Fusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management


  • Vyron Antoniou Multi-National Geospatial Support Group Frauenberger Str. 250, 53879, Euskirchen, Germany
  • Flavio Lupia CREA Council for Agricultural Research and Economics Via Po, 14 00198, Rome, Italy

Parole chiave:

Earth observation, VGI, machine learning, deep learning, digital agriculture, land management


The ever-growing availability of Earth Observation (EO) data is demonstrating a wide range of potential applications in the realm of land management. On the other hand, large volumes of data need to be handled and analysed to extract meaningful information and Geomatics coupled with new approaches such as Artificial Intelligence (AI) and Machine Learning (AI) will play a pivotal role in the years to come.
Training datasets need to be developed to use these new models and Volunteered Geographic Information can be one of the promising sources for EO processing. Among the various applications, agriculture may benefit from the large dataset availability and AI processing. However, several issues remain unsolved and further steps should be taken in the near future by researchers and policy makers.

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Come citare

Antoniou, V., & Lupia, F. (2020). Fusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management. GEOmedia, 24(3). Recuperato da https://www.mediageo.it/ojs/index.php/GEOmedia/article/view/1727




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