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RESEARCH PRODUCT
Toward a Collective Agenda on AI for Earth Science Data Analysis
Jan Dirk WegnerXiao Xiang ZhuDevis TuiaRibana RoscherGustau Camps-vallsNathan Jacobssubject
Signal Processing (eess.SP)FOS: Computer and information sciences010504 meteorology & atmospheric sciencesGeneral Computer Science530 PhysicsInterface (Java)Computer Vision and Pattern Recognition (cs.CV)Earth sciencedata analysisComputer Science - Computer Vision and Pattern Recognition0211 other engineering and technologiesearth observation02 engineering and technology01 natural sciencesEnvironmental scienceData modelingFOS: Electrical engineering electronic engineering information engineeringClimate science1700 General Computer ScienceElectrical Engineering and Systems Science - Signal ProcessingElectrical and Electronic EngineeringInstrumentation021101 geological & geomatics engineering0105 earth and related environmental sciences11476 Digital Society Initiative3105 Instrumentation2208 Electrical and Electronic Engineering1900 General Earth and Planetary SciencesDeep learninginterpretable AIRemote sensingartificial intelligencehybrid modelsEarth system scienceAIRemote sensing (archaeology)10231 Institute for Computational ScienceGeneral Earth and Planetary SciencesPotential gameDisciplinedescription
In the last years we have witnessed the fields of geosciences and remote sensing and artificial intelligence to become closer. Thanks to both the massive availability of observational data, improved simulations, and algorithmic advances, these disciplines have found common objectives and challenges to advance the modeling and understanding of the Earth system. Despite such great opportunities, we also observed a worrying tendency to remain in disciplinary comfort zones applying recent advances from artificial intelligence on well resolved remote sensing problems. Here we take a position on research directions where we think the interface between these fields will have the most impact and become potential game changers. In our declared agenda for AI on Earth sciences, we aim to inspire researchers, especially the younger generations, to tackle these challenges for a real advance of remote sensing and the geosciences.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-06-01 | IEEE Geoscience and Remote Sensing Magazine |