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| National Geographic Information System | |
|---|---|
| Name | National Geographic Information System |
| Type | Geographic information system |
National Geographic Information System
The National Geographic Information System is a comprehensive spatial data infrastructure used for mapping, analysis, and dissemination of geospatial information across national and transnational programs. It integrates datasets from agencies such as the United States Geological Survey, Ordnance Survey, National Aeronautics and Space Administration, European Space Agency, and United Nations bodies to support planning, conservation, disaster response, and research. The system underpins initiatives by institutions like the World Bank, Food and Agriculture Organization, United Nations Development Programme, Intergovernmental Panel on Climate Change, and regional organizations including the African Union and Association of Southeast Asian Nations.
The system aggregates raster and vector data produced by organizations such as National Oceanic and Atmospheric Administration, US Forest Service, Environmental Protection Agency, Geological Survey of Canada, Geoscience Australia, and the Japan Aerospace Exploration Agency. It serves stakeholders including the National Park Service, Smithsonian Institution, International Union for Conservation of Nature, Red Cross, and World Wildlife Fund to support projects in biodiversity mapping, hydrology, urban planning, and heritage preservation. Core capabilities align with standards promulgated by the Open Geospatial Consortium, International Organization for Standardization, Global Spatial Data Infrastructure, and the Group on Earth Observations.
Early predecessors trace to mapping programs of the Royal Geographical Society, United States Coast and Geodetic Survey, and the cartographic collections of the Library of Congress and British Library. Advances accelerated with satellite programs from Landsat, Sentinel, SPOT, Terra and initiatives by DigitalGlobe and Planet Labs. Development involved collaborations among research centers such as Massachusetts Institute of Technology, Stanford University, Imperial College London, University of Oxford, ETH Zurich, and national labs including Lawrence Berkeley National Laboratory and Los Alamos National Laboratory.
Architectural layers combine contributions from mapping platforms like Esri, QGIS, GRASS GIS, MapInfo, and server technologies including GeoServer, MapServer, and PostGIS. The system relies on spatial databases and services such as Oracle Spatial, Microsoft SQL Server, MongoDB, and Amazon Web Services offerings integrated with OpenStreetMap and cadastral datasets from agencies such as Land Registry (England and Wales), Cadastre (France), and national cadastral authorities. Security and governance draw on frameworks from National Institute of Standards and Technology, European Union Agency for Cybersecurity, and policies adopted by ministries like the Department of the Interior (United States) and Ministry of Defence (United Kingdom) for sensitive layers.
Primary datasets derive from remote sensing programs including Landsat 8, Sentinel-2, ICESat, and airborne lidar campaigns run by institutions like the U.S. Geological Survey National Geospatial Program and private firms such as Airbus Defence and Space. Standards referenced include ISO 19115, ISO 19117, OGC Web Map Service, OGC Web Feature Service, OGC Catalogue Service, and metadata schemas used by the National Geospatial-Intelligence Agency and European Environment Agency. The system integrates statistical boundaries from entities like the United Nations Statistical Division, Eurostat, and national statistical offices including U.S. Census Bureau and Statistics Canada.
Use cases span disaster risk reduction with agencies such as Federal Emergency Management Agency and United Nations Office for Disaster Risk Reduction, conservation initiatives led by Conservation International and BirdLife International, urban resilience projects in partnership with UN-Habitat and the World Bank Group, and agricultural monitoring supported by International Fund for Agricultural Development and Food and Agriculture Organization. Additional applications include maritime domain awareness coordinated with International Maritime Organization, transportation planning with World Road Association (PIARC), and public health mapping by World Health Organization and national ministries of health.
Implementations exploit programming ecosystems including Python (programming language), R (programming language), JavaScript, and frameworks such as Leaflet (JavaScript library), OpenLayers, Django, and Flask (web framework). Workflow automation uses tools like Apache Airflow, Docker, Kubernetes, Hadoop, and Apache Spark for big-data processing, while machine learning and remote sensing analysis utilize libraries from TensorFlow, PyTorch, scikit-learn, and community toolkits such as Google Earth Engine and ESA SNAP. Visualization and dissemination employ portals modeled after Data.gov, Copernicus Open Access Hub, and institutional repositories maintained by National Archives and Records Administration and the British Geological Survey.
Challenges include interoperability between legacy products from vendors like Trimble and contemporary open-source stacks, licensing tensions involving private providers Maxar Technologies and public agencies, data quality control across contributors such as regional mapping agencies and international programs, and governance disputes among bodies like the United Nations Committee of Experts on Global Geospatial Information Management and national mapping authorities. Technical limitations arise from variable temporal resolution of satellites (e.g., Landsat, Sentinel), computational constraints in processing petabyte-scale archives at centers such as European Centre for Medium-Range Weather Forecasts and national supercomputing facilities like Oak Ridge National Laboratory.
Category:Geographic information systems