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Autologistic modelling of susceptibility to landsliding in the Central Apennines, Italy

Autologistic modelling of susceptibility to landsliding in the Central Apennines, Italy
Autologistic modelling of susceptibility to landsliding in the Central Apennines, Italy
In previous research, a logistic regression of landslide occurrence on several explanatory variables was fitted and used to map landslide susceptibility for a small area in the central Apennines, Italy. Here, the spatial dependence or spatial correlation in the residuals from the fitted regression model was accounted for by inserting an autocovariate into the model. The autocovariate was estimated by applying a Gibbs sampler to the susceptibilities for neighbouring pixels. As in any landslide susceptibility analysis, accuracy was difficult to assess because of the requirement for data on future landslides. However, by comparing the ordinary logistic model to the autologistic model obtained on the same set of data, it was possible to assess the influence of the autocovariate. The autocovariate rendered the model simpler because several variables lost their significance and were, therefore, omitted from the model. Further, areas of high landslide susceptibility estimated from the autologistic model were geographically clustered, as one would expect, and this may be advantageous in terms of (i) interpreting the model and (ii) displaying the results to non-experts
landslide susceptibility, logistic regression, autologistic regression, spatial scale
0169-555X
55-64
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Massari, R.
4d973214-aebb-4ff7-9cc2-136c8ccf1d2a
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Massari, R.
4d973214-aebb-4ff7-9cc2-136c8ccf1d2a

Atkinson, P.M. and Massari, R. (2011) Autologistic modelling of susceptibility to landsliding in the Central Apennines, Italy. Geomorphology, 130 (1-2), 55-64. (doi:10.1016/j.geomorph.2011.02.001).

Record type: Article

Abstract

In previous research, a logistic regression of landslide occurrence on several explanatory variables was fitted and used to map landslide susceptibility for a small area in the central Apennines, Italy. Here, the spatial dependence or spatial correlation in the residuals from the fitted regression model was accounted for by inserting an autocovariate into the model. The autocovariate was estimated by applying a Gibbs sampler to the susceptibilities for neighbouring pixels. As in any landslide susceptibility analysis, accuracy was difficult to assess because of the requirement for data on future landslides. However, by comparing the ordinary logistic model to the autologistic model obtained on the same set of data, it was possible to assess the influence of the autocovariate. The autocovariate rendered the model simpler because several variables lost their significance and were, therefore, omitted from the model. Further, areas of high landslide susceptibility estimated from the autologistic model were geographically clustered, as one would expect, and this may be advantageous in terms of (i) interpreting the model and (ii) displaying the results to non-experts

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More information

e-pub ahead of print date: 12 March 2011
Published date: July 2011
Keywords: landslide susceptibility, logistic regression, autologistic regression, spatial scale
Organisations: Global Env Change & Earth Observation

Identifiers

Local EPrints ID: 202303
URI: https://eprints.soton.ac.uk/id/eprint/202303
ISSN: 0169-555X
PURE UUID: 59d71678-b63f-4e84-912a-87336e271871
ORCID for P.M. Atkinson: ORCID iD orcid.org/0000-0002-5489-6880

Catalogue record

Date deposited: 04 Nov 2011 15:25
Last modified: 29 Oct 2019 02:06

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