Papers by Massimiliano Pittore
Earthquake Spectra, 2018
The seismological community acknowledges the essential contribution of macroseismic assessment to... more The seismological community acknowledges the essential contribution of macroseismic assessment to the compilation of the seismic catalogs used for seismic hazard assessment. Furthermore, macroseismic observations are routinely employed by civil protection authorities in the aftermath of damaging events to improve their decision making. In this paper, we describe a novel methodology for the rapid, probabilistic estimation of macroseismic intensity in the epicentral area of a major event according to the European Macroseismic scale. The methodology includes mobile mapping and a collaborative online platform for rapid post earthquake reconnaissance. A Bayesian scheme is proposed to integrate direct damage observations and prior information, allowing consideration of ancillary data and expert judgment. According to a feasibility study carried out in the area affected by the 2016 Amatrice (Central Italy) earthquake, the proposed methodology should provide a reliable estimation of intensity, efficiently integrating further post earthquake building damage surveys.
Frontiers in Built Environment, 2018
Earthquake exposure describes the assets that are exposed to seismic activity and are susceptible... more Earthquake exposure describes the assets that are exposed to seismic activity and are susceptible to be damaged. In seismic risk applications, it mostly refers to the residential and commercial building portfolios, although in general may also include transport infrastructure and lifelines. Providing an efficient description of a complex urban environment in terms of the structural characteristics of buildings related to their seismic vulnerability is challenging, considering the variety of building practices, materials and configurations. A common approach entails the use of pre-defined building typologies, but this may introduce a bias in the resulting models. Faceted taxonomies have been recently introduced to provide a standardized description of buildings using a rich set of basic attributes, but cannot be used directly for risk-related applications. We argue that a bottom-up approach to exposure modeling might prove instrumental in increasing the quality and reliability of risk assessment, and propose hereby a novel score-based methodology to define and assign building classes to unclassified buildings in a sound and transparent way. The approach can be adopted for standard building classifications as well as for original typologies that may be more efficient in capturing the specific features of the building stock. The proposed methodology efficiently decouples the collection of buildings observations, typical of surveying activities, from the assignment of risk-aimed building classes, and provides a useful tool to practitioners and engineers involved in large-scale earthquake risk assessment. The proposed methodology has been exemplified with a building portfolio collected in France near the geothermal plant of Soultz-sous-Fôrets, and is used to rapidly characterize the seismic exposure of a built environment for induced seismicity applications.
Natural Hazards, 2016
The need for a global approach to natural hazard and risk assessment is becoming increasingly app... more The need for a global approach to natural hazard and risk assessment is becoming increasingly apparent to the disaster risk reduction community. Different natural (e.g. earthquakes, tsunamis, tornadoes) and anthropogenic (e.g. industrial accidents) hazards threaten millions of people every day all over the world. Yet, while hazards can be so different from each other, the exposed assets are mostly the same: populations, buildings, infrastructure and the environment. Exposure should be regarded as a dynamic process, as best exemplified by rapid urbanization, depopulation of rural areas and all of the changes associated with the actual evolution of the settlements themselves. The challenge is thus to find innovative, efficient methods to collect, organize, store and communicate exposure data on a global scale, while also accounting for its inherent spatio-temporal dynamics. The aim of this paper is to assess the challenge of implementing an exposure model at a global scale, suitable for different geo-hazards within a dynamic and scalable framework. In this context, emerging technologies, from remote sensing to crowd-sourcing, are assessed for their usability in exposure modelling and a road map is laid out towards a global exposure model that will continuously evolve over time by the continuous input and updating of data, including the consideration of uncertainties. Such an exposure model would lay the basis for global vulnerability and risk assessments by providing reliable, standardized information on the exposed assets across a range of different hazards.
PhD Thesis Proposal: Dynamic Events in Image Sequences
ABSTRACT
Towards a Multi-Resolution Model of Seismic Risk in Central Asia. Challenge and perspectives
ABSTRACT
We propose an integrated approach to estimating building inventory for seismic vulnerability asse... more We propose an integrated approach to estimating building inventory for seismic vulnerability assessment, which can be applied to different urban environments and be efficiently scaled depending on the desired level of detail. The approach employs a novel multi-source method for evaluating structural vulnerability-related building features based on satellite remote sensing and ground-based omnidirectional imaging. It aims to provide a comparatively cost-and time-efficient way of inventory data capturing over large areas. The latest image processing algorithms and computer vision techniques are used on multiple imaging sources within the framework of an integrated sampling scheme, where each imaging source and technique is used to infer specific, scale-dependent information. Globally available low-cost data sources are preferred and the tools are being developed on an open-source basis to allow for a high degree of transferability and usability. An easily deployable omnidirectional camerasystem is introduced for ground-based data-capturing. After a general description of the approach and the developed tools and techniques, preliminary results from a first application to our study area, Bishkek, Kyrgyzstan, are presented.
A modular image processing chain for feature extraction from multi-spectral satellite images
Following an object-based approach to image analysis we propose an automated image processing cha... more Following an object-based approach to image analysis we propose an automated image processing chain to extract objects of interest from high resolution multi-spectral satellite images. The processing chain is based on open-source solutions and consists of several modules including image segmentation, segmentation optimization and evaluation, feature selection and machine learning based classification. An automated extraction of detailed built-up masks from Quickbird and WorldView-2 images is presented to illustrate the approach. In an initial processing stage an efficient graph-based image segmentation algorithm is deployed and combined with a specifically developed multi-scale optimization and evaluation procedure. The optimization procedure iteratively merges a hierarchical set of segmentations into a single multi-scale segmentation based on the mean percentage difference of the weighted brightness values between sub-segments and super-segments. A supervised evaluation of segmenta...
Towards a cross-border exposure model for the Earthquake Model Central Asia
This work provides an insight into the development of the first harmonized exposure model for Cen... more This work provides an insight into the development of the first harmonized exposure model for Central Asia. The model was derived in the frame of the Earthquake Model Central Asia (EMCA) project, which is the regional initiative for Central Asia to the Global Earthquake Model (GEM). The EMCA exposure model combines commonly used data sources and acquisition techniques (e.g., rapid visual screening) with novel rapid assessment approaches (e.g., satellite remote sensing and omnidirectional imaging) in the framework of an integrated sampling scheme and stores the data in a multi-resolution spatio-temporal database. The exposure model implements a newly developed building typology, harmonized for the five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan) and follows the international building taxonomy of the GEM. Emphasis is given to the multi-scale nature and the temporal dynamics of exposure data. Results from a selected urban area are provided ...
In this work, the development of an on-site early warning system for Bishkek (Kyrgyzstan) is outl... more In this work, the development of an on-site early warning system for Bishkek (Kyrgyzstan) is outlined. Several low cost sensors equipped with MEMS accelerometers are installed in eight buildings distributed within the urban area. The different sensing units communicate each other via wireless links and the seismic data are streamed in real-time to the data center using internet. Since each single sensing unit has computing capabilities , software for data processing can be installed to perform decentralized actions. In particular, each sensing unit can perform event detection task and run software for on-site early warning. If a description for the vulnerability of the building is uploaded in the sensing unit, this piece of information can be exploited to introduce the expected probability of damage in the early-warning protocol customized for a specific structure.
The Capabilities of Earth Observation to Contribute along the Risk Cycle
Earthquake Hazard, Risk and Disasters, 2014
ABSTRACT The complexity of earthquake events and their manifold effects uncovers a strong niche f... more ABSTRACT The complexity of earthquake events and their manifold effects uncovers a strong niche for interdisciplinary and multidisciplinary analyses. Remote sensing data and methods are nowadays widely deployed to contribute information along the risk cycle. In this chapter, we document these contributions and discuss limitations simultaneously by means of an in-depth literature survey and presentation of selected examples. These include hazard-centered analysis such as site characterization and quantification of surface deformations in preevent and postevent applications. Furthermore, preevent seismic vulnerability-centered assessments of the built and natural environment are presented, which build upon the capability of remote sensing to map elements at risk, area wide. Lastly, damage assessment for postevent applications is discussed and completed by demonstrating recovery monitoring capabilities.
Remote Sensing, 2014
In this study, a classification and performance evaluation framework for the recognition of urban... more In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS) and very high resolution (WorldView-2, Quickbird, Ikonos) multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm's performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based), have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.
A Multiscale Exposure Model for Seismic Risk Assessment in Central Asia
Seismological Research Letters, 2014
ABSTRACT This work provides an insight into the development of the first harmonized exposure mode... more ABSTRACT This work provides an insight into the development of the first harmonized exposure model for Central Asia. The model was derived in the frame of the EMCA project, which is the regional initiative for Central Asia to the Global Earthquake Model (GEM). The EMCA exposure model combines commonly used data sources and acquisition techniques (e.g., rapid visual screening) with novel rapid assessment approaches (e.g., satellite remote sensing and omnidirectional imaging) in the framework of an integrated sampling scheme and stores the data in a multi-resolution spatio-temporal database. The exposure model implements a newly developed building typology, harmonized for the five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan) and follows the international standard taxonomy and ontology of the GEM. Emphasis is given to the multi-scale nature and the temporal dynamics of exposure data. Results from selected urban areas are provided to illustrate the current state of the continuously updated exposure model.
Natural Hazards and Earth System Sciences Discussions, 2013
Both aleatory and epistemic uncertainties associated with different sources and components of ris... more Both aleatory and epistemic uncertainties associated with different sources and components of risk (hazard, exposure, vulnerability) are present at each step of seismic risk assessments. All individual sources of uncertainty contribute to the total uncertainty, which might be very high and, within the decision-making context, may therefore lead to either very conservative and expensive decisions or the perception of considerable risk. When anatomizing the structure of the total uncertainty, it is therefore important to propagate the different individual uncertainties through the computational chain and to quantify their contribution to the total value of risk. The present study analyses different uncertainties associated with the hazard, vulnerability and loss components by the use of logic trees. The emphasis is on the analysis of epistemic uncertainties, which represent the reducible part of the total uncertainty, including a sensitivity analysis of the resulting seismic risk assessments with regard to the different uncertainty sources. This investigation, being a part of the EU FP7 project MATRIX (New Multi-Hazard and Multi-Risk Assessment Methods for Europe), is carried out for the example of, and with reference to, the conditions of the city of Cologne, Germany, which is one of the MATRIX test cases. At the same time, this particular study does not aim to revise nor to refine the hazard and risk level for Cologne; it is rather to show how large are the existing uncertainties and how they can influence seismic risk estimates, especially in less wellstudied areas, if hazard and risk models adapted from other regions are used.
2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
Rapid, often unplanned urbanization, taking place in earthquake-prone areas represents an increas... more Rapid, often unplanned urbanization, taking place in earthquake-prone areas represents an increasing challenge for planners and decision makers. Quantification of exposed building stock and its seismic vulnerability can become infeasible with the standard approaches, and aggregated estimates are often unsuitable for a proper risk mitigation. We propose a new approach to a rapid, yet reliable, first estimate of vulnerability of the exposed stock at city-block spatial scale. Latest image processing algorithms as well as computer vision and Geographical Information System (GIS) techniques are used on multiple imaging sources in the framework of an integrated sampling scheme. Each imaging source and technique is used to infer specific, scale-dependent information. An easily deployable omnidirectional camera-system is introduced for ground-based data-capturing. Preliminary results from a first application to the town of Bishkek, Kyrgyzstan, are shown.
Visual Dynamic Event Recognition with Support Vector Machines
MAPPING GLOBAL EXPOSURE FROM SPACE: A REVIEW OF EXISTING PRODUCTS AND COMPARISON OF TWO NEW LAYERS OF GLOBAL URBAN EXTENT
Thinking Fast Thinking Slow: bridging the gap between research and practice in disaster recovery
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Papers by Massimiliano Pittore