IEEE AICCSA 2024 Special Track
Geo Big Data

Track co-chairs

  • Takoua Abdellatif, University of Sousse; SERCOM/University of Carthage, Tunisia
  • Mohamed Ali Mahjoub, University of Sousse, Tunisia
  • Ahmed Ezzine, National Remote Sensing and Mapping Center (CNCT), Tunisia
  • Tijeni Dellegi, Tunisian Military Research Center (CRM), Tunisia


Geospatial big data, often referred to as Geo Big Data, refers to large volumes of spatially referenced data that is generated continuously or collected from various sources such as satellites, GPS devices, sensors, social media, and mobile devices. This data typically includes location information, such as coordinates (latitude and longitude), addresses, or other spatial identifiers, along with associated attributes. Analyzing and deriving insights from Geo Big Data can help organizations make informed decisions, optimize operations, and address complex challenges related to spatial data. The objective of this track is to gather recent research and applications focused on handling geo big data. It presents an opportunity to facilitate exchanges between regional experts and international counterparts regarding patterns, tools, and cutting-edge technologies relevant to this field.


Geo Big Data encompasses a wide range of data types and formats, including Satellite Imagery, GPS Data, Sensor Data, Spatial Databases including LiDAR (Light Detection and Ranging), RADAR (Radio Detection and Ranging), and aerial photography, used for terrain mapping, 3D modeling, and natural resource management, location-Based Social Media Data which is data generated by users of social media platforms that include location information, such as check-ins, geotagged photos, and location-based posts, used for social network analysis, marketing, and urban planning. Other data comprises Geographic Information Systems (GIS) Data that is Spatial data stored in GIS formats, such as shapefiles and GeoJSON, used for mapping, spatial analysis, and decision-making. Managing and analyzing Geo Big Data poses several challenges due to its volume, velocity, variety, and veracity. Specialized tools and techniques are required for storing, processing, analyzing, and visualizing large-scale geospatial datasets. These may include distributed storage and processing frameworks like Hadoop and Apache Spark, spatial databases like PostGIS and MongoDB, and geospatial analysis libraries and software platforms like GDAL, QGIS, and ArcGIS.

  1. Geospatial Data Storage and Management
  2. Geospatial Data Processing and Analysis
  3. Geospatial Data Visualization
  4. Geospatial Data Applications
  5. Machine Learning and AI for Geospatial Data
  6. Geospatial Data Ethics and Privacy Applications of Geo Big Data including urban planning, transportation, agriculture, environmental monitoring, natural resource management, disaster response, public health, and location-based services.

Program committee

  • Abderrazek Jmaii, SERCOM/University of Carthage, Tunisia
  • Rabeh Attia, SERCOM/University of Carthage, Tunisia
  • Ines Bousnina, SERCOM/University of Carthage, Tunisia
  • Wided Souidene, SERCOM/University of Carthage, Tunisia
  • Feten Slimani, Military Academy of Fondouk Jedid, Tunisia
  • Imen Boudali, SERCOM/University of Carthage, Tunisia
  • Olfa Besbes, Isitcom, University of Sousse, Tunisia
  • Maher Boughdir, SERCOM/University of Carthage, Tunisia
  • Ghassan Graja, National Remote Sensing and Mapping Center (CNCT), Tunisia
  • Yassine Gacha, Tunisia Military Research Center (CRM); SERCOM/University of Carthage, Tunisia