tt ntttttttntttttttttntttnttttttttt nnnttttnttttttttSpatial Data Analytics - AI-driven Probability Mapsttttnttttnnttt ntttttttt nntt ntttnn 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. nnnn Schedule: nnnn n 14:45 u2013 14:55 u2013 Intro and introductions (Dr. Lu00e1szlu00f3 Istvu00e1n Etesi, Prof. Gerd Simons - FHNW) nnnn 14:55 u2013 15:30 u2013 Probability Maps: Current research & applications in the field of environmental monitoring nnnn 15:30 u2013 16:00 u2013 Break nnnn 16:00 u2013 16:30 u2013 Indicate challenges around robust multi-sensor & multi-scale data integration and harmonization  nnnn 16:30 u2013 17:00 u2013 Discussion on ideas which can be further evaluated in the frame of the Innovation Booster n nntt n