Using Spatiotemporal Analysis in Urban Sprawl Assessment and Prediction

  • Federico Amato
  • Piergiuseppe Pontrandolfi
  • Beniamino Murgante
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8580)

Abstract

The importance of soil resource protection is now universally recognized, but despite a lot of debates and principles enunciation, in the last decades the soil was consumed at a rate of 8 m2 per second. In this paper a simulation model has been proposed based on two methods: Joint information uncertainty and Weights of Evidence in order to analyse and predict new built-up areas. The proposed model has been applied to Pisticci Municipality in Basilicata region (Southern Italy). This area is a significant example, because of high landscape values and, at the same time, of a lot of developing pressure due to touristic activities along the coastal zone.

Keywords

Urban planning Soil Consumption Urban sprawl Built-up areas Sustainability 

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References

  1. 1.
    Zampogno, L., Cattaneo, T. (eds.): Suolo bene commune – dalla convenzione europea del paesaggio al governo sostenibile del territorio. Legambiente Lombardia Onlus (2012)Google Scholar
  2. 2.
    COM/2006/0231 a firma della Commissione al parlamento Europeo, al Consiglio, al Comitato Economico e Sociale ed al Comitato delle Regioni in data 22/09/2006 “Strategia tematica per la protezione del suolo”Google Scholar
  3. 3.
    Agostinacchio, M., Ciampa, D., Diomedi, M., Olita, S.: The management of air pollution from vehiculartraffic by implementing forecasting models. In: Sustainability, Eco-Efficiency and Conservation in Transportation Infrastructure Asset Management - Proceedings of the 3rd International Conference on Tranportation Infrastructure, ICTI 2014, pp. 549–560 (2014)Google Scholar
  4. 4.
    Romano, B., Zullo, F.: Models of Urban Land Use in Europe: Assessment tools and criticalities. International Journal of Agricultural and Environmental Information Systems (IJAEIS) 4(3), 80–97 (2013), doi:10.4018/ijaeis.2013070105CrossRefGoogle Scholar
  5. 5.
    Koomen, E.: Modelling Land-Use Change: Progress and Applications. Springer (2007)Google Scholar
  6. 6.
    Bonham-Carter, G.F.: Geographic information system for geoscientist: modelling with GIS, pp. 243–247. Pergamon Press (1994)Google Scholar
  7. 7.
    Smith, E.P., Lipkovich, I., Ye, K.: Weight of evidence: quantitative estimation of probabil-ity of impact. Dept. of Statistic, Virginia Tech (2002)Google Scholar
  8. 8.
    Romano, B., Zullo, F.: The urban transformation of Italy’s Adriatical coastal strip: Fifty years of unsustainability. Land Use Policy 38 (2014)Google Scholar
  9. 9.
    Perchinunno, P., Rotondo, F., Torre, C.M.: The Evidence of Links between Landscape and Economy in a Rural Park. International Journal of Agricultural and Environmental Information Systems 3(2), 72–85 (2012), doi:10.4018/jaeis.2012070105CrossRefGoogle Scholar
  10. 10.
    Murgante, B., Danese, M.: Urban versus rural: the decrease of agricultural areas and the development of urban zones analyzed with spatial statistics. Int. J. Agric. Environ. Inform. Syst. 2(2), 16–28 (2011), http://dx.doi.org/10.4018/jaeis.2011070102 CrossRefGoogle Scholar
  11. 11.
    Modica, G., Vizzari, M., Pollino, M., Fichera, C.R., Zoccali, P., Di Fazio, S.: Spatio-temporal analysis of the urban-rural gradient structure: an application in a Mediterranean mountainous landscape (Serra San Bruno, Italy). Earth Syst. Dyn. 3(2), 263–279 (2012), http://dx.doi.org/10.5194/esd-3-263-2012 CrossRefGoogle Scholar
  12. 12.
    Martellozzo, F.: Forecasting high correlation transition of agricul-tural landscapes into urban areas: diachronic case study in North East-ern Italy. Int. J. Agric. Environ. Inform. Syst (IJAEIS) 3(2), 22–34 (2012), http://dx.doi.org/10.4018/jaeis.2012070102 CrossRefGoogle Scholar
  13. 13.
    Evaluation of Urban Sprawl from space using open source technologiesGoogle Scholar
  14. 14.
    NolèG., M.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
  15. 15.
    Nolè, G., Lasaponara, R., Lanorte, A., Murgante, B.: Quantifying Urban Sprawl with Spatial Autocorrelation Techniques using Multi-Temporal Satellite Data. Int. J. Agric. Environ. Inform. Syst. 5(2) (2014)Google Scholar
  16. 16.
    Clarke, K.C., Gaydos, L.: Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington/Baltimore. Int. J. of Geographic Inf. Sci. 12, 699–714 (1998)CrossRefGoogle Scholar
  17. 17.
    Cerreta, M., Poli, G.: A Complex Values Map of Marginal Urban Landscapes: An Experiment in Naples (Italy). International Journal of Agricultural and Environmental Information Systems 4(3), 41–62 (2013), doi:10.4018/ijaeis.2013070103CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Federico Amato
    • 1
  • Piergiuseppe Pontrandolfi
    • 1
  • Beniamino Murgante
    • 1
  1. 1.University of BasilicataPotenzaItaly

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