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Metrics to Rank Illegal Buildings

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Computational Science and Its Applications – ICCSA 2019 (ICCSA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11620))

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Abstract

The problem of illegal buildings (IBs) is becoming dramatic in developing countries due to the population explosion, but, at the same time, it is still an unsolved issue also in several states usually called advanced (e.g., Italy). To protect the environment and, hence, people, authorities must respond to the challenge of IBs by demolishing them. However, in countries where the phenomenon is extended, it is indispensable provide land managers with IT tools that guide them in defining an order of intervention towards demolition. Through remote sensing methods, we can identify suspicious buildings with a good approximation, but they are all ex-aequo. The research described in this work proposes three metrics to rank the IBs located close to rivers. The ranking may be used as the IBs demolition order.

Research supported by an internal grant of the University of L’Aquila.

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Notes

  1. 1.

    The elevation of point Q is its height above the sea level; while the elevation variation of building \(b_i\) (described by its centroid) with respect to a river (described by the point, belonging to the river geometry, most close to \(b_i\)) is the value, taken with sign, of the difference given by the equation:

    $$\begin{aligned} {\varDelta }h_{b_i} = h_{b_i} - h_{r_j}.\qquad \qquad \qquad \qquad \qquad \qquad (4) \end{aligned}$$

References

  1. Biffi, L., et al.: Abbatti l’abuso. I numeri delle (mancate) demolizioni nei comuni italiani. Palermo, Sept. 2018. www.legambiente.it. (in Italian)

  2. Agbola, B.S., et al.: The August 2011 flood in Ibadan, Nigeria: anthropogenic causes and consequences. Int. J. Disaster Risk Sci. 3(4), 20–217 (2012). https://doi.org/10.1007/s13753-012-0021-3

    Article  Google Scholar 

  3. Chen, X., et al.: Analyzing the effect of urbanization on flood characteristics at catchment levels. In: Proceedings of IAHS, vol. 370, pp. 33–38 (2015). proc-iahs.net/370/33/2015/. https://doi.org/10.5194/piahs-370-33-2015

  4. Dong, Y., et al.: Extraction of buildings from multiple-view aerial images using a feature-level-fusion strategy. Remote Sens. 10(12), 1947 (2018). https://doi.org/10.3390/rs10121947

    Article  Google Scholar 

  5. Fiorillo, A., et al. (eds.): 2007 Urban ecosystem. Legambiente (2007). (in Italian). http://www.legambiente.it/contenuti/dossier/ecosistema-urbano-2007

  6. Forte, F., Granata, M.F., Nesticò, A.: A prioritisation model aiding for the solution of illegal buildings problem. In: Gervasi, O., et al. (eds.) ICCSA 2016. LNCS, vol. 9786, pp. 193–206. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-42085-1_15

    Chapter  Google Scholar 

  7. Hollis, G.E.: The effects of urbanization on floods of different recurrence intervals. Water Resour. Res. 11(3), 431–435 (1975)

    Article  Google Scholar 

  8. Huang, G.: A revisit to impact of urbanization on flooding. In: Huang, G., Shen, Z. (eds.) Urban Planning and Water-related Disaster Management. Strategies for Sustainability. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-90173-2_4

    Chapter  Google Scholar 

  9. Karathanassi, V., Iossifidis, C., Rokos, D.: Remote sensing methods and techniques as a tool for the implementation of environmental legislation. The Greek Forest Law case study. Int. J. Remote Sens. 24(1), 39–51 (2003). https://doi.org/10.1080/01431160305004

    Article  Google Scholar 

  10. Kundzewicz, Z.W., et al.: Assessing river flood risk and adaptation in Europe - review of projections for the future. Mitig. Adapt. Strat. Glob. Change 15, 641–656 (2010). https://doi.org/10.1007/s11027-010-9213-6

    Article  Google Scholar 

  11. Li, G.F., et al.: Impact assessment of urbanization on flood risk in the Yangtze River Delta. Stoch. Environ. Res. Risk Assess. 27, 1683–1693 (2013). https://doi.org/10.1007/s00477-013-0706-1

    Article  Google Scholar 

  12. Mukherjee, D.: Effect of urbanization on flood - a review with recent flood in Chennai (India). Int. J. Eng. Sci. Res. Technol. 5(7), 1–5 (2016)

    Article  Google Scholar 

  13. Nirupama, N., Simonovic, S.P.: Increase of flood risk due to urbanisation: a canadian example. Nat. Hazards 40, 25–41 (2007). https://doi.org/10.1007/s11069-006-0003-0

    Article  Google Scholar 

  14. Prathap, G. Afanasyev, I.: Deep learning approach for building detection in satellite multispectral imagery. In: International Conference on Intelligent Systems (IS) (2018 )

    Google Scholar 

  15. Shetty, A.R., Krishna Mohan, B.: Building extraction in high spatial resolution images using deep learning techniques. In: Gervasi, O., et al. (eds.) ICCSA 2018. LNCS, vol. 10962, pp. 327–338. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95168-3_22

    Chapter  Google Scholar 

  16. Singhal, S., Radhika, S.: Automatic detection of buildings from aerial images using color invariant features and canny edge detection. Int. J. Eng. Trends Technology (IJETT) 11(8), 393–396 (2014)

    Article  Google Scholar 

  17. Yang, L., et al.: Research of illegal building monitoring system construction with 3S integration technology. In: 2nd International Conference on Information Science and Engineering, pp. 3908–3911 (2010)

    Google Scholar 

  18. Zhu, D., Fan, J.: IBMDCH: illegal building monitoring in digital city based on HPC. In: Proceedings of SPIE 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments, p. 71451A, 3 November 2008. https://doi.org/10.1117/12.813024

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Correspondence to Paolino Di Felice .

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Di Felice, P. (2019). Metrics to Rank Illegal Buildings. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11620. Springer, Cham. https://doi.org/10.1007/978-3-030-24296-1_4

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  • DOI: https://doi.org/10.1007/978-3-030-24296-1_4

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