FIG Commission 3 - Spatial Information Management

Working Group 3.2
Geospatial Big Data: collection, processing, and presentation

Policy Issues

The definition of “Big Data” is complex and constantly changing, mainly based on the three Vs definition of their characteristics, such as “Big data represents the information assets characterized by such a high Volume, Variety and Velocity to require specific technology and analytical methods for its transformation into value”, or “data sets characterized by huge amounts (Volume) of frequently updated data (Velocity) in various formats, such as numeric, textual, or images/videos (Variety)”.

A significant portion of big data is actually geospatial data, and the size of such data is growing rapidly at least by 20% every year due to the rapid technological development. Geospatial big data (GBD) collection methods include surveying, photogrammetry, remote sensing, LIDAR/Laser scanning, VGI, Mobile mapping systems, GNSS tracking, real time sensor observations, geo-sensor networks, IoTs, etc. The various types of GBD include raster data (e.g., geoimages-aerial, satellite, etc-, 3D objects), vector data (e.g., points, lines, polygons), and graph data (e.g., road networks, topological coverage, grid data).

The “Volume” characteristic of the GBD deals with issues related to data storage and massive analysis; the “Variety” deals with issues related to data management models and structures as well as indexes; while “Velocity” refers to issues such as matching the speed of data generation and processing. However, the three Vs definition is further expanded with more characteristics, such as the one called “Veracity” which refers to quality assessment of source data, data improvement, etc.

The increasing volume and varying format of collected GBD presents challenges in storing, managing, processing, analyzing, visualizing and verifying the quality of data.

The target of Working Group 3.2 will be to investigate the opportunities and challenges and to propose a framework for understanding the ways that GBD may be obtained, processed, presented, shared and best used together with data derived from traditional surveying methods to provide richer datasets, and to be used in ways that are complementary.

Workign Group 3.2 will contribute to UN SDG 11 (Sustainable Cities) but also to SDG 1 (No Poverty) and SDG 2 and 3 (Zero Hunger) and 13 (Climate Action).

Working Group 3.2 will focus to motivate researchers in academia and industry, students, as well as delegates from the state sector to partner and join efforts to improve the value of GBD for the society as well as to take advantage of this value for improving the surveying profession. Intercommission activity as well as collaboration with other FIG Com3 WGs in this field will be encouraged.


Prof. Charalabos Ioannidis (Greece)
email: cioannid[at]

Specific topics

Topics of interest of Working Group 3.2 include the following:

Topics of general interest/raising awareness:

  • Good practice applications of GBD in land administration, economy, health, planning, 3d modelling, climate change, disaster response, monitoring infrastructure, transportation, agriculture for the Sustainable Development Agenda 2030
  • GBD in GIS (import, analysis, processing tools, presentation)
  • Case studies using GBD
  • Platforms for sharing GBD
  • Policies/legislation

Technical topics:

  • Hardware and Software for GBD collection and processing
  • IoT and surveying activity
  • Spatial computing techniques/methodologies
  • Algorithms of GBD processing
  • Visualization of GBD
  • GBD and mobile devices
  • GBD handling methods in storing, managing, processing, analyzing, visualizing, verifying the quality of data, data security
  • Cloud computing and cloud storage for efficient access and process of GBD
  • Methodological/Theoretical/Technical developments in modelling, processing, analyzing, visualizing GBD
  • Data mining for decision support
  • Knowledge discovery from GBD
  • Cluster-based systems for processing GBD


What we are working on -

  • FIG publication on Smart Cities (2022) - contribute to the publication with Working Group 3.1

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