esri. Esri created this buildings scene layer using data from the Overture Maps Foundation (OMF) which is supported by Meta, Microsoft, Amazon, TomTom, Esri and other members. Overture includes data from many sources, including OpenStreetMap (OSM). The 3D buildings layer will be updated each month with the latest version of Overture data, which includes the latest updates from OSM, Esri Community Maps, and other sources.Overture Maps is a collaborative project to create reliable, easy-to-use, and interoperable open map data. Member companies work to bring together the best available open datasets, and the resulting data can be downloaded from Microsoft Azure or Amazon S3. Esri is a member of the OMF project and is excited to make this 3D web scene available to the ArcGIS user community.

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Important Note: This item is in mature support as of June 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.The GEOGloWS ECMWF Streamflow System represents a daily 51-member ensemble streamflow forecast for over 1 million reaches across the globe. Gridded surface runoff, provided by the European Centre for Medium-range Weather Forecasting (ECMWF), is downscaled and routed to the streams using the Routing Application for Parallel computation of Discharge (RAPID). This animation layer shows the first 6-days of a 15-day forecast at 3-hr intervals. Additionally, a 40-yr historical simulation was produced based on ECMWF’s ERA5 dataset. From this historical simulation , return periods for each reach are calculated and used to color the stream segments when/where events exceed these thresholds. Credits: This forecast model was produced as part of the GEOGloWS Partnership with collaboration from BYU, ECMWF, esri, NOAA, NASA, SERVIR, USAID, ICIMOD, JRC, Copernicus, World Bank, and Microsoft Azure.What can you do with this layer?This map service is designed for fast data visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the forecast data sequentially using the time slider, which is set to three hour intervals by default by Enabling Time Animation. This layer type is not recommended for use in analysis.Revisions:Dec 15, 2020: Updated 'flowstyle' field values from color names: 'blue', 'yellow', 'purple', ... to Return Period values. This now reports '0', '2', '5', '10', '25', '50', and '100' indicating the forecasted return period. The symbology has also been extended to better depict the relevant state of each reach using these periods.

Map Data Services market has a significant presence globally, with a market size valued at XXX million in 2025. It is projected to expand at a CAGR of XX% during the forecast period, reaching XXX million by 2033. The growth of the market is primarily driven by the increasing demand for accurate and reliable map data for various applications such as navigation, location-based services, and urban planning. Additionally, the rise of autonomous vehicles and the adoption of advanced technologies like augmented reality and virtual reality are further contributing to the demand for map data. The key players in the Map Data Services market include Google, WikiMapia, Apple Maps, Here, Bing Maps, Navinfo, TomTom, Mapbox, Esri, AutoNavi, Baidu Apollo, Sanborn, Yandex, Azure Maps, OpenStreetMap, and ArcGIS. These companies offer a wide range of map data products and services to meet the diverse needs of various industries and consumers. The market is segmented by application, type, and region, providing a comprehensive overview of the industry landscape and competitive dynamics. North America, Europe, and Asia Pacific are the major regional segments of the market, with North America holding a significant share due to the presence of major technology companies and the adoption of advanced technologies.

The Saudi Arabian geospatial analytics market, valued at $400 million in 2025, is poised for significant growth, exhibiting a Compound Annual Growth Rate (CAGR) of 9.22% from 2025 to 2033. This expansion is driven by several key factors. Firstly, substantial investments in infrastructure development, including smart city initiatives and digital transformation across various sectors, are fueling the demand for sophisticated geospatial analytics solutions. Secondly, the Kingdom's strategic focus on Vision 2030, which emphasizes diversification and technological advancement, is creating a favorable environment for the adoption of geospatial technologies across sectors such as agriculture, utilities, defense, and real estate. The increasing availability of high-resolution satellite imagery, coupled with advancements in data analytics and artificial intelligence (AI), further enhances the market's growth trajectory. Government initiatives promoting data sharing and open data platforms are also playing a crucial role. Segmentation reveals that network analysis and geovisualization are experiencing the fastest growth, driven by their applications in urban planning, resource management, and emergency response. Key players, including established technology giants like Microsoft and Esri, as well as specialized geospatial firms, are actively competing in this dynamic market, contributing to innovation and service diversification. Despite the promising outlook, challenges remain. Data security and privacy concerns related to handling sensitive geospatial data pose a significant restraint. Furthermore, the lack of skilled professionals proficient in geospatial analytics and data interpretation could hinder market growth in the short term. Nevertheless, ongoing investments in education and training programs should mitigate this issue. The overall market landscape indicates substantial potential for growth, particularly in leveraging geospatial analytics for sustainable development and effective resource allocation across Saudi Arabia's diverse sectors. The forecast period, spanning from 2025 to 2033, projects substantial market expansion, driven by consistent technological innovation and governmental support for digital transformation. Recent developments include: May 2023: Microsoft introduced three new functions for geospatial analysis in Azure Data Explorer, geo_point_buffer, geo_line_buffer, and geo_polygon_buffer. These functions allow users to create polygonal buffers around geospatial points, lines, or polygons, respectively, and return the resulting geometry. Users can use these functions to perform spatial operations such as intersection, containment, distance, or proximity on user geospatial data or to visualize data on maps., October 2022: ROSHN, the Kingdom of Saudi Arabia's nationwide real estate developer, backed by the government's Public Investment Fund (PIF), supported government efforts to improve homeownership rates while delivering sophisticated living standards. The Saudi Arabia designer built communities that looked to the nation's heritage and evolving resident aspirations. To support its vision and ongoing regional projects, ROSHN signed a memorandum of understanding (MOU) with Esri, the global player in location intelligence., . Key drivers for this market are: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Potential restraints include: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Notable trends are: Geovisualization is Expected to Hold Significant Share of the Market.

The Location Analytics market is experiencing robust growth, projected to reach a significant size by 2033. A Compound Annual Growth Rate (CAGR) of 19.70% from 2019 to 2024 suggests a substantial increase in market value. This expansion is driven by several key factors. The increasing availability and affordability of location data from various sources, including GPS, mobile devices, and IoT sensors, fuels the market's growth. Businesses across diverse sectors are leveraging location analytics to gain actionable insights for improved operational efficiency, targeted marketing campaigns, and better customer experiences. Furthermore, advancements in data analytics technologies, such as AI and machine learning, are enabling more sophisticated location-based analysis, further driving market adoption. The emergence of cloud-based location analytics platforms enhances accessibility and scalability for businesses of all sizes. However, the market also faces certain challenges. Data privacy concerns and regulations, such as GDPR, pose significant restraints. The complexity of integrating various data sources and the need for skilled professionals to interpret and utilize the insights can also hinder wider market penetration. Despite these challenges, the long-term outlook for the location analytics market remains optimistic. The continued proliferation of connected devices and the rising demand for data-driven decision-making across industries will propel further growth. Market segmentation reveals strong performance across various sectors including retail, transportation and logistics, and government, with North America and Europe currently holding the largest market shares. The increasing adoption of location analytics in emerging economies like those within the Asia-Pacific region promises substantial future growth potential. The competitive landscape is characterized by a mix of established players, including Microsoft, Salesforce (through Tableau), and SAS, and emerging pure-play vendors like Google and TomTom, indicating a dynamic and innovative market. Recent developments include: November 2021 - Noogata announced the launch of its location analytics library. Building on the success of its existing e-commerce library, the location analytics library applies the power of Noogata's no code AI data analytics platform to physical locations for consumer packaged goods (CPG) brands., December 2020 - Microsoft unveiled a 'unified data governance service' as part of its Azure cloud platform, Azure Purview, that can discover and catalog all of an organization's data across all environments and locations.. Key drivers for this market are: Increasing Use of Spatial Data and Analytics in Various Industries, Growing Propensity of Consumers Toward Applications that Use Location Data. Potential restraints include: Increasing Use of Spatial Data and Analytics in Various Industries, Growing Propensity of Consumers Toward Applications that Use Location Data. Notable trends are: FMCG and E-Commerce Sector is Expected to Hold Significant Market Share.

Dataset of the green spaces of the City of Versailles. This dataset contains: - the trees of alignments - the trees located in the parks and gardens of the city - the remarkable trees - The parks and public gardens

Dataset of the green spaces of the City of Versailles. It contains: - the trees of alignments - the trees located in the parks and gardens of the city - the remarkable trees - The parks and public gardens

All the data concerning Versailles parking.

Layer of information referencing all the information concerning road works or closures on the territory.

Data concerning parking 15 minutes from Versailles.

Vegetation

This feature layer displays completed project locations as tracked by engineering staff at Leon County Public Works. This feature layer is a subset (view) of a parent hosted feature layer that is updated twice daily from a cloud (Azure) hosted SQL database that is administered by Leon County Applications team and maintained by engineering staff at Leon County Public Works.

This feature layer displays historical project locations as tracked by engineering staff at Leon County Public Works. This feature layer is a subset (view) of a parent hosted feature layer that is updated twice daily from a cloud (Azure) hosted SQL database that is administered by Leon County Applications team and maintained by engineering staff at Leon County Public Works.

Deep learning AI analysis of cardinal photosphere images for Anaheim unincorporated area in Orange County California (2018-338p2). The image locations (8 cardinal photospheres per location) containing results of image recognition by Azure cognitive vision model implementation.

The GEOGloWS ECMWF Streamflow System represents a daily 51-member ensemble streamflow forecast for over 1 million reaches across the globe. Gridded surface runoff, provided by the European Centre for Medium-range Weather Forecasting (ECMWF), is downscaled and routed to the streams using the Routing Application for Parallel computation of Discharge (RAPID). This animation layer shows the first 6-days of a 15-day forecast at 3-hr intervals. Additionally, a 40-yr historical simulation was produced based on ECMWF’s ERA5 dataset. From this historical simulation , return periods for each reach are calculated and used to color the stream segments when/where events exceed these thresholds.Credits: This forecast model was produced as part of the GEOGloWS Partnership with collaboration from BYU, ECMWF, esri, NOAA, NASA, SERVIR, USAID, ICIMOD, JRC, Copernicus, World Bank, and Microsoft Azure.What can you do with this layer?This map service is designed for fast data visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the forecast data sequentially using the time slider, which is set to three hour intervals by default by Enabling Time Animation. This layer type is not recommended for use in analysis.Revisions:Dec 15, 2020: Updated 'flowstyle' field values from color names: 'blue', 'yellow', 'purple', ... to Return Period values. This now reports '0', '2', '5', '10', '25', '50', and '100' indicating the forecasted return period. The symbology has also been extended to better depict the relevant state of each reach using these periods.