Integration of Geomatic, Geophysical and Chemical Data in a GIS Environment for Monitoring Contaminated Soils | SpringerLink
Skip to main content

Integration of Geomatic, Geophysical and Chemical Data in a GIS Environment for Monitoring Contaminated Soils

  • Conference paper
  • First Online:
Computational Science and Its Applications – ICCSA 2024 Workshops (ICCSA 2024)

Abstract

This paper presents a GIS-based integration of a multidisciplinary dataset concerning a heavy metal contaminated soil. The case study is an area extending for about half a hectare where nearly 600 young trees have been planted to carry out a phytostabilization treatment. Three different plant species have been used for the experiment, lentisk, poplar and oleander, with different characteristics in terms of foliage and mean heights. The area has been monitored by exploiting geomatics, geophysical and chemical techniques, to acquire a comprehensive dataset able to describe the vegetation health status and the soil pollution levels. Low-cost UAV flights, GNSS surveys, and geophysical and chemical investigations have been performed in the area at four different epochs. The different acquisitions were elaborated resulting in specific products (point clouds, DSMs, specific maps) and the related quantitative and qualitative parameters. All the available data have been managed in a GIS project to provide a broad description of the site and to ease the understanding of complex dynamics. The presented analysis belongs to a wider project, aiming at defining monitoring procedures for soils contaminated by heavy metals, using a combination of geomatics, geophysical, and chemical derived parameters. The final purpose will be the definition of algorithms implemented in the GIS environment, specific for different soils, plant species and microbial populations allowing the identification of the optimal conditions for the contaminated site’s restoration.

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 14871
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 18589
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

Disclosure of Interests

The authors have no competing interests to declare that are relevant to the content of this article.

References

  1. SardegnaArpa. https://www.sardegnaambiente.it/arpas. Accessed 01 Feb 2024

  2. SardegnaAmbiente. https://portal.sardegnasira.it/-/aggiornamento-del-piano-regionale-bonifica-siti-inquinati. Accessed 01 Feb 2024

  3. Ashraf, S., Ali, Q., Zahir, Z.A., Ashraf, S., Asghar, H.N.: Phytoremediation: environmentally sustainable way for reclamation of heavy metal polluted soils. In: Ecotoxicology and Environmental Safety, vol. 174, pp. 714–727. Elsevier, Amsterdam (2019)

    Google Scholar 

  4. Pivetz, B.E.: Phytoremediation of contaminated soil and ground water at hazardous waste sites. US Environmental Protection Agency, Office of Research and Development, Office of Solid Waste and Emergency Response (2001)

    Google Scholar 

  5. Mahar, A., et al.: Challenges and opportunities in the phytoremediation of heavy metals contaminated soils: a review. In: Ecotoxicology and Environmental Safety, vol. 126, pp.111–121. Elsevier, Amsterdam (2016)

    Google Scholar 

  6. Saleem, M.H., et al.: Jute: a potential candidate for phytoremediation of metals—a review. In: Plants, vol. 9, no. 2, p. 258. MDPI, Basel (2020)

    Google Scholar 

  7. Kafle, A., Timilsina, A., Gautam, A., Adhikari, K., Bhattarai, A., Aryal, N.: Phytoremediation: mechanisms, plant selection and enhancement by natural and synthetic agents. In: Environmental Advances, vol. 8, pp. 100203. Elsevier, Amsterdam (2022)

    Google Scholar 

  8. Raihan, A.: A systematic review of geographic information systems (GIS) in agriculture for evidence-based decision making and sustainability. In: Global Sustainability Research, vol. 3, no. 1, pp. 1–24 (2024). https://doi.org/10.56556/gssr.v3i1.636

  9. Kross, A., Kaur, G., Jaeger, J.A.: A geospatial framework for the assessment and monitoring of environmental impacts of agriculture. In: Environmental Impact Assessment Review, vol. 97, 106851. Elsevier, Amsterdam (2022)

    Google Scholar 

  10. Avanidou, K., Alexandridis, T., Kavroudakis, D., Kizos, T.: Development of a multi scale interactive web-GIS system to monitor farming practices: a case study in Lemnos Island, Greece. In: Smart Agricultural Technology, vol. 5, pp. 100313. Elsevier, Amsterdam (2023)

    Google Scholar 

  11. Deidda, M., Musa, C., Vacca, G.: A GIS of Sardinia’s coastal defense system (XVI – XVIII century). In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 40(4/W7), pp. 17–22 (2015)

    Google Scholar 

  12. Trivedi, A., Rao, K.V.R., Rajwade, Y., Yadav, D., Verma, N.S.: Remote sensing and geographic information system applications for precision farming and natural resource management. In: Indian Journal of Ecology, vol. 49, no. 5, pp. 1624–1633 (2022)

    Google Scholar 

  13. Vacca, G., Vecchi, E.: UAV photogrammetric surveys for tree height estimation. In: Drones, vol. 8, no. 3, pp. 106. MDPI, Basel (2024)

    Google Scholar 

  14. Bai, P., Vignoli, G., Viezzoli, A., Nevalainen, J., Vacca, G.: Quasi-real-time inversion of airborne time-domain electromagnetic data via artificial neural network. In: Remote Sensing, vol. 12, no. 20, pp. 3440. MDPI, Basel (2020)

    Google Scholar 

  15. Zaru, N., Rossi, M., Vacca, G., Vignoli, G.: Spreading of localized information across an entire 3D electrical resistivity volume via constrained EMI inversion based on a realistic prior distribution. In: Remote Sensing, vol. 15, no. 16, pp. 3993. MDPI, Basel (2023)

    Google Scholar 

  16. Zaru, N., Silvestri, S., Assiri, M, Bai, P., Hansen, T.M., Vignoli, G.: Probabilistic petrophysical reconstruction of danta’s alpine peatland via electromagnetic induction data. In: Earth and Space Science, vol. 11, no. 3, pp. e2023EA003457. Wiley, Hoboken (2024)

    Google Scholar 

  17. Mambwe, M., Kalebaila, K.K., Johnson, T.: Photochemical oxidation and landfarming as remediation techniques for oil-contaminated soil. In: Global Journal of Environmental Science and Management, vol. 10.2, pp. 517–536 (2024)

    Google Scholar 

  18. Vacca, G., Quaquero, E., Pili, D., Brandolini, M.: Integrating BIM and GIS data to support the management of large building stocks. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 42, pp. 647–653 (2018)

    Google Scholar 

  19. Panda, S., et al.: Decision support system for lespedeza cuneata production and quality evaluation: a WebGIS dashboard approach to precision agriculture. In: Preprints (2024)

    Google Scholar 

  20. Lanki, A.D., Onwu, C.A.: Geographic Information System (GIS) application in soil fertility management: a review. In: Journal of Global Agriculture and Ecology, vol. 16, no. 2, pp. 29–40 (2024)

    Google Scholar 

  21. Adão, T., Soares, A., Pádua, L., Guimãrdes, N., Pinho, T., Sousa, J.J., Morais, R., Peres, E.: Mysense-Webgis: a graphical map layering-based decision support tool for agriculture. In: IGARSS 2020–2020 IEEE International Geoscience and Remote Sensing Symposium, pp. 4195–4198 (2020)

    Google Scholar 

  22. Vacca, G.: 3D Survey with Apple LiDAR sensor - test and assessment for architectural and cultural heritage. In: Heritage, vol. 6, no. 2, pp. 1476–1501. MDPI, Basel (2023)

    Google Scholar 

  23. Sanz-Ablanedo, E., Chandler, J.H., Rodríguez-Pérez, J.R., Ordóñez, C.: Accuracy of Unmanned Aerial Vehicle (UAV) and SfM photogrammetry survey as a function of the number and location of ground control points used. In: Remote Sensing, vol. 10, no. 10, pp. 1606 (2018)

    Google Scholar 

  24. Dzikunoo, E.A., Vignoli, G., Jørgensen, F., Yidana, S.M., Banoeng-Yakubo, B.: New regional stratigraphic insights from a 3D geological model of the Nasia sub-basin, Ghana, developed for hydrogeological purposes and based on reprocessed B-field data originally collected for mineral exploration. In: Solid Earth, vol. 11, no. 2, pp. 349–361 (2020)

    Google Scholar 

  25. Christiansen, A.V., Auken, E., Kirkegaard, C., Schamper, C., Vignoli, G.: An efficient hybrid scheme for fast and accurate inversion of airborne transient electromagnetic data. In: Exploration Geophysics, vol 47, no. 4, pp. 323–330. Taylor&Francis (2016)

    Google Scholar 

  26. Klose, T., Guillemoteau, J., Vignoli, G., Tronicke, J.: Laterally constrained inversion (LCI) of multi-configuration EMI data with tunable sharpness. In: Journal of Applied Geophysics, vol. 196, pp. 104519: Elsevier, Amsterdam (2022)

    Google Scholar 

  27. Bai, P., Vignoli, G., Hansen, T.M.: 1D stochastic inversion of airborne time-domain electromagnetic data with realistic prior and accounting for the forward modeling error. In: Remote Sensing, vol. 13, no. 19, pp. 3881. MDPI, Basel (2021)

    Google Scholar 

  28. Klose, T., Guillemoteau, J., Vignoli, G., Walter, J., Herrmann, A., Tronicke, J.: Structurally constrained inversion by means of a Minimum Gradient Support regularizer: examples of FD-EMI data inversion constrained by GPR reflection data. In: Geophysical Journal International, vol. 233, no. 3, pp. 1938–1949 (2023)

    Google Scholar 

  29. Wang, Y., et al.: Remediation of Cd (II), Zn (II) and Pb (II) in contaminated soil by KMnO4 modified biochar: stabilization efficiency and effects of freeze–thaw ageing. In: Chemical Engineering Journal, vol. 487, pp. 150619. Elsevier, Amsterdam (2024)

    Google Scholar 

  30. Ecoserdiana. Progetto di Ricerca su Tecnologie di CARatterizzazione Monitoraggio e Analisi per il ripristino e la bonifica (CARMA) - Fondo Europeo di Sviluppo Regionale - Por Fesr Sardegna 2014–2020. https://www.ecoserdiana.com/servizi/progetti-di-ricerca.html. Accessed 01 Apr 2024

  31. Sarnet. Web Server della Rete di Stazioni Permanenti Della Sardegna. www.sarnet.it/servizi.html. Accessed 01 Jan 2024

  32. AgiSoft PhotoScan Standard (Version 1.2.6) (Software). (2016*). http://www.agisoft.com/downloads/installer/. Accessed 03 Mar 2024

  33. CloudCompare. https://www.danielgm.net/cc/. Accessed 17 Jan 2024

  34. Qgis Documentation. https://docs.qgis.org/2.8/en/. Accessed 01 Feb 2024

Download references

Acknowledgments

This research was funded by Sardegna Ricerche CUP: G28C17000250006, https://www.ecoserdiana.com/servizi/progetti-di-ricerca.html.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Giuseppina Vacca .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

De Montis, S. et al. (2024). Integration of Geomatic, Geophysical and Chemical Data in a GIS Environment for Monitoring Contaminated Soils. In: Gervasi, O., Murgante, B., Garau, C., Taniar, D., C. Rocha, A.M.A., Faginas Lago, M.N. (eds) Computational Science and Its Applications – ICCSA 2024 Workshops. ICCSA 2024. Lecture Notes in Computer Science, vol 14824. Springer, Cham. https://doi.org/10.1007/978-3-031-65332-2_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-65332-2_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-65331-5

  • Online ISBN: 978-3-031-65332-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics