Alessandro Battistini

GIS techniques for regional-scale landslide susceptibility assessment: the Sicily (Italy) case study

This study describes the assessment of landslide susceptibility in Sicily (Italy) at a 1:100,000 scale using a multivariate logistic regression model. The model was implemented in a GIS environment by using the ArcSDM (Arc Spatial Data Modeller) module, modified to develop spatial prediction through regional data sets. A newly developed algorithm was used to automatically extract the detachment area from mapped landslide polygons. The following factors were selected as independent variables of the logistic regression model: slope gradient, lithology, land cover, a curve number derived index and a pluviometric anomaly index. The above-described configuration has been verified to be the best one among others employing from three to eight factors. All the regression coefficients and parameters were calculated using selected landslide training data sets. The results of the analysis were validated using an independent landslide data set. On an average, 82% of the area affected by instability and 79% of the not affected area were correctly classified by the model, which proved to be a useful tool for planners and decision-makers.

Updating EWS rainfall thresholds for the triggering of landslides

In this paper, the updating of rainfall thresholds for landslide early warning systems (EWSs) is presented. Rainfall thresholds are widely used in regional-scale landslide EWSs, but the efficiency of those systems can decrease during the time, so a periodically updating should be required to keep their functionality. The updating of 12 of the 25 thresholds used in the EWS of Tuscany region (central Italy) is presented, and a comparison between performances of new and previous thresholds has been made to highlight the need of their periodical update. The updating has been carried out by collecting ca. 1200 new landslide reports (from 2010 to March 2013) and their respective rainfall data, collected by 332 rain gauges. The comparison has been made by the use of several statistical indexes and showed a marked increasing in the performances of the new thresholds with respect to previous ones.

ES4LUCC: A GIS-tool for remotely monitoring landscape dynamics

Given the potential impacts of land cover changes on surface processes, accurate mapping of landscape dynamics is a crucial task in environmental monitoring. The use of commercial software for remote sensing of landscape changes requires appropriate expertise in sensor technology and computing resources that are not always available to decision makers. This paper presents the development of an experimental prototype of a lightweight and user-friendly GIS tool - ES4LUCC - a semiautomatic software for change detection and classification of land use/cover. The tool is based on image processing techniques applied on multi-temporal remotely sensed spectral and surface model data. The GIS-based tiling approach allows to non-specialists of remote sensing to manage high-dimensional data even from low performance computing platforms. The paper synthesizes the implemented digital image processing that form the basis of ES4LUCC, including data correction, classification and change detection, map refinements. It also describes the software architecture, the main IDL modules and the integration with GIS through a tight coupling approach and.dll calling functions. The main modelling process is controlled through a powerful GUI developed as part of the ArcMap component of ESRI ArcGIS. The software is tested by using bi-temporal color-infrared ADS40 and Light detection and ranging data acquired on a 80-km transect of the Marecchia river (Italy). The outputs of ES4LUCC give an understanding of the natural- and human-induced surface processes, such as urban planning, agricultural and forest practices, fluvial dynamics and slope instability. The model provides reliable maps (90.77% overall classification accuracy) that represent useful layers for environmental landscape management.

A Cost Effective Methodology for the Rapid Evaluation of the Flood Susceptibility Along Anthropized Rivers

On the basis of the recent experience over the perifluvial areas of the Arno river (Italy), a cost effective approach is proposed to make a preliminary assessment of the flood susceptibility along urbanized rivers. This method encompass two operative phases: a rapid mapping of all the most important natural and artificial elements connected to the hydraulic risk and a reasoned analysis of the collected information with some topographic data that are usually stored in the public offices. The first step includes a field survey using a GPS (global positioning system) device in Real Time Kinematic (RTK) mode and the developing of a local geoid model whose application allows to convert the measured ellipsoidal heights in orthometric heights affected with errors ≤5 cm. Consequently a properly structured GIS geodatabase can be built in order to visualize the spatial distribution of the mapped elements and to store the most important technical data. The second step includes some analyses that allow to define all the most detailed implications for the hydraulic risk in urban and suburban areas. In particular the combination of the previously obtained orthometric heights with the available flow levels data for various return periods is able to produce the preliminary evaluation of the most dangerous dikes in terms of overflowing. Such result, joined to the surface water flow model of the urbanized perifluvial areas which relies on the processing of digital terrain data coming from LIDAR acquisitions, provides significant flood susceptibility scenarios.

A Regional Real Time Landslide Warning System Based on Spatially Variable Rainfall Thresholds

In the Tuscany region (23,000 km2, Central Italy) landslides triggered by rainfall are a recurring phenomenon. We set up a regional warning system for the prediction and monitoring of the occurrence of landslides, which is based on statistical intensity–duration rainfall thresholds. Since a single regional threshold would be affected by a too large uncertainty, the region was partitioned into 25 alert zones and for each of them an independent set of thresholds was defined analyzing with an automated and objective procedure the rainfall measurements connected to the triggering of 2,132 past landslides.

Definition of a Fully Functional EWS Based on Rainfall Thresholds, the Case of Study of Tuscany Region

Open image in new window In this paper the set-up of a fully functional landslide warning system, based on rainfall thresholds, is described. This work was developed in Tuscany region (Italy), an area characterized by a heterogeneous distribution of relieves and rainfalls. The work started with the initial definition of a single set of rainfall thresholds, but it resulted to be ineffective to EWS purposes. Then a software capable to analyze several rainfall events in short time was developed, in order to overcome the problem of the subjectivity of the analyses. Once the thresholds were defined, a WebGis-based warning system was developed. This system can use both real time and forecasting rainfall data and identifies the most hazardous rainfall of each rain event. The last step of this work was the updating of the thresholds using an enhanced calibration dataset, to enhance the performances of the EWS and to account for the changes on territory and on rainfall distribution.

Clean and renewable energy from the Arno River: a feasibility study in the Province of Florence (northern Italy)

During a joint project between the Provincia di Firenze Administration and the Earth Sciences Department of the University of Firenze, the Arno riverbed was studied from the terminal portion of the Upper Valdano up to the Middle Valdarno (about 75 km). In particular, we analysed the preservation status of the existing weirs, which are nowadays the most important hydraulic works as concern the profile riverbed conservation and the fluvial dynamics. Such research was oriented to perform a practical analysis useful for a complete recovery of the hydraulic functionality and also for a possible renovation of some structures in order to produce clean electricity, following the current sensitivity in many national and international institutions. This analysis resulted in the determination of a different degree of feasibility, identifying from a technical point of view the most suitable weir and its annex for a quick recovery intervention and highlighting their economic impact on potential investors that might be attracted to the economic income related to the sale of electricity to the local network.

Application of GIS Techniques for Landslide Susceptibility Assessment at Regional Scale

We evaluated the landslide susceptibility in Sicily region (Italy) (25,000 km2) using a multivariate Logistic Regression model. The susceptibility model was implemented in a GIS environment by using ArcSDM (Arc Spatial Data Modeller) to develop spatial prediction models through regional datasets. A newly developed algorithm was used to automatically extract the scarp area from the whole landslide polygon. From the many susceptibility factors which influence landslide occurrence, on the basis of detailed analysis of the study area and univariate statistical analysis, the following factors were chosen: slope gradient, lithology, land cover, a curve number derived index and a pluviometric anomaly index. All the regression logistic coefficients and parameters were calculated using a selected landslide training dataset. Through the application of the logistic regression modelling technique the final susceptibility map was derived for the whole area. The results of the analysis were validated using an independent landslide dataset. On average, the 81 % of the area affected by instability and the 80 % of the area not affected by instability was correctly classified by the model.