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Tag: Spatial Data Analytics

GEOSummit – Session on New Methods in Spatial Data Analytics

With the increasing availability of spatial data, analysis methods are also evolving. It is therefore not surprising that, in addition to established approaches from the field of machine learning, Large Language Models, which are very present in the media, are also used when working with spatial data. But are these sometimes very complex methods only to be found in research or are there already concrete applications and operational services in Switzerland? Examples from research and practice are presented, which are convincing with new methods of spatial data analysis.

Find more information on the official website.

Spatial Data Analytics – AI-driven Probability Maps

In the field of environmental monitoring, artificial intelligence (AI) coupled with probability maps emerges as a powerful tool for comprehensively understanding and managing ecological systems. By harnessing machine learning algorithms, intricate patterns within environmental datasets can be discerned with unprecedented accuracy. Based on this understanding, probability maps can be calculated to offer valuable insights into the likelihood of various environmental events. These maps serve as crucial decision-making aids for policymakers, conservationists, and researchers alike, enabling proactive measures to mitigate ecological threats and promote sustainable practices.

Schedule:

  • 14:45 – 14:55 – Intro and introductions (Dr. László István Etesi – FHNW)
  • 14:55 – 15:30 – Probability Maps: Current research & applications in the field of environmental monitoring
  • 15:30 – 16:00 – Break
  • 16:00 – 16:30 – Indicate challenges around robust multi-sensor & multi-scale data integration and harmonization 
  • 16:30 – 17:00 – Discussion on ideas which can be further evaluated in the frame of the Innovation Booster