6 min read

What is Geospatial Data: Your Essential Guide

What is Geospatial Data: Your Essential Guide

Geospatial data, an indispensable element of modern mapping and location-based services, offers a unique perspective on our world.

This article is your essential guide to exploring the aspects of geospatial data: types, coordinates, structures, and formats. We'll show you the power of raster and vector data and explain why coordinate systems matter. Plus, we'll reveal how geospatial data can be your key to mapping, planning, navigation, and groundbreaking research. Whether you're a GIS professional or new to the field, this is your passport to the geospatial world.

  1. Geospatial data overview
  2. Coordinate reference frames
  3. Geospatial data structures and formats
  4. Geographic information systems (GIS)

Geospatial data overview

Geospatial data is data with a unique location on Earth. It can include information about physical features, such as landforms, bodies of water, and vegetation, as well as human-made structures, such as roads, buildings, and public transport. Geospatial data can be collected in a variety of ways, including satellite imagery, aerial photography, and ground surveys. The data is commonly represented as one of these two types: raster and vector.

  • Raster data is a type of geospatial data that is represented as a grid of cells. Each cell in the grid has one or several values that represent properties at a specific location. For example, a raster dataset of satellite imagery might have a value for each cell that represents the brightness of the Earth's surface at that location.
  • Vector data is a type of geospatial data that is represented as different geometries: points, lines, and polygons. Each point, line, or polygon has one or several values that represent properties at a specific location. Points represent discrete locations, lines represent linear features, such as roads or rivers, and polygons represent area features, such as lakes or buildings. Point cloud data is a special type of vector data that often refers to large data sets that require different data formats and structures to handle the data.

Vector data Polygon features - Geospatial Data Blog

Image: The left panel shows the three types of vector data: point, line, and polygon. The right panel shows the same data translated into a raster format (Image source). Data can be converted from vector to raster and vice versa, but the nature of the data will be very different and depends on the conversion algorithm.

💡Independent of the data type, knowing the coordinate reference frame is utterly important to plot the data in its correct location! Without any reference information, spatial data becomes useless.

TrueOcean and TrueEarth automatically geo-index uploaded data and store this information with each data file. This index is used to make data findable and accessible, e.g. in the search function. By default, TrueEarth and TrueOcean recognise the type of data during upload to support also inexperienced users in using and understanding their geospatial data.


Coordinate reference frames

Geospatial data provides a location for the stored information in a coordinate frame (spatial reference system) representing the Earth’s surface. There are two types of spatial reference systems:

  • Geographic coordinate systems (GCS) provide the location as latitude and longitude on a three-dimensional surface, for example, on the Earth’s surface as defined in the World Geodetic System 1984 (WGS84) ellipsoid. See for example GoogleEarth.
  • Projected coordinate systems (PCS) project the location information onto a planar surface (e.g., map sheet or computer screen) to better visualise the spatial data. Prominent PCS are the Mercator projection for visualising global data or UTM (Universal Transverse Mercator) map projection for visualising regional or local data. The projection of locations onto a planar surface causes graphical distortion. Therefore, PCS can be either conformal, preserving angles, or equivalent, preserving the relative area of features.

For referencing, map projections are commonly indexed using the EPSG catalogue (EPSG) or indicated as WKT information (OGC WKT).

Conformal Mercator projection - Geospatial Data Blog


Image: Conformal (equal-angular) Mercator projection, which shrinks Africa and blows up the area of Europe (c Wikipedia).

Mollweide projection - Geospatial Data Blog


Image: Equal-area Mollweide projection, in which Africa is significantly bigger than Europe.

Spilhaus Projection - Geospatial Data Blog


Image: Spilhaus Projection (c John Nelson) visualising the ocean as one water mass.

💡 While EPSG are commonly used and cover most of the global and regional reference frames, very specific local reference frames need to be defined as WKT. Each EPSG catalogue entry can be linked to a WKT string, but not every WKT can be linked to an EPSG catalogue entry.

TrueOcean and TrueEarth use the Pseudo-Mercator map projection EPSG:3857. This is indicated in the map view at the bottom right. They translate any uploaded geospatial data into the projection of its map view (also Pseudo-Mercator, EPSG:3857). Already in the file preview, the user can check the position of the data and data quality. This provides the necessary consistency in large and growing projects.

❗CAUTION: The maps are only correct in angles and shapes. However, distance and area measurements should exclusively be conducted using the built-in measurement tools that convert the projection distortion.

Geospatial data structures and formats

Geospatial data can be structured in a variety of ways, depending on the type of data and the intended use. However, some common ways to structure geospatial data include:

  • File: Geospatial data can be stored in files. An individual file usually represents a single data set and can either store vector data (e.g., shapefiles, geopackes, geoparquet) or raster data (e.g., GeoTIFFs, NetCDF, Zarr).
  • Database: Geospatial data can be stored in a database, which groups several (related) data sets. These data sets are typically contained as files of different types (vector and raster). Geospatial databases are either relational or a NoSQL, which allows the data to be queried and analysed using standard SQL commands.
  • Cloud: Geospatial data can also be stored in the cloud, using services such as Amazon Web Services (AWS) or Google Cloud Platform (GCP). This allows the data to be accessed and used from anywhere in the world.

TrueEarth and TrueOcean leverage a scalable geo-cloud architecture to handle big data from satellite imagery to complex 3D point cloud data. Data are stored and managed either on centralised servers (e.g., IONOS) or in a decentralised, distributed manner. Using open-source components ensures interoperability and allows users to work across multiple projects on one single platform.

👉TrueOcean translates the majority of available marine data structures in a standardised manner to make the data FAIR and to foster standard quality control procedures. TrueEarth standardises typical land survey data and offers tools for processing and analysis of these data.

Geospatial Data Blog - Featured Image

Image: TrueOcean Marine Data Platform - Map view with geospatial data

When choosing a way to structure geospatial data, it is important to consider the following factors:

  • The type of data: Raster data and vector data have different structures, so it is important to choose a structure that is appropriate for the type of data.
  • The intended use: The structure of the data should be designed to support the intended use of the data. For example, if the data will be used for querying and analysis, it may be best to store the data in a database. If the data will be used for visualization, it may be best to store the data in a file format such as GeoTIFF or geopackage/geoparquet.
  • The scale of the data: If the data is large or complex, it may be necessary to use a distributed database or cloud-based storage solution (e.g., parquet/geoparquet).

💡 While shapefiles (.shp) are still the most commonly used format, there are several reasons why this format is outdated. Alternative file formats to be considered are Geopackage and Geoparquet.

TrueEarth and TrueOcean convert large data files (e.g., point clouds) into Parquet files, which reduces the file size dramatically optimising it for cloud applications. The project data overview automatically structures data after upload and visualises even complex data structures.

👉 TrueOcean optimises workflows dealing with marine data formats, e.g. from multibeam echosounders. TrueEarth supports file formats typically used in land surveys, such as drone video footage or LiDAR data.

Once the geospatial data has been structured, it can be used for a variety of purposes, such as:

  • Mapping: Geospatial data can be used to create maps of the Earth's surface. Maps can be used for planning, navigation, and research.
  • Planning: Geospatial data can be used to plan for new development projects, such as roads, bridges, and wind farms. Geospatial data can also be used to identify and mitigate environmental hazards.
  • Navigation: Geospatial data can be used to develop navigation systems for cars, boats, and airplanes. Navigation systems use geospatial data to determine the location of the user and to provide directions to the desired destination.
  • Research: Geospatial data can be used for a variety of scientific research projects, such as studying climate change, tracking wildlife populations, and mapping natural resources.

TrueOcean and TrueEarth streamline large data volumes. Their modular setup provides a high degree of flexibility for fitting workflows to individual needs and to a certain purpose. With innovative tools users are enabled to analyse complex data on their own. Map views can be managed, modified and shared simply via a browser interface.

Geospatial data provide a valuable basis for a variety of purposes. By carefully structuring geospatial data, it can be made more accessible, easier to use, and more valuable.

Geographic information systems (GIS)

Geospatial data are visualised and organised in Geographic Information System (GIS) software for a variety of purposes, including mapping, planning, and addressing research questions. The most common commercial GIS software is ArcGIS by ESRI; the most common open-source equivalent is QGIS. GIS software organises geospatial data in feature layers (vector data) or raster layers (raster data). The style of layers can be exported with a feature or raster layer as a layer file (.lyr) for ArcGIS or a layer style file (.qml) for QGIS.

GIS developed from individual desktop-based use and data storage is typically limited to desktop or server solutions. For this, GIS projects refer to direct data paths or relative data paths. Cloud solutions and multi-user projects become increasingly popular: ESRI offers its ArcOnline tool, now; an open-source equivalent does not exist, so far.

Common GIS softwares offer a vast variety of tools to visualise, modify, analyse, and export data.

Geospatial search functionality - TrueOcean MDP

Image: Geospatial search functionality in the TrueOcean MDP

TrueOcean and TrueEarth optimise data management in large multi-user, multi-sensor projects. Their unique GeoSearch technology offers a new way to find geodata across multiple projects and based on their true location. Stop looking, start finding.

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