Skip to main content

A Quantitative Prediction of Soil Consumption in Southern Italy

  • Conference paper
  • First Online:
Computational Science and Its Applications -- ICCSA 2015 (ICCSA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9157))

Included in the following conference series:

Abstract

Landuse/cover evolution dynamic is a subject widely and thoroughly investigated, especially concerning consumption of natural and other lands, due to anthropogenic activities. This paper focuses on a region in southern Italy, where soil consumption is known to represent a urging matter of concern. However, although negative impacts of soil consumption are well known, to our knowledge there are no case studies presenting a precise quantitative measurement of the intensity of such phenomenon for the region of interest. This study aims at forecasting the development of urban settlements through the application of the cellular automata model SLEUTH; the first region to be investigated has been the Municipality of Altamura (Apulia region, Italy). This area has been used as a pilot case study to explore many difficulties and advantages in applying such a methodology to the whole southern Italian region. The final goal was to frame and populate an atlas of soil consumption in southern Italy, which intends to offer useful support to sustainable planning and policies.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Balena, P., Sannicandro, V., Torre, C.M.: Spatial multicrierial evaluation of soil consumption as a tool for SEA. In: Murgante, B., et al. (eds.) ICCSA 2014, Part III. LNCS, vol. 8581, pp. 446–458. Springer, Heidelberg (2014)

    Google Scholar 

  2. Sannicandro, V., Torre, C.M.: Monitoraggiodel land cover index e valutazionemultidimensionaledelletrasformazioniinsediativepotenziali, Atti 2015. ConvegnoRecuperiamoTerreno, IstitutoSuperiore per la Protezione e la RicercaAmbientale (ISPRA), Milano, vol. I, pp. 94–105, 6 maggio 2015. ISBN: 978-88-448-0710-8

    Google Scholar 

  3. Romano, B., Zullo, F.: Land urbanization in Central Italy: 50 years of evolution. J. Land Use Sci. (2012). http://dx.doi.org/10.1080/1747423X.2012.754963

  4. Romano, B., Zullo, F.: Models of urban land use in Europe: assessment tools andcriticalities. Int. J. Agric. Environ. Inf. Syst. 4(3), 80–97 (2013). doi:10.4018/ijaeis.2013070105. IGI Global

    Article  Google Scholar 

  5. Romano, B., Zullo, F.: The urban transformation of Italy’s Adriatic Coast Strip: fifty years of unsustainability. Land Use Policy 38, 26–36 (2014)

    Article  Google Scholar 

  6. ISTAT. Le problematicheconnesse al consumo del suolo (2012). http://www.istat.it/it/archivio/51331

  7. Murgante, B., Borruso, G., Lapucci, A.: Geocomputation and urban planning. In: Murgante, B., Borruso, G., Lapucci, A. (eds.) Geocomputation and Urban Planning Studies in Computational Intelligence. SCI, vol. 176, pp. 1–18. Springer, Heidelberg (2009). doi:10.1007/978-3-540-89930-3_1. ISBN: 978-3-540-89929-7

    Chapter  Google Scholar 

  8. Von Neumann, J.: Theory of Self-Producing Automata. University of Illinois Press, Urban and Chicago (1996)

    Google Scholar 

  9. USGS. Project gigalopolis: urban and land cover modelling. US Geological Survey (2003) http://www.ncgia.ucsb.edu/projects/gig/

  10. Clarke, K.C., Hoppens, S., Gaydos, L., A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environmental and Planning B: Planning and Design 24 (1997)

    Google Scholar 

  11. Jantz, C.A., Goetz, S.J., Shelley M.K.: Using the SLEUTH urban growth model to simualte the impacts of future policy scenarios on urban land use in the Baltimore - Washington metropolitan area. Environmental and Planning B: Planning and Design 30 (2003)

    Google Scholar 

  12. Clarke, K.C., Gaydos, L.J.: Loose-coupling a cellular automaton model and GIS: long-term urban growth prediction for San Francisco and Washington/Baltimore. International Journal of Geographical Information Science 12 (1998)

    Google Scholar 

  13. Caglioni, M., Pelizzoni, M., Rabino, G.A.: Urban sprawl: a case study for project gigalopolis using SLEUTH model. In: El Yacoubi, S., Chopard, B., Bandini, S. (eds.) ACRI 2006. LNCS, vol. 4173, pp. 436–445. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  14. Martellozzo, F., Clarke, K.C.: Measuring urban sprawl, coalescence, and dispersal: a case study of Pordenone, Italy. Environment and Planning B: Planning and Design 2011 38, 1085–1104 (2011). doi:10.1068/b36090

    Article  Google Scholar 

  15. Martellozzo, F.: Forecasting High Correlation Transition of Agricultural Landscapes into Urban Areas: Diachronic Case Study in North Eastern Italy. International Journal of Agricultural and Environmental Information Systems (IJAEIS) 3(2), 22–34 (2012). doi:10.4018/jaeis.2012070102

    Article  Google Scholar 

  16. Nolè, G., Murgante, B., Calamita, G., Lanorte, A., Lasaponara, R.: Evaluation of Urban Sprawl from space using open source technologies. Ecological Informatics (2014). DOI http://dx.doi.org/10.1016/j.ecoinf.2014.05.005

  17. Nolè, G., Lasaponara, R., Lanorte, A., Murgante, B.: Quantifying Urban Sprawl with Spatial Autocorrelation Techniques using Multi-Temporal Satellite Data. International Journal of Agricultural and Environmental Information Systems 5(2), 20–38 (2014). doi:10.4018/IJAEIS.2014040102. IGI Global

    Article  Google Scholar 

  18. Amato, F., Pontrandolfi, P., Murgante, B.: Using spatiotemporal analysis in urban sprawl assessment and prediction. In: Murgante, B., et al. (eds.) ICCSA 2014, Part II. LNCS, vol. 8580, pp. 758–773. Springer, Heidelberg (2014). doi:10.1007/978-3-319-09129-7_55

    Google Scholar 

  19. Amato, F., Pontrandolfi, P., Murgante, B.: Modelli di analisi e previsionespazio-temporali per la valutazione del consumo di suoloedimplicazioninellepoliticheurbanistiche, UrbanisticaInformazioni, Anno XXXXI, Settembre-Ottobre 2014, Sessione 7, vol. 257, pp. 6–10. INU Edizioni (2014b). ISSN: 0392-5005

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Beniamino Murgante .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Amato, F., Martellozzo, F., Murgante, B., Nolè, G. (2015). A Quantitative Prediction of Soil Consumption in Southern Italy. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9157. Springer, Cham. https://doi.org/10.1007/978-3-319-21470-2_58

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-21470-2_58

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21469-6

  • Online ISBN: 978-3-319-21470-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics