Ricardo A. C. Garcia

Mapping landslide susceptibility using data-driven methods

Most epistemic uncertainty within data-driven landslide susceptibility assessment results from errors in landslide inventories, difficulty in identifying and mapping landslide causes and decisions related with the modelling procedure. In this work we evaluate and discuss differences observed on landslide susceptibility maps resulting from: (i) the selection of the statistical method; (ii) the selection of the terrain mapping unit; and (iii) the selection of the feature type to represent landslides in the model (polygon versus point). The work is performed in a single study area (Silveira Basin - 18.2km2 - Lisbon Region, Portugal) using a unique database of geo-environmental landslide predisposing factors and an inventory of 82 shallow translational slides. The logistic regression, the discriminant analysis and two versions of the information value were used and we conclude that multivariate statistical methods perform better when computed over heterogeneous terrain units and should be selected to assess landslide susceptibility based on slope terrain units, geo-hydrological terrain units or census terrain units. However, evidence was found that the chosen terrain mapping unit can produce greater differences on final susceptibility results than those resulting from the chosen statistical method for modelling. The landslide susceptibility should be assessed over grid cell terrain units whenever the spatial accuracy of landslide inventory is good. In addition, a single point per landslide proved to be efficient to generate accurate landslide susceptibility maps, providing the landslides are of small size, thus minimizing the possible existence of heterogeneities of predisposing factors within the landslide boundary. Although during last years the ROC curves have been preferred to evaluate the susceptibility models performance, evidence was found that the model with the highest AUC ROC is not necessarily the best landslide susceptibility model, namely when terrain mapping units are heterogeneous in size and reduced in number.

Structure and Characteristics of Landslide Input Data and Consequences on Landslide Susceptibility Assessment and Prediction Capability

The main objective of this study is to assess the influence of landslide representation format (i.e. landslide represented as points or areas) in landslide susceptibility results, especially at scales that can directly interfere with spatial planning. For the study area of Rio Grande da Pipa basin, Arruda dos Vinhos, Portugal, the Information Value method is used to statistically integrate two rotational slides groups (deep and shallow) and a dataset of independent predisposing geo-environmental factors. For both landslide groups, landslides were represented by: (i) the landslide area; (ii) the landslide depletion area; (iii) the centroid of landslide area; and (iv) the centroid of landslide depletion area. Additionally each group was randomly partitioned in two equivalent landslide sub-groups (50–50%), one for modeling and the other for independent validation of the landslide susceptibility maps. The evaluation of the landslide representation format on the prediction capacity of each landslide susceptibility model was based on Receiving Operating Characteristic curves and in the calculation of Area Under the Curve. As main results this work points out the sensitivity of landslide susceptibility models prediction capability to the landslide representation format. Consistently, for both landslide groups, the better predictive results were achieved by modeling with the landslide depletion area and validating with landslide depletion area and the worst results by modeling with landslide centroid and validating with the landslides area. Furthermore the same hierarchy of landslide representation formats regarding the prediction capability of the landslide susceptibility models was recorded independently of being deep or shallow rotational slide types.

Landslide quantitative risk analysis of buildings at the municipal scale based on a rainfall triggering scenario

ABSTRACT A landslide quantitative risk analysis is applied the municipality of Santa Marta de Penaguião (N of Portugal) to evaluate the risk to which the buildings are exposed, using a vector data model in GIS. Two landslide subgroups were considered: landslide subgroup 1 (event inventory of landslides occurred on January 200)1; and landslide subgroup 2 (inventoried landslides occurred after the 2001 event until 2010). Seven landslide predisposing factors were weighted and integrated using the Information Value Method. The landslide susceptibility model was independently validated and the model performance was expressed by ROC curves. The probability of landslide size was estimated using a probability density function and the landslide hazard scenario was defined using the same landslide rainfall-triggering event. A vulnerability curve was constructed for each type of building considering its structural properties and the proxy of landslide magnitude. The economic value assigned for each building represents an approximated cadastral value. The landslide risk was computed for each building in vector format based on a rainfall triggering scenario and two landslide magnitudes. The probability of occurrence of small landslides is two orders of magnitude higher than the probability of occurrence for large landslides, which explains the higher risk generated by small landslides, despite of registering.

Integration of Landslide Susceptibility Maps for Land Use Planning and Civil Protection Emergency Management

Landslides are one of the most relevant geomorphological hazards in Portugal, by the high levels of people affected, destruction of assets and disruption of economic and social activities. Regarding the Portuguese territorial land use planning and emergency management, regulation, practice, prevention and risk management have been promoted in different ways. In Portugal, the areas susceptible to landslides are included in the ‘National Ecological Reserve’, which is a public utility restriction legal figure that rules the land use planning at the municipal level. In addition, the Municipal Emergency Plans include landslide susceptibility maps that are combined with the map of the exposed elements, allowing the assessment of exposure to landslides. This study is applied to the Loures municipality located to the north of Lisbon. In this municipality 621 landslides registered in a landslide inventory (rotational slides, deep-seated translational slides and shallow translational slides) that affected 1,469,577 m2 (0.87%) of the Loures territory. The final landslide susceptibility map shows that in Loures municipality 1347 ha are associated to a Very high landslide susceptibility and 2372 ha to High landslide susceptibility, which corresponds both to 22.1% of the entire municipality, and constitutes the larger fraction of the National Ecological Reserve, related to landslides. These areas do not present geomorphological and geotechnical suitability for building structures or infrastructures. From the civil protection and emergency management point of views 34 classes of exposed elements were identified in the municipality, with point, linear and polygonal representations. The elements at risk located in the Very High or High landslide susceptibility classes were summarized and correspond to: high voltage poles; wind turbines; transmission/reception antennas; industrial areas; water tanks; silo; gas station/tank; service area; buildings of educational institutions; worship buildings; buildings of electricity facilities; regular buildings; gas pipeline; motorways; national roads; and municipal roads.

Form-Ose Post Graduate Training School - Cerg

lizados do Conselho da Europa, organizou, entre 14 e 19 de Setembro de 2004, mais um Curso de Pos-Graduacao, inserido no programa FORM-OSE (European Training Programme on Risk Sciences) do Conselho da Europa. O curso, intitulado Living with Hydro-Geomorphological Risks: from Theory to Practice, decorreu na Faculdade de Geografia da Universidade Louis Pasteur (Estrasburgo) com o apoio do Observatorio das Ciencias da Terra de Estrasburgo e da International Association of Geomorphology (IAG). Os alunos seleccionados (24, de entre as 43 candidaturas) revelam a grande internacionalizacao e multidisciplinaridade destes cursos, com 13 paises representados (Quadro 1), sendo a participacao portuguesa de 5 jovens investigadores, 3 dos quais do Centro de Estudos Geograficos da Universidade de Lisboa e 2 do Centro de Vulcanologia e Avaliacao de Riscos Geologicos da Universidade dos Acores. No que diz respeito a sua formacao de base, 40% eram geomorfologos (geografos fisicos e geologos), 25% engenheiros civis, 20% geofisicos e 15% provenientes das areas relacionadas com as ciencias do Ambiente. Quanto as suas habilitacoes, 1 elemento esta a realizar Pos-Doutoramento, 18 sao alunos de Doutoramento, 5 de Mestrado e 1 dedica-se exclusivamente a investigacao. Apesar das diferencas de formacao, o grupo interagiu muito bem, entre si e com os professores, permitindo a partilha de experiencias e a possibilidade de discussoes sobre diversos temas.