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The diversity of geological and geomorphological landscapes in mainland Portugal is responsible for the occurrence of different landslide types. The present chapter illustrates three examples of destructive landslide hazardscapes responsible for recent hillslope evolution: in a granitic context, the Frades landslide, a lethal debris flow; and in sedimentary contexts, the Calhandriz landslide, the biggest rainfall-triggered landslide that occurred in Portugal in the last 50 years, and the Grande da Pipa River basin, the major landslide-prone area within the north of Lisbon region.

In the last decades, Portugal was affected by several geomorphological hazards that produced high levels of destruction and disruption on human activities, particularly due to the inappropriate occupation of areas where natural hazardous phenomena occur. To cope against the consequences of these hazards, a set of legal instruments has been implemented in the last 30–40 years by national initiative or by transposition to the national law of European Directives within the thematic of risk assessment and management. This chapter broadly presents the planning and emergency management legal framework in Portugal, as well as the specific normative instruments for the major geomorphological hazards that influence land use regulation.

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.

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.