29 datasets found
  1. m

    Beijing SuperMap Software Co Ltd - Cash-and-Equivalents

    • macro-rankings.com
    csv, excel
    Updated Oct 1, 2025
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    macro-rankings (2025). Beijing SuperMap Software Co Ltd - Cash-and-Equivalents [Dataset]. https://www.macro-rankings.com/markets/stocks/300036-she/balance-sheet/cash-and-equivalents
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    csv, excelAvailable download formats
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    macro-rankings
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    china, Beijing
    Description

    Cash-and-Equivalents Time Series for Beijing SuperMap Software Co Ltd. Beijing SuperMap Software Co., Ltd. provides geographic information system and spatial intelligence software products and services in China and internationally. The company offers SuperMap iServer, which provides web services for geospatial big data; GeoAI, an 3D to support massive vector/raster data publishing; SuperMap iPortal that offers Web applications; and SuperMap iManager to monitor various GIS data storage, computing, service nodes, or other Web sites, as well as occupancy of hardware resources, map access hotspots, node health, and other indicators to achieve integrated operation and maintenance management of GIS system. It also provides Edge GIS Server for service publishing and real-time analysis and calculation, reduces response latency and bandwidth consumption, and reduces the pressure of cloud GIS center; Terminal GIS for Components, a large-scale full-component GIS development platform; SuperMap iDesktop and SuperMap iDesktopX, which are 2D and 3D integrated desktop GIS software platforms; SuperMap iExplorer3D, a 3D scene browsing software; SuperMap iMaritimeEditor, a cross-platform electronic chart production desktop software; and SuperMap ImageX Pro, a cross-platform remote sensing image processing desktop software. In addition, the company offers SuperMap iClient JavaScript, a GIS web terminal development platform; SuperMap iClient3D for WebGL, a 3D web terminal development platform; SuperMap iClient3D for WebGPU, a 3D GIS network client development platform; SuperMap iMobile, a mobile GIS software development platform based on map browsing, data collection, data analysis, and route navigation and combined with AR maps, mobile 3D, cloud collaboration, etc.; and SuperMap online GIS platform that integrates GIS data management, service management, data mining, and display. Beijing SuperMap Software Co., Ltd. was founded in 1997 and is based in Beijing, the People's Republic of China.

  2. m

    Beijing SuperMap Software Co Ltd - Other-Operating-Expenses

    • macro-rankings.com
    csv, excel
    Updated Oct 5, 2025
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    macro-rankings (2025). Beijing SuperMap Software Co Ltd - Other-Operating-Expenses [Dataset]. https://www.macro-rankings.com/markets/stocks/300036-she/income-statement/other-operating-expenses
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    csv, excelAvailable download formats
    Dataset updated
    Oct 5, 2025
    Dataset authored and provided by
    macro-rankings
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    china, Beijing
    Description

    Other-Operating-Expenses Time Series for Beijing SuperMap Software Co Ltd. Beijing SuperMap Software Co., Ltd. provides geographic information system and spatial intelligence software products and services in China and internationally. The company offers SuperMap iServer, which provides web services for geospatial big data; GeoAI, an 3D to support massive vector/raster data publishing; SuperMap iPortal that offers Web applications; and SuperMap iManager to monitor various GIS data storage, computing, service nodes, or other Web sites, as well as occupancy of hardware resources, map access hotspots, node health, and other indicators to achieve integrated operation and maintenance management of GIS system. It also provides Edge GIS Server for service publishing and real-time analysis and calculation, reduces response latency and bandwidth consumption, and reduces the pressure of cloud GIS center; Terminal GIS for Components, a large-scale full-component GIS development platform; SuperMap iDesktop and SuperMap iDesktopX, which are 2D and 3D integrated desktop GIS software platforms; SuperMap iExplorer3D, a 3D scene browsing software; SuperMap iMaritimeEditor, a cross-platform electronic chart production desktop software; and SuperMap ImageX Pro, a cross-platform remote sensing image processing desktop software. In addition, the company offers SuperMap iClient JavaScript, a GIS web terminal development platform; SuperMap iClient3D for WebGL, a 3D web terminal development platform; SuperMap iClient3D for WebGPU, a 3D GIS network client development platform; SuperMap iMobile, a mobile GIS software development platform based on map browsing, data collection, data analysis, and route navigation and combined with AR maps, mobile 3D, cloud collaboration, etc.; and SuperMap online GIS platform that integrates GIS data management, service management, data mining, and display. Beijing SuperMap Software Co., Ltd. was founded in 1997 and is based in Beijing, the People's Republic of China.

  3. Pharos Data

    • figshare.com
    Updated Nov 20, 2025
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    Thomas Scherr (2025). Pharos Data [Dataset]. http://doi.org/10.6084/m9.figshare.29817092.v2
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    text/x-script.pythonAvailable download formats
    Dataset updated
    Nov 20, 2025
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    Authors
    Thomas Scherr
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    IntroductionThis data repository includes the cleaned dataset for the Pharos application 2023-2024 data collection period (May 2023-March 2024). This dataset includes the full recurring network measurement (RNM), landmark (LM) datasets, as well as the county geographies used for the study catchment area. Also included in this dataset are the necessary software files to clean and visualize the collected data replicating the methods used in our published analysis.Setup and Execution Instructions for ReproductionPrerequisitesPython 3.9.16 (likely compatible, but untested with >3.7)pip (Python package installer)Files Included_main.py - Main execution script_clean_df.py - Data cleaning module_make_viz.py - Visualization module_clean_lms.csv - Landmark measurement data_clean_rnms.csv - Recurring network measurement data_Counties_WesternKenya.json - Geographic boundaries for Western Kenya counties_requirements.txt - Python package dependenciesInstallation and Execution1a. Create a virtual environment (using a virtual environment is recommended, but not required)python3 -m venv venv1b. Activate the virtual environment (using a virtual environment is recommended, but not required)source venv/bin/activate2. Install required packagespip install -r requirements.txt3. Run the analysispython _main.py4. Deactivate virtual environment when done (if used)deactivate

  4. Geographic Response Plan (GRP) Staging Areas

    • geodata.myfwc.com
    • data2-myfwc.opendata.arcgis.com
    • +2more
    Updated Jan 15, 2015
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    Florida Fish and Wildlife Conservation Commission (2015). Geographic Response Plan (GRP) Staging Areas [Dataset]. https://geodata.myfwc.com/datasets/geographic-response-plan-grp-staging-areas
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    Dataset updated
    Jan 15, 2015
    Dataset authored and provided by
    Florida Fish and Wildlife Conservation Commissionhttp://myfwc.com/
    Area covered
    Description

    For full FGDC metadata record, please click here.These data represent Staging and Response Locations collected by GPS for Mississippi, Alabama, and the Florida Panhandle prior to the Deepwater Horizon Oil Spill. The locations for the Peninsular portion of Florida, Georgia, South Carolina, Puerto Rico, and the US Virgin Islands have been compiled from numerous sources into this database schema and will at some later date (after Nov. 2010) be verified and validated by GPS. Staging and response locations were identified first by defining the types of locations that fit these descriptions. The broad categories were defined as Boat Ramp, Marina, Staging Area, or any combination of these. A marina may contain a boat ramp as well as a large parking lot with a seawall suitable for deploying equipment into the water. A staging area may contain just a waterfront park with access to the water, but no boat ramp or marina, but perhaps a dock or pier. These categories and attributes were used to design a specific database schema to collect information on these geographic features that could be used on a GPS-enabled field data collection device. Once the categories of information to be collected and the specifics of what types of information to be collected within each category were determined (the database schema), mobile devices were programmed to accomplish this task and area committee volunteers were used to conduct the field surveys. Field crews were given training on the devices. Guided by base maps identifying potential locations, they then traveled into the field to validate and collect specific GPS and attribute data on those locations. This was a cooperative effort between many federal, state, and local entities guided by FWC-FWRI that resulted in detailed and location-specific information on 366 staging area locations within Sector Mobile and a comprehensive GIS data set that is available on the DVD ROM and website as well a being used in the Geographic Response Plan Map Atlas production. Cyber-Tracker was the software used for this field data collection. Cyber-Tracker is a "shareware" software package developed as a data-capture tool designed for use in Environmental Conservation, Wildlife Biology and Disaster Relief. The software runs on numerous types of mobile devices and designing custom data capture processes for these devices requires no programming experience. Funded in large part by the European Commission and patroned by Harvard University, Cyber-Tracker Software has been a very valuable tool in the data collection efforts of this project. Cyber-Tracker Software can be found on the Internet at: http://www.cybertracker.co.za/.

  5. D

    Spatial Mapping Software Market Research Report 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Oct 1, 2025
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    Dataintelo (2025). Spatial Mapping Software Market Research Report 2033 [Dataset]. https://dataintelo.com/report/spatial-mapping-software-market
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    pptx, csv, pdfAvailable download formats
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Spatial Mapping Software Market Outlook



    According to our latest research, the global spatial mapping software market size reached USD 6.2 billion in 2024, reflecting the sector’s robust expansion across industries. The market is expected to grow at a CAGR of 14.1% from 2025 to 2033, reaching an estimated USD 19.3 billion by 2033. The primary growth factor propelling this market is the increasing adoption of spatial data analytics and geospatial intelligence across urban planning, environmental monitoring, and asset management sectors, as organizations strive for enhanced decision-making and operational efficiency.




    One of the most significant growth drivers for the spatial mapping software market is the rapid urbanization witnessed globally. Governments and private entities are investing heavily in smart city initiatives, which require advanced mapping tools for infrastructure planning, traffic management, and resource allocation. The integration of spatial mapping software with IoT devices and sensors is enabling real-time data collection and visualization, thus streamlining urban planning processes. Moreover, the growing need for sustainable development and efficient land use is pushing city planners to leverage spatial mapping solutions for accurate geospatial analysis, zoning, and resource optimization. This trend is expected to continue, with urban centers increasingly relying on spatial intelligence to tackle challenges related to population growth, environmental sustainability, and public safety.




    Technological advancements in artificial intelligence, machine learning, and cloud computing are further accelerating the growth of the spatial mapping software market. Modern mapping platforms now offer sophisticated features such as 3D visualization, predictive analytics, and automated data processing, which significantly enhance the value proposition for end-users. These innovations are not only improving the accuracy and usability of spatial data but are also making it accessible to non-technical users through intuitive interfaces and seamless integrations with enterprise resource planning (ERP) and geographic information system (GIS) platforms. Additionally, the proliferation of mobile devices and high-speed internet connectivity has made spatial mapping tools more versatile, enabling field workers and remote teams to access, update, and share geospatial information in real time.




    Another critical factor contributing to the market’s expansion is the rising importance of spatial mapping software in disaster management and environmental monitoring. Governments, NGOs, and emergency response teams are increasingly utilizing these platforms to assess risks, plan evacuations, and coordinate relief efforts in the wake of natural disasters such as floods, earthquakes, and wildfires. Spatial mapping software enables the integration of diverse datasets, including satellite imagery, sensor data, and historical records, to create comprehensive risk maps and predictive models. This capability is invaluable for proactive disaster preparedness and rapid response, helping to minimize loss of life and property. Similarly, environmental agencies are leveraging these tools to monitor deforestation, track wildlife movements, and manage natural resources, further boosting market demand.




    From a regional perspective, North America currently leads the spatial mapping software market, driven by substantial investments in smart infrastructure, advanced technological adoption, and a mature ecosystem of geospatial solution providers. Europe follows closely, with strong government support for digital transformation in urban planning and environmental sustainability. The Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, infrastructure development, and increasing adoption of smart city solutions in countries like China, India, and Japan. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth, supported by government initiatives for modernization and improved disaster management capabilities. These regional dynamics are shaping the competitive landscape and driving innovation in the global spatial mapping software market.



    Component Analysis



    The spatial mapping software market is segmented by component into software and services. The software segment dominates the market, accounting for the largest share due to the widespread adoption of propriet

  6. a

    Alaska 2023 Forest Health Flightlines

    • gis.data.alaska.gov
    • data-soa-dnr.opendata.arcgis.com
    • +3more
    Updated Mar 6, 2025
    + more versions
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    Alaska Department of Natural Resources ArcGIS Online (2025). Alaska 2023 Forest Health Flightlines [Dataset]. https://gis.data.alaska.gov/datasets/alaska-2023-forest-health-flightlines
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    Dataset updated
    Mar 6, 2025
    Dataset authored and provided by
    Alaska Department of Natural Resources ArcGIS Online
    Area covered
    Description

    This forest health dataset includes flightlines from 2023. Along these flightlines, surveyors from the Alaska Division of Forestry & Fire Protection and USDA Forest Service - Forest Health Protection document insect, disease, and abiotic damage in the forest from about 1000 feet altitude using a digital mobile sketch-mapping tablet and software. The aerial survey covers about 15% of the forests statewide each year. Note that much of the forest damage documented during these surveys does not typically result in tree or shrub mortality. Aerial survey data disclaimer: USDA Forest Service - Forest Health Protection and the Alaska Division of Forestry & Fire Protection make every attempt to accurately identify and locate forest damage. The data is offered "as is".

  7. m

    Beijing SuperMap Software Co Ltd - Retained-Earnings

    • macro-rankings.com
    csv, excel
    Updated Aug 16, 2025
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    macro-rankings (2025). Beijing SuperMap Software Co Ltd - Retained-Earnings [Dataset]. https://www.macro-rankings.com/markets/stocks/300036-she/balance-sheet/retained-earnings
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    csv, excelAvailable download formats
    Dataset updated
    Aug 16, 2025
    Dataset authored and provided by
    macro-rankings
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    china, Beijing
    Description

    Retained-Earnings Time Series for Beijing SuperMap Software Co Ltd. Beijing SuperMap Software Co., Ltd. provides geographic information system and spatial intelligence software products and services in China and internationally. The company offers SuperMap iServer, which provides web services for geospatial big data; GeoAI, an 3D to support massive vector/raster data publishing; SuperMap iPortal that offers Web applications; and SuperMap iManager to monitor various GIS data storage, computing, service nodes, or other Web sites, as well as occupancy of hardware resources, map access hotspots, node health, and other indicators to achieve integrated operation and maintenance management of GIS system. It also provides Edge GIS Server for service publishing and real-time analysis and calculation, reduces response latency and bandwidth consumption, and reduces the pressure of cloud GIS center; Terminal GIS for Components, a large-scale full-component GIS development platform; SuperMap iDesktop and SuperMap iDesktopX, which are 2D and 3D integrated desktop GIS software platforms; SuperMap iExplorer3D, a 3D scene browsing software; SuperMap iMaritimeEditor, a cross-platform electronic chart production desktop software; and SuperMap ImageX Pro, a cross-platform remote sensing image processing desktop software. In addition, the company offers SuperMap iClient JavaScript, a GIS web terminal development platform; SuperMap iClient3D for WebGL, a 3D web terminal development platform; SuperMap iClient3D for WebGPU, a 3D GIS network client development platform; SuperMap iMobile, a mobile GIS software development platform based on map browsing, data collection, data analysis, and route navigation and combined with AR maps, mobile 3D, cloud collaboration, etc.; and SuperMap online GIS platform that integrates GIS data management, service management, data mining, and display. Beijing SuperMap Software Co., Ltd. was founded in 1997 and is based in Beijing, the People's Republic of China.

  8. a

    Alaska 2024 Forest Health Damage

    • gis.data.alaska.gov
    • data-soa-dnr.opendata.arcgis.com
    • +1more
    Updated Mar 6, 2025
    + more versions
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    Alaska Department of Natural Resources ArcGIS Online (2025). Alaska 2024 Forest Health Damage [Dataset]. https://gis.data.alaska.gov/datasets/SOA-DNR::alaska-forest-health-aerial-survey?layer=1
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    Dataset updated
    Mar 6, 2025
    Dataset authored and provided by
    Alaska Department of Natural Resources ArcGIS Online
    Area covered
    Description

    This forest health dataset includes both polygon and point data from 2024. Points have a buffered area based on tree number. Surveyors from the Alaska Division of Forestry & Fire Protection and USDA Forest Service - Forest Health Protection document insect, disease, and abiotic damage in the forest from about 1000 feet altitude using a digital mobile sketch-mapping tablet and software. The aerial survey covers about 15% of the forests statewide each year. Note that much of the forest damage documented during these surveys does not typically result in tree or shrub mortality. Aerial survey data disclaimer: USDA Forest Service - Forest Health Protection and the Alaska Division of Forestry & Fire Protection make every attempt to accurately identify and locate forest damage. The data is offered "as is".

  9. c

    Data from: City Of Birmingham

    • catalog.civicdataecosystem.org
    Updated Sep 2, 2011
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    (2011). City Of Birmingham [Dataset]. https://catalog.civicdataecosystem.org/dataset/city-of-birmingham
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    Dataset updated
    Sep 2, 2011
    Area covered
    Birmingham
    Description

    Birmingham, Alabama Mayor William A. Bell signed an executive order to improve the way citizens interact with their government. The new law allowed the creation of this online open data portal to increase transparency and accountability in Birmingham by making key information easily accessible and usable to both city officials and citizens. Click here to view the Birmingham Open Data Policy. You may use the search bar at the top of the page to find data. Once you find a dataset you would like to download, select the data and view the available download options. Datasets can also be filtered to display only the features of the dataset that you are interested in for download. Data is offered for download in several formats. Spatial and tabular data formats (CSV, KML, shapefile, and JSON) are available for use in GIS and other applications. Mobile users may require additional software to view downloaded data. To edit a shapefile on an iOS device, users will need to unzip the file with an app such as iZip and then open the file in a viewer/editor such as iGIS. By using data made available through this site, the user agrees to all the conditions stated in the following paragraphs as well as the terms and conditions described under the City of Birmingham homepage. The data made available has been modified for use from its original source, which is the City of Birmingham. The City of Birmingham makes no claims as to the completeness, accuracy, timeliness, or content of any data contained in this application; makes no representation of any kind, including, but not limited to, warranty of the accuracy or fitness for a particular use; nor are any such warranties to be implied or inferred with respect to the information or data furnished herein. The data is subject to change as modifications and updates are complete. It is understood that the information contained in the site is being used at one's own risk. The City of Birmingham reserves the right to discontinue providing any or all of the data feeds at any time and to require the termination of any and all displaying, distributing or otherwise using any or all of the data for any reason including, without limitation, your violation of any provision of these Terms of Use. If you have questions, suggestions, requests or any other feedback, please contact or email at [email protected]

  10. C

    Replication Data for: Proximidad y mixticidad urbana para una ciudad...

    • dataverse.csuc.cat
    csv +3
    Updated May 27, 2025
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    Enric Villavieja-Martinez; Enric Villavieja-Martinez; Carles Crosas Armengol; Carles Crosas Armengol; Eulalia Maria Gomez Escoda; Eulalia Maria Gomez Escoda (2025). Replication Data for: Proximidad y mixticidad urbana para una ciudad saludable. Criterios y herramientas para la evaluación y promoción de la mezcla de actividades en áreas metropolitanas compactas [METRO·MIX] [Dataset]. http://doi.org/10.34810/data2115
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    tsv(1097), tsv(7718), tsv(2177931), tsv(64659), tsv(569548), tsv(1512), text/comma-separated-values(1013), text/comma-separated-values(947), tsv(33079), tsv(727), tsv(13600), tsv(53477), text/comma-separated-values(78946), tsv(65077), tsv(49244), txt(16700), tsv(59441), csv(1767179), tsv(238179), tsv(20921), tsv(132407), text/comma-separated-values(708), tsv(59908), tsv(625), tsv(24972)Available download formats
    Dataset updated
    May 27, 2025
    Dataset provided by
    CORA.Repositori de Dades de Recerca
    Authors
    Enric Villavieja-Martinez; Enric Villavieja-Martinez; Carles Crosas Armengol; Carles Crosas Armengol; Eulalia Maria Gomez Escoda; Eulalia Maria Gomez Escoda
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Time period covered
    2019 - 2023
    Area covered
    Galicia, Spain, A Coruña, Barcelona, Catalonia, Spain, Andalusia, Málaga, Spain, Madrid, Spain
    Dataset funded by
    Agencia Estatal de Investigación
    Description

    This dataset supports the METRO·MIX research project, which investigates urban proximity and land-use mix as foundational criteria for promoting healthier, more compact metropolitan areas. The data are organized into three main components: General Data, City Data, and 15-Minute City Data, covering the Spanish cities of Barcelona, Madrid, Málaga, and A Coruña between 2021 and 2023. The General Data includes harmonized national-scale information derived from cadastral records and demographic statistics provided by the Spanish Land Registry and the National Institute of Statistics (INE), with variables such as land use categories, building function, population structure, and socioeconomic indicators. The City Data component provides spatially disaggregated information at the census section level for each city, integrating official records with field-collected data on urban functions. This data was processed to derive indices such as the Residential/Non-Residential Balance (RNR Index) and the Land Use Mix Index (LUM Index), facilitating comparative urban analysis. The 15-Minute City Data focuses on neighborhood-scale accessibility and functional diversity, particularly in Barcelona. It incorporates high-resolution, geolocated data on ground-floor commercial activities, categorized and verified through in-situ fieldwork and a custom-built mobile application. All datasets were processed using GIS software (QGIS 3.32) and validated through a multi-step quality control process, including spatial checks, field verification, and harmonization protocols. The dataset is structured in open formats (CSV, GeoJSON, Shapefiles) and intended to support further analysis in urban planning, geography, and public health research.

  11. a

    Alaska Region 10 ADS Dataset 2022 Public view

    • usfs.hub.arcgis.com
    Updated Feb 2, 2023
    + more versions
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    U.S. Forest Service (2023). Alaska Region 10 ADS Dataset 2022 Public view [Dataset]. https://usfs.hub.arcgis.com/maps/usfs::alaska-region-10-ads-dataset-2022-public-view
    Explore at:
    Dataset updated
    Feb 2, 2023
    Dataset authored and provided by
    U.S. Forest Service
    Area covered
    Description

    This forest health dataset includes both polygon and point data from the current year . Points have a buffered area based on tree number. Surveyors from the Alaska Division of Forestry & Fire Protection and USDA Forest Service - Forest Health Protection document insect, disease, and abiotic damage in the forest from about 1000 feet altitude using a digital mobile sketch-mapping tablet and software. The aerial survey covers about 15% of the forests statewide each year. Note that much of the forest damage documented during these surveys does not typically result in tree or shrub mortality. Aerial survey data disclaimer: USDA Forest Service - Forest Health Protection and the Alaska Division of Forestry make every attempt to accurately identify and locate foreset damage. The data is offered 'as is'.

  12. D

    High-Clearance Route Database Platform Market Research Report 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 30, 2025
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    Dataintelo (2025). High-Clearance Route Database Platform Market Research Report 2033 [Dataset]. https://dataintelo.com/report/high-clearance-route-database-platform-market
    Explore at:
    pptx, pdf, csvAvailable download formats
    Dataset updated
    Sep 30, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    High-Clearance Route Database Platform Market Outlook



    According to our latest research, the global high-clearance route database platform market size in 2024 stands at USD 1.34 billion, with a robust compound annual growth rate (CAGR) of 12.7% expected throughout the forecast period. By 2033, the market is anticipated to reach an impressive USD 3.92 billion, reflecting the sector’s dynamic expansion. This growth is primarily driven by the increasing demand for intelligent routing solutions in sectors such as logistics, transportation, and infrastructure management, where the safe and efficient movement of oversized and high-clearance vehicles is a critical operational requirement.




    The growth trajectory of the high-clearance route database platform market is underpinned by the rapid digital transformation occurring in logistics and transportation industries worldwide. As supply chains become more complex and urbanization accelerates, organizations are investing in advanced route planning platforms that can accommodate the unique requirements of high-clearance vehicles. The proliferation of smart city initiatives and the integration of Internet of Things (IoT) sensors in infrastructure have further amplified the need for real-time, accurate, and adaptable route databases. These platforms enable operators to avoid costly delays, infrastructure damage, and safety risks by providing up-to-date clearance information, restrictions, and optimal routing alternatives.




    Another significant driver is the growing emphasis on public safety and regulatory compliance. Government agencies and transportation authorities are mandating stricter adherence to clearance regulations, especially as the frequency of oversized cargo movements increases. High-clearance route database platforms play a pivotal role in ensuring compliance by offering automated checks, historical data analysis, and integration with permit management systems. The rise in emergency service requirements, such as fire trucks and utility vehicles needing rapid access through urban and rural environments, has also spurred adoption across new end-user segments. This trend is expected to continue as urban infrastructure becomes denser and more challenging to navigate.




    Technological advancements within the market are propelling further innovation and adoption. The integration of artificial intelligence (AI), machine learning, and predictive analytics into high-clearance route database platforms is enabling real-time route optimization and proactive maintenance planning. Cloud-based deployment models are making these solutions more accessible to a broader range of organizations, from large-scale government agencies to smaller transportation companies. The convergence of high-definition mapping, GIS technologies, and mobile connectivity is driving a new era of intelligent, data-driven route management that supports both operational efficiency and sustainability goals.




    From a regional perspective, North America currently leads the market, benefiting from a well-established transportation infrastructure, high levels of digital adoption, and stringent regulatory frameworks. Europe follows closely, driven by cross-border logistics, infrastructure modernization projects, and a strong focus on safety and compliance. The Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, expanding logistics networks, and significant investments in smart city and infrastructure development. Latin America and the Middle East & Africa, while smaller in market share, are witnessing increasing interest as governments and enterprises recognize the value of advanced routing solutions for oversized and high-clearance vehicles.



    Component Analysis



    The component segment of the high-clearance route database platform market is divided into software, hardware, and services, each playing a crucial role in the overall ecosystem. Software solutions form the backbone of these platforms, providing the core functionalities required for route planning, clearance verification, and data analytics. Advanced software modules leverage AI and machine learning to deliver real-time route optimization, predictive maintenance alerts, and integration with third-party logistics and fleet management systems. The demand for customizable and scalable software solutions is rising as organizations seek to tailo

  13. Random intercept variances and model fit statistics comparison of multilevel...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Nov 18, 2024
    + more versions
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    Aklilu Habte Hailegebireal; Habtamu Mellie Bizuayehu; Yordanos Sisay Asgedom; Jira Wakoya Feyisa (2024). Random intercept variances and model fit statistics comparison of multilevel mixed effect logistic regression model. [Dataset]. http://doi.org/10.1371/journal.pone.0313893.t006
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    xlsAvailable download formats
    Dataset updated
    Nov 18, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Aklilu Habte Hailegebireal; Habtamu Mellie Bizuayehu; Yordanos Sisay Asgedom; Jira Wakoya Feyisa
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Random intercept variances and model fit statistics comparison of multilevel mixed effect logistic regression model.

  14. Feed the Future Senegal: Naatal Mbay 2015-2019

    • catalog.data.gov
    Updated Jul 23, 2019
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    USAID (2019). Feed the Future Senegal: Naatal Mbay 2015-2019 [Dataset]. https://catalog.data.gov/ro/dataset/feed-the-future-senegal-naatal-mbay-2015-2019
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    Dataset updated
    Jul 23, 2019
    Dataset provided by
    United States Agency for International Developmenthttp://usaid.gov/
    Area covered
    Senegal
    Description

    The datasets contained in this data asset were generated through the Feed the Future Senegal Naatal May project, an agricultural market systems development project from 2015-2019. Naatal Mbay worked with 120+ producer organizations across the irrigated rice, rainfed rice, maize, and millet value chains though a data collection system for monitoring and evaluation data that relied on engaging farmers and field agents of partner producer networks as active members of a data collection/feedback loop. Producer networks were trained to collect data and to use it to better plan and manage their own activities while also providing data for the project performance indicators. The producer networks used a set of data management tools established and validated through a close participatory process during the predecessor Projet Croissance Economique project with technical team and partner networks across different value chains. Excel spreadsheets, GIS software, and a CommCare-based mobile data collection application were used to generate agricultural input (fertilizer, seeds) requirements and crop forecasts, track field activities, map farms, and organize harvests. The databases contain information on the producer members, partner producer organizations of the project, monitoring of agronomic activities of plots, financing, marketing, and rainfall data. The databases were audited by Naatal Mbay’s M&E staff and aggregated for the project's key performance indicators.

  15. f

    The weighted proportion of receipt of BPCR messages across selected...

    • figshare.com
    • plos.figshare.com
    xls
    Updated Dec 8, 2023
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    Aklilu Habte; Samuel Hailegebreal; Tamirat Melis; Dereje Haile (2023). The weighted proportion of receipt of BPCR messages across selected characteristics of the respondents in Ethiopia, EDHS 2016. [Dataset]. http://doi.org/10.1371/journal.pone.0295744.t002
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    xlsAvailable download formats
    Dataset updated
    Dec 8, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Aklilu Habte; Samuel Hailegebreal; Tamirat Melis; Dereje Haile
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    The weighted proportion of receipt of BPCR messages across selected characteristics of the respondents in Ethiopia, EDHS 2016.

  16. m

    Beijing SuperMap Software Co Ltd - Depreciation

    • macro-rankings.com
    csv, excel
    Updated Oct 13, 2025
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    macro-rankings (2025). Beijing SuperMap Software Co Ltd - Depreciation [Dataset]. https://www.macro-rankings.com/markets/stocks/300036-she/cashflow-statement/depreciation
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    excel, csvAvailable download formats
    Dataset updated
    Oct 13, 2025
    Dataset authored and provided by
    macro-rankings
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    china, Beijing
    Description

    Depreciation Time Series for Beijing SuperMap Software Co Ltd. Beijing SuperMap Software Co., Ltd. provides geographic information system and spatial intelligence software products and services in China and internationally. The company offers SuperMap iServer, which provides web services for geospatial big data; GeoAI, an 3D to support massive vector/raster data publishing; SuperMap iPortal that offers Web applications; and SuperMap iManager to monitor various GIS data storage, computing, service nodes, or other Web sites, as well as occupancy of hardware resources, map access hotspots, node health, and other indicators to achieve integrated operation and maintenance management of GIS system. It also provides Edge GIS Server for service publishing and real-time analysis and calculation, reduces response latency and bandwidth consumption, and reduces the pressure of cloud GIS center; Terminal GIS for Components, a large-scale full-component GIS development platform; SuperMap iDesktop and SuperMap iDesktopX, which are 2D and 3D integrated desktop GIS software platforms; SuperMap iExplorer3D, a 3D scene browsing software; SuperMap iMaritimeEditor, a cross-platform electronic chart production desktop software; and SuperMap ImageX Pro, a cross-platform remote sensing image processing desktop software. In addition, the company offers SuperMap iClient JavaScript, a GIS web terminal development platform; SuperMap iClient3D for WebGL, a 3D web terminal development platform; SuperMap iClient3D for WebGPU, a 3D GIS network client development platform; SuperMap iMobile, a mobile GIS software development platform based on map browsing, data collection, data analysis, and route navigation and combined with AR maps, mobile 3D, cloud collaboration, etc.; and SuperMap online GIS platform that integrates GIS data management, service management, data mining, and display. Beijing SuperMap Software Co., Ltd. was founded in 1997 and is based in Beijing, the People's Republic of China.

  17. m

    Beijing SuperMap Software Co Ltd - Fixed-Asset-Turnover

    • macro-rankings.com
    csv, excel
    Updated Aug 16, 2025
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    macro-rankings (2025). Beijing SuperMap Software Co Ltd - Fixed-Asset-Turnover [Dataset]. https://www.macro-rankings.com/markets/stocks/300036-she/key-financial-ratios/activity/fixed-asset-turnover
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    csv, excelAvailable download formats
    Dataset updated
    Aug 16, 2025
    Dataset authored and provided by
    macro-rankings
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    china, Beijing
    Description

    Fixed-Asset-Turnover Time Series for Beijing SuperMap Software Co Ltd. Beijing SuperMap Software Co., Ltd. provides geographic information system and spatial intelligence software products and services in China and internationally. The company offers SuperMap iServer, which provides web services for geospatial big data; GeoAI, an 3D to support massive vector/raster data publishing; SuperMap iPortal that offers Web applications; and SuperMap iManager to monitor various GIS data storage, computing, service nodes, or other Web sites, as well as occupancy of hardware resources, map access hotspots, node health, and other indicators to achieve integrated operation and maintenance management of GIS system. It also provides Edge GIS Server for service publishing and real-time analysis and calculation, reduces response latency and bandwidth consumption, and reduces the pressure of cloud GIS center; Terminal GIS for Components, a large-scale full-component GIS development platform; SuperMap iDesktop and SuperMap iDesktopX, which are 2D and 3D integrated desktop GIS software platforms; SuperMap iExplorer3D, a 3D scene browsing software; SuperMap iMaritimeEditor, a cross-platform electronic chart production desktop software; and SuperMap ImageX Pro, a cross-platform remote sensing image processing desktop software. In addition, the company offers SuperMap iClient JavaScript, a GIS web terminal development platform; SuperMap iClient3D for WebGL, a 3D web terminal development platform; SuperMap iClient3D for WebGPU, a 3D GIS network client development platform; SuperMap iMobile, a mobile GIS software development platform based on map browsing, data collection, data analysis, and route navigation and combined with AR maps, mobile 3D, cloud collaboration, etc.; and SuperMap online GIS platform that integrates GIS data management, service management, data mining, and display. Beijing SuperMap Software Co., Ltd. was founded in 1997 and is based in Beijing, the People's Republic of China.

  18. List of potential predictors of HIV/AID-KAB extracted from the EDHS 2016...

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 4, 2024
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    Aklilu Habte; Habtamu Mellie Bizuayehu; Yosef Haile; Daniel Niguse Mamo; Yordanos Sisay Asgedom (2024). List of potential predictors of HIV/AID-KAB extracted from the EDHS 2016 report. [Dataset]. http://doi.org/10.1371/journal.pone.0304982.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Aklilu Habte; Habtamu Mellie Bizuayehu; Yosef Haile; Daniel Niguse Mamo; Yordanos Sisay Asgedom
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    List of potential predictors of HIV/AID-KAB extracted from the EDHS 2016 report.

  19. a

    Alaska 2021 Forest Health Flightlines

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • forestrymaps-soa-dnr.hub.arcgis.com
    Updated Mar 6, 2025
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    Alaska Department of Natural Resources ArcGIS Online (2025). Alaska 2021 Forest Health Flightlines [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/SOA-DNR::alaska-forest-health-aerial-survey?layer=6
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    Dataset updated
    Mar 6, 2025
    Dataset authored and provided by
    Alaska Department of Natural Resources ArcGIS Online
    Area covered
    Description

    This forest health dataset includes both polygon and point data from 2021. Points have a buffered area based on tree number. Surveyors from the Alaska Division of Forestry & Fire Protection and USDA Forest Service - Forest Health Protection document insect, disease, and abiotic damage in the forest from about 1000 feet altitude using a digital mobile sketch-mapping tablet and software. The aerial survey covers about 15% of the forests statewide each year. Note that much of the forest damage documented during these surveys does not typically result in tree or shrub mortality. Aerial survey data disclaimer: USDA Forest Service - Forest Health Protection and the Alaska Division of Forestry & Fire Protection make every attempt to accurately identify and locate forest damage from the air. A very small percentage of the mapped data can be ground-checked and it is possible that errors in the data exist. These data are offered 'as is'.

  20. m

    Hexagon AB (publ) - Inventory-Turnover

    • macro-rankings.com
    csv, excel
    Updated Mar 18, 2025
    + more versions
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    macro-rankings (2025). Hexagon AB (publ) - Inventory-Turnover [Dataset]. https://www.macro-rankings.com/Markets/Stocks/HEXA-B-ST/Inventory-Turnover
    Explore at:
    csv, excelAvailable download formats
    Dataset updated
    Mar 18, 2025
    Dataset authored and provided by
    macro-rankings
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    sweden
    Description

    Inventory-Turnover Time Series for Hexagon AB (publ). Hexagon AB (publ) provides geospatial and industrial enterprise solutions worldwide. It operates in Manufacturing Intelligence, Asset Lifecycle Intelligence, Geosystems, Autonomous Solutions, and Safety, structure & Geospatial segments. The company offers analysis and management, machine control, embedded electronics, monitoring, and planning and optimization solutions to agriculture division; design and visualization, asset lifecycle information and outage management, engineering and schematics, enterprise project performance, smart digital, utility GIS, OT/ICS cyber security, operation and maintenance, procurement, fabrication, and construction services for asset lifecycle intelligence division; anti-jam systems, correction services, GNSS and SMART antennas, GNSS/INS receivers and post processing, offroad anatomy, resilience and integrity technology, and visualization software for autonomy and positioning division; and AEC and survey software, airborne, digital realities platform, documentation and verification, geospatial content, machine control, laser scanning and measurement tools, levels, total stations, monitoring, document and verification solutions, detection, GNSS, and mobile mapping system to geosystem division. It also provides CAD CAM and CAE software, CNC simulation and computed tomography software, measurement and inspection hardware and software, manufacturing project management, digital transformation for manufacturing, environmental health and safety, and quality management systems to manufacturing intelligence division; and evaluation, planning and design, drill and blast, load and haul, survey and monitoring, processing, reclamation, safety, autonomous operations, and insights services to mining division. In addition, the company offers GIS, imagery analysis and data management, collaboration, government, transportation, and geospatial and public safety platform solutions. The company was founded in 1975 and is based in Stockholm, Sweden.

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macro-rankings (2025). Beijing SuperMap Software Co Ltd - Cash-and-Equivalents [Dataset]. https://www.macro-rankings.com/markets/stocks/300036-she/balance-sheet/cash-and-equivalents

Beijing SuperMap Software Co Ltd - Cash-and-Equivalents

Beijing SuperMap Software Co Ltd - Cash-and-Equivalents - Historical Dataset (6/30/2018/6/30/2025)

Explore at:
csv, excelAvailable download formats
Dataset updated
Oct 1, 2025
Dataset authored and provided by
macro-rankings
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
china, Beijing
Description

Cash-and-Equivalents Time Series for Beijing SuperMap Software Co Ltd. Beijing SuperMap Software Co., Ltd. provides geographic information system and spatial intelligence software products and services in China and internationally. The company offers SuperMap iServer, which provides web services for geospatial big data; GeoAI, an 3D to support massive vector/raster data publishing; SuperMap iPortal that offers Web applications; and SuperMap iManager to monitor various GIS data storage, computing, service nodes, or other Web sites, as well as occupancy of hardware resources, map access hotspots, node health, and other indicators to achieve integrated operation and maintenance management of GIS system. It also provides Edge GIS Server for service publishing and real-time analysis and calculation, reduces response latency and bandwidth consumption, and reduces the pressure of cloud GIS center; Terminal GIS for Components, a large-scale full-component GIS development platform; SuperMap iDesktop and SuperMap iDesktopX, which are 2D and 3D integrated desktop GIS software platforms; SuperMap iExplorer3D, a 3D scene browsing software; SuperMap iMaritimeEditor, a cross-platform electronic chart production desktop software; and SuperMap ImageX Pro, a cross-platform remote sensing image processing desktop software. In addition, the company offers SuperMap iClient JavaScript, a GIS web terminal development platform; SuperMap iClient3D for WebGL, a 3D web terminal development platform; SuperMap iClient3D for WebGPU, a 3D GIS network client development platform; SuperMap iMobile, a mobile GIS software development platform based on map browsing, data collection, data analysis, and route navigation and combined with AR maps, mobile 3D, cloud collaboration, etc.; and SuperMap online GIS platform that integrates GIS data management, service management, data mining, and display. Beijing SuperMap Software Co., Ltd. was founded in 1997 and is based in Beijing, the People's Republic of China.

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