LandCover2RDF: An API for Computing the Land Cover of a Geographical Area and Generating the RDF Graph | SpringerLink
Skip to main content

LandCover2RDF: An API for Computing the Land Cover of a Geographical Area and Generating the RDF Graph

  • Conference paper
  • First Online:
The Semantic Web: ESWC 2020 Satellite Events (ESWC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12124))

Included in the following conference series:

  • 875 Accesses

Abstract

Land cover classifications are recognised to be a fundamental source of data to characterise Earth surface and to support change detection analyses. Land cover maps have been produced from different sources as a result of massive time-series image processing. This paper proposes a REST API (and a web user interface) that allows for computing the percentage of land cover classes of a geographic area according to a given map. The computed data is then represented as an RDF graph based on an ontology dedicated to this kind of data focusing on their temporal and spatial dimensions. We illustrate the use of the API to study the evolution of Land Cover on a French geographical area.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 5719
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 7149
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    http://linkedopendata.gr/dataset/corine-land-cover-of-greece.

  2. 2.

    https://www.app-lab.eu/linked-data/.

  3. 3.

    https://www.w3.org/2015/03/inspire/.

  4. 4.

    https://www.w3.org/2015/03/corine.

  5. 5.

    http://www.fao.org/land-water/land/land-governance/land-resources-planning-toolbox/category/details/en/c/1036355.

  6. 6.

    http://www.cesbio.ups-tlse.fr/.

  7. 7.

    https://gdal.org/.

  8. 8.

    http://melodi.irit.fr/share/demo_landcover2RDF_curl.mp4.

  9. 9.

    http://melodi.irit.fr/share/demo_landcover2rdf.webm.

  10. 10.

    Full query at http://melodi.irit.fr/rasterStats?query-blagnac.

References

  1. Arenas, H., Aussenac-Gilles, N,. Comparot, C., Trojahn, C.: Relations topologiques pour l’intégration sémantique de données et images d’observation de la terre. In: Actes du XXXVIème Congrès INFORSID, pp. 63–78 (2018)

    Google Scholar 

  2. Dumitru, C., Schwarz, G., Datcu, M.: Land cover semantic annotation derived from high-resolution SAR images. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 9(6), 2215–2232 (2016)

    Article  Google Scholar 

  3. Espinoza-Molina, D., et al.: Very-high-resolution SAR images and linked open data analytics based on ontologies. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 8(4), 1696–1708 (2015)

    Article  Google Scholar 

  4. Lambin, E., Geist, H.: Land-Use and Land-Cover Change. Springer, Heidelberg (2006). https://doi.org/10.1007/3-540-32202-7

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Cassia Trojahn .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dorne, J., Aussenac-Gilles, N., Comparot, C., Hugues, R., Trojahn, C. (2020). LandCover2RDF: An API for Computing the Land Cover of a Geographical Area and Generating the RDF Graph. In: Harth, A., et al. The Semantic Web: ESWC 2020 Satellite Events. ESWC 2020. Lecture Notes in Computer Science(), vol 12124. Springer, Cham. https://doi.org/10.1007/978-3-030-62327-2_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-62327-2_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62326-5

  • Online ISBN: 978-3-030-62327-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics