Advertisement

Spatio-Temporal Analysis Using Urban-Rural Gradient Modelling and Landscape Metrics

  • Marco Vizzari
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6782)

Abstract

Urbanization can be considered as a particular environmental gradient that produces modifications in the structures and functions of ecological systems. In landscape analysis and planning there is a clear need to develop specific and comparable indicators permitting the spatio-temporal quantification of this gradient and the study of its relationships with the composition and configuration of other land uses. This study, integrating urban gradient modelling and landscape pattern analysis, aims to investigate the spatiotemporal changes induced by urbanization and by other anthropogenic factors. Unlike previous studies, based on the transect approach, landscape metrics are calculated diachronically within five contiguous zones defined along the urban to rural gradient and characterized by decreasing intervals of settlement density. The results show that, within the study area, urban sprawl and agricultural land simplification remain the dominant forces responsible for the landscape modifications that have occurred during the period under investigation.

Keywords

urban-rural gradient urban spatial modelling urban fringe agricultural landscapes landscape metrics kernel density analysis GIS 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bridges, L., Crompton, A., Schaffer, J.: Landscapes as gradients: The spatial structure of terrestrial ecosystem components in southern Ontario, Canada. Ecological Complexity 4, 34–41 (2007)CrossRefGoogle Scholar
  2. 2.
    Luck, M., Wu, J.: A gradient analysis of urban landscape pattern: a case study from the Phoenix metropolitan region, Arizona, USA. Landscape Ecology 17, 327–339 (2002)CrossRefGoogle Scholar
  3. 3.
    McDonnell, M.J., Pickett, S.T.A.: Ecosystem structure and function along urban rural gradients - an unexploited opportunity for ecology. Ecology 71, 1232–1237 (1990)CrossRefGoogle Scholar
  4. 4.
    McDonnell, M.J., Hahs, A.K.: The use of gradient analysis studies in advancing our understanding of the ecology of urbanizing landscapes: current status and future directions. Landscape Ecology 23, 1143–1155 (2008)CrossRefGoogle Scholar
  5. 5.
    Burrough, P.A., Frank, A.U.: Geographic objects with indeterminate boundaries. Taylor & Francis, Abington (1996)Google Scholar
  6. 6.
    Cavailhès, J., Peeters, D., Sékeris, E., Thisse, J.-F.: The periurban city: why to live between the suburbs and the countryside. Regional Science and Urban Economics 34, 681–703 (2004)CrossRefGoogle Scholar
  7. 7.
    Valentini, A.: Il senso del confine – Colloquio con Piero Zanini. Ri-Vista Ricerche per la progettazione del paesaggio 4, 70–74 (2006)Google Scholar
  8. 8.
    Baker, W.L.: A review of models of landscape change. Landscape Ecology 2, 111–133 (1989)CrossRefGoogle Scholar
  9. 9.
    Pryor, R.J.: Defining the rural-urban fringe. Social Forces 47, 202–215 (1968)CrossRefGoogle Scholar
  10. 10.
    Thapa, R., Murayama, Y.: Land evaluation for peri-urban agriculture using analytical hierarchical process and geographic information system techniques: A case study of Hanoi. Land Use Policy 25, 225–239 (2008)CrossRefGoogle Scholar
  11. 11.
    Wehrwein, G.S.: The rural-urban fringe. Economic Geography 18, 217 (1942)CrossRefGoogle Scholar
  12. 12.
    Brook, R., Davila, J.D.: The peri-urban interface: a tale of two cities. Development Planning Unit, UCL (2000)Google Scholar
  13. 13.
    Tacoli, C.: Rural-urban interactions: a guide to the literature. Environment and Urbanization 10, 147–166 (1998)CrossRefGoogle Scholar
  14. 14.
    Allen, A.: Environmental planning and management of the peri-urban interface: perspectives on an emerging field. Environment and Urbanization 15, 135–148 (2003)CrossRefGoogle Scholar
  15. 15.
    Vizzari, M.: Spatial modelling of potential landscape quality. Applied Geography 31, 108–118 (2011)CrossRefGoogle Scholar
  16. 16.
    Blaschke, T.: The role of the spatial dimension within the framework of sustainable landscapes and natural capital. Landscape and Urban Planning 75, 198–226 (2006)CrossRefGoogle Scholar
  17. 17.
    Turner, M.G.: Spatial and temporal analysis of landscape patterns. Landscape Ecology 4, 21–30 (1990)CrossRefGoogle Scholar
  18. 18.
    Uuemaa, E., et al.: Landscape Metrics and Indices: An Overview of Their Use in Landscape Research. Living Reviews in Landscape Research 3 (2009)Google Scholar
  19. 19.
    McGarigal, K., Cushman, S., Neel, M.: FRAGSTATS: Spatial pattern analysis program for categorical maps (2002)Google Scholar
  20. 20.
    Li, H., Wu, J.: Use and misuse of landscape indices. Landscape Ecology 19, 389–399 (2004)CrossRefGoogle Scholar
  21. 21.
    Hahs, A.K., McDonnell, M.J.: Selecting independent measures to quantify Melbourne’s urban–rural gradient. Landscape and Urban Planning 78, 435–448 (2006)CrossRefGoogle Scholar
  22. 22.
    Wang, Y., Li, J., Wu, J., Song, Y.: Landscape pattern changes in urbanization of Pudong New District, Shanghai. Chinese Journal of Applied Ecology 17, 36–40 (2006)Google Scholar
  23. 23.
    Weng, Y.: Spatiotemporal changes of landscape pattern in response to urbanization. Landscape and Urban Planning 81, 341–353 (2007)CrossRefGoogle Scholar
  24. 24.
    Yang, Y., Zhou, Q., Gong, J., Wang, Y.: Gradient analysis of landscape pattern spatial-temporal changes in Beijing metropolitan area. Science in China. Series E, Technological sciences 53(1), 91–98 (2010)CrossRefGoogle Scholar
  25. 25.
    Fichera, C.R., Modica, G., Pollino, M.: Remote sensing and GIS for rural/urban gradient detection. In: Fichera, C.R., Modica, G., Pollino, M. (eds.) XVIIth World Congress of the International Commission of Agricultural and Biosystems Engineering (CIGR), Québec City (2010)Google Scholar
  26. 26.
    Romano, B., Ragni, B., Vizzari, M., Orsomando, E., Pungetti, G.: Rete Ecologica regionale della Regione Umbria. Petruzzi editore, Perugia (2009)Google Scholar
  27. 27.
    McCoy, J., Johnston, K.: Using ArcGIS Spatial Analyst. Environmental Systems Research Institute, Redlands (2002)Google Scholar
  28. 28.
    Soille, P., Vogt, P.: Morphological segmentation of binary patterns. Pattern Recognition Letters 30, 456–459 (2009)CrossRefGoogle Scholar
  29. 29.
    Bailey, T.C., Gatrell, A.C.: Interactive spatial data analysis. Longman Higher Education, Harlow (1995)Google Scholar
  30. 30.
    Silverman, B.W., Jones, M.C., Fix, E., Hodges, J.L.: An Important Contribution to Nonparametric Discriminant Analysis and Density Estimation. International Statistical Review 57, 233–247 (1989)CrossRefGoogle Scholar
  31. 31.
    Danese, M., Lazzari, M., Murgante, B.: Kernel density estimation methods for a geostatistical approach in seismic risk analysis: The case study of Potenza hilltop town (southern Italy). In: Gervasi, O., et al. (eds.) ICCSA 2008, Part I. LNCS, vol. 5072, pp. 415–429. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  32. 32.
    Jones, M.C., Marron, J.S., Sheather, S.J.: A Brief Survey of Bandwidth Selection for Density Estimation. Journal of the American Statistical Association 91, 401–407 (1996)MathSciNetCrossRefzbMATHGoogle Scholar
  33. 33.
    Borruso, G.: Network Density Estimation: A GIS approach for analysing point patterns in a network space. Transactions in GIS 12, 377–402 (2008)CrossRefGoogle Scholar
  34. 34.
    Lloyd, C.D.: Local models for spatial analysis. CRC Press, Boca Raton (2007)Google Scholar
  35. 35.
    Wickham, J.D., Riitters, K.H.: Sensitivity of landscape metrics to pixel size. International Journal of Remote Sensing 16, 3585–3594 (1995)CrossRefGoogle Scholar
  36. 36.
    Wu, J., David, J.L.: A spatially explicit hierarchical approach to modeling complex ecological systems: theory and applications. Ecological Modelling 153, 7–26 (2002)CrossRefGoogle Scholar
  37. 37.
    Imre, A.R., Rocchini, D.: Explicitly accounting for pixel dimension in calculating classical and fractal landscape shape metrics. Acta Biotheoretica 57, 349–360 (2009)CrossRefGoogle Scholar
  38. 38.
    Zhu, M., Xu, J., Jiang, N., Li, J., Fan, Y.: Impacts of road corridors on urban landscape pattern: a gradient analysis with changing grain size in Shanghai, China. Landscape Ecology 21, 723–734 (2006)CrossRefGoogle Scholar
  39. 39.
    Hengl, T.: Finding the right pixel size. Computers & Geosciences 32, 1283–1298 (2006)CrossRefGoogle Scholar
  40. 40.
    Eastman, J.R.: Multicriteria evaluation and GIS. In: Longley, P.A., Goodchild, M.F., Maquire, D.J., Rhind, D.W. (eds.) Geographical Information Systems, pp. 493–502 (1999)Google Scholar
  41. 41.
    Malczewski, J.: GIS and multicriteria decision analysis. John Wiley and Sons, West Sussex (1999)Google Scholar
  42. 42.
    Murgante, B., Casas, G.L., Danese, M.: The use of spatial statistics to analyze the periurban belt. In: Wachowicz, M., Bodum, L. (eds.) The european information society: leading the way with geoinformation. Proceedings of the 10th Agile International Conference on Geographical Information Science, Aalborg, Denmark (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marco Vizzari
    • 1
  1. 1.Department of Man and TerritoryUniversity of PerugiaPerugiaItaly

Personalised recommendations