Emerging technologies for assessing ecosystem services: A synthesis of opportunities and challenges

Uta Schirpke*, Andrea Ghermandi, Michael Sinclair, Derek Van Berkel, Nathan Fox, Leonardo Vargas, L. Willemen

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)
36 Downloads (Pure)

Abstract

Rapid technological development opens up new opportunities for assessing ecosystem services (ES), which may help to overcome current knowledge gaps and limitations in data availability. At the same time, emerging technologies, such as mobile devices, social media platforms, and artificial intelligence, give rise to a series of challenges and limitations. This study provides a comprehensive overview of the broad range of technologies that are increasingly used for collecting, analyzing, and visualizing data on ES, including Earth observation, mobile technologies, data science, modeling/simulation, immersive technologies, visualization, and web-based tools. To identify current opportunities and challenges, we systematically reviewed the literature on ES of the last 10 years (2012–2022). We first describe the state-of-the-art of emerging technologies, synthesizing their applicability, opportunities, and limitations. Then, we discuss open issues, future research needs, and potential for further applications in ES research. Our findings indicate great opportunities to increase knowledge on ES thanks to low costs, high data availability, and high flexibility of the technologies. We also find a strong potential to support decision-making, learning and communication. However, limitations and challenges related to the accuracy of the variables and models, accessibility to data, technologies, and information as well as ethical concerns need to be addressed by the research community to assure an inclusive and meaningful use of the technologies. Our findings also suggest that further insights into ES may be achieved through a better integration of different technologies in the future, e.g., Earth observation, data science, and web-based platforms, a stronger transdisciplinary collaboration to advance knowledge on ES, and by broadening the perspective to technological developments in other related fields of research.

Original languageEnglish
Article number101558
Number of pages14
JournalEcosystem services
Volume63
DOIs
Publication statusPublished - Oct 2023

Keywords

  • Big data
  • Machine learning
  • Nature's contributions to people
  • Remote sensing
  • Social media data
  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-HYBRID

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