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Future Occupational Profiles in Earth Observation and Geoinformation—Scenarios Resulting from Changing Workflows

  • Barbara HoferEmail author
  • Stefan Lang
  • Nicole Ferber
Conference paper
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Technological advances require continuous efforts to keep existing curricula up-to-date and graduates employable in the Earth observation (EO) and geoinformation (GI) sectors. The increasing availability of space/geospatial data and the maturity of technology induce disruptive changes to workflows in the EO/GI sector that suggest the development of training programmes and academic courses for re-skilling of workforce and training new user groups. The target in the EO domain in this respect is to facilitate the ‘user uptake’ of the space infrastructure. User uptake requires knowledge of the workforce demand on the market as well as a skills strategy that takes potential emerging and disruptive changes in the sector into account. In the present contribution we build upon a study of demand for current workforce on the EO/GI market and occupational profiles that require priority when developing training programmes and curricula. Reflections on the findings of that study highlight the need to illustrate expected changes of workflows, i.e. the sequence of tasks executed by employees with a certain occupational profile, for an improved basis of discussion. Therefore, we present a methodology to first, acquire current occupational profiles and second, to illustrate sector developments by mapping the developments on tasks of the workflow. This methodology is demonstrated for the profile of remote sensing specialists. The illustration of changing tasks suggests scenarios for future workforce and questions and directions for the development of a sector skills strategy.

Keywords

Earth observation Geoinformation User uptake Sector skills strategy Technological trends 

Notes

Acknowledgements

We kindly acknowledge the participation of the following remote sensing specialists in the DACUM workshop and their support of this work: Sebastian d’Oleire-Oltmanns, Kerstin Kulessa, Gina Schwendemann and Thomas Strasser. We also acknowledge the input received from Peter Zeil during the development of the presented material. Comments by anonymous reviewers improved the content of the paper. This work has partially been supported by the Erasmus + Sector Skills Alliance project EO4GEO.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Interfaculty Department of Geoinformatics – Z_GISParis-Lodron-University of SalzburgSalzburgAustria

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