Geodata is information about geographic locations that can be stored in and used with a geographic information system (GIS).
What is Geodata?
Geodata, also known as geographic data or geospatial data, refers to data and information that has explicit or implicit association with a location relative to Earth.
Common types of geographic data include vector files, which consist of vertices and paths; raster files, which is made up of pixels and grid cells; geographic databases, which serves the function of housing vectors and rasters; multi-temporal data, which attaches a time component to information; and Web files.
Geographic data can be sourced from telematics devices, Global Positioning System (GPS) data, geospatial satellite imagery, Internet of Things, and geotagging. Some geographic themes into which geographic data can be grouped include:
- Administrative data (boundaries -- cities and planning)
- Socioeconomic data (demographics -- economy and crime)
- Transportation (roads -- railways and airport)
- Elevation data (terrain and relief)
- Environmental data (agriculture -- soils and climate)
- Hydrography data (oceans, lakes, and rivers)
Retrieving geodata is accomplished with the use of a geodata service, which facilitates the access of a geodatabase through either a local area network (LAN) or through the Internet using a server. Geodata services facilitate remote geodata management via the geodata cloud, which enables remote geodatabase replication operations, execution of queries in the geodatabase, and creation of copies using data extraction. A popular and recent example of GIS mapping application includes Geodata Explorer, which was published by Tech Maven Geospatial in 2019.
What is Geodata Used For?
Geospatial data is used to visually depict and better understand the impact of human activity based on a specific geographic location. GIS use digital geodata software to collect, store, and analyze geospatial data, which is then used to create layered maps to better analyze complex environmental events and socioeconomic trends.
Presenting data visually with a geographic context helps clarify how data relates to a specific location and illuminates patterns that may otherwise go undetected. Geodata visualization is achieved with geospatial modeling, which uses advanced cartographic technologies to integrate interactive visualization into traditional maps, providing analysts with the ability to interact with, change the parameters of, and identify relationships on a geodata map.
The application of geographic data in geospatial technologies is especially useful in cases such as urban planning and development, routing for airlines, property risk assessment for insurance, weather-related evacuation alerts, optimization of military logistics, fast identification and repair of network anomalies, and telecommunications.
Geodata for 5G
Good geodata is critical for the telecommunication industry's fifth-generation network (5G), which relies on current, high-resolution maps to deliver valuable context for informed, data-driven decision making. Next-generation 5G geodata helps optimize 5G network design by identifying obstructions that may interfere with 5G’s highly sensitive signal propagation.
Gathering and analyzing advanced geodata for 5g networks requires the use of 3D geodata mapping software, which provides highly accurate observations to meet the demands of 5G signal sensitivity caused by frequency features. GIS and mapping software solutions enable the geosimulation and spatial calculations execution required for 5G geodata planning. 3D geodata for telecom requires a platform on which telecommunication network operators, engineers, and data scientists can analyze and visualize complex data records at scale.
Does OmniSci Offer a Geodata Solution?
Geodata has tremendous potential across the federal and telecom industries with the right tools. Agencies now have access to billions of location-rich records and geospatial intelligence analysts need a platform that can query and render these massive spatiotemporal data sets. OmniSci leverages the power of CPUs and GPUs to accelerate existing analytics solutions or to render interactive visualization of massive geospatial datasets with millisecond latency.
The OmniSciDB SQL engine natively stores geometric and geographic data types, enabling geo calculations with the massively parallel processing power of CPUs and GPUs. And geospatial analysts can use the OmniSci Immerse visualization system with powerful cross-filtering for zero-latency exploration of big geodata to better understand and prepare the dataset for further use.