This work evaluates the influence of land use and land cover (LUC) data with different properties on the landslide susceptibility zonation of the road network in the Zêzere watershed (Portugal). The information value method was used to assess the landslide susceptibility using two models: one including detailed LUC data (the Portuguese Land Cover Map – COS) and the other including more generalized LUC data (the CORINE Land Cover – CLC). A set of fixed independent layers was considered as landslide predisposing factors (slope angle, slope aspect, slope curvature, slope-over-area ratio, soil, and lithology) while COS and CLC were used to find the differences in the landslide susceptibility zonation. A landslide inventory was used as a dependent layer, including 259 shallow landslides obtained from the photointerpretation of orthophotos from 2005, and further validated in three sample areas. The landslide susceptibility maps were assigned to the road network data and resulted in two landslide susceptibility road network maps. The models' performance was evaluated with prediction and success rate curves and the area under the curve (AUC). The landslide susceptibility results obtained in the two models present a high accuracy in terms of the AUC (>90 %), but the model with more detailed LUC data (COS) produces better results in the landslide susceptibility zonation on the road network with the highest landslide susceptibility.

Understanding the processes of land use and land cover changes (LUCC) and the associated driving forces is important for achieving sustainable development. This paper presents the LUCC in Portugal at the regional level (NUTS II) from 1995 to 2010 and discusses the main driving forces and implications associated with these LUCC. The main objectives of this work are: (a) to quantify the land use and land cover (LUC) types (level I of LUC cartography) by NUT II in Portugal for the years 1995, 2007 and 2010; (b) to assess the spatio-temporal LUCC; and (c) to identify and discuss the main driving forces of LUCC and corresponding implications based on correlations and Principal Components Analysis. The results revealed large regional and temporal LUCC and further highlighted the different and sometimes opposite time trends between neighboring regions. By associating driving forces to LUCC, different influences at the regional level were observed, namely LUCC into agriculture land derived from the construction of dams (Alentejo region), or the conversion of coniferous forest into eucalypt forest (Centre region) associated with increased gross value added (GVA) and employment in industry and forestry. Temporal differentiation was also observed, particularly in the settlements that expanded between 1995 and 2007 due to the construction of large infrastructures (e.g., highways, industrial complexes, or buildings), which is reflected on employment in industry and construction and respective GVA. However, certain LUCC have implications, particularly in energy consumption, for which different behavior between regions can be highlighted in this analysis, but also on land-use sustainability.

Vegetation recovery after the large wildfires that occurred in central Portugal in 2017 is assessed in the present study. These wildfires had catastrophic consequences, among which were human losses and a vast extent of forest devastation. Landsat 8 OLI images were used to obtain the land use and cover (LUC) classification and to determine the Normalized Burned Ratio index (NBR) for different times. NBR results were used to determine the difference between the NBR (dNBR) before the fire (pre-fire) and after the fire (post-fire), and the results obtained were cross-checked with the LUC. The dNBR results were cross-referenced with biophysical data to identify the characteristics of the most important burned areas in need of vegetative recovery. The results showed the spatial differentiation in vegetation recovery, highlighting different factors in this process, in particular the type of vegetation (the predominant species and bank of seeds available), the biophysical characteristics of burned areas (for example, the soil type in burned areas), the continentality gradient, and the climate conditions. The vegetation recovery was differentiated by time according to the species present in the burned areas pre-fire. In general, shrubland recovery was faster than that of tree species, and the recovery was more marked for species that were regenerated by the rhizomes after fire. The recovery process was also influenced by the season in the study area. It was more efficient in the spring and at the beginning of the summer, highlighting the importance of optimal conditions needed for vegetation regeneration, such as the temperature and precipitation (soil humidity and water availability for growing plants). The results of this research are important to forest planning: the definition of the strategies for the ecosystems’ recovery, the adoption of preventive measures to avoid the occurrence of large wildfires, the modification of anthropogenic practices, etc.

Wildfires are responsible for major land use and land cover (LUC) changes. These events are frequent and catastrophic in Portugal and are responsible for great damage and loss of human life. In this study, a map to assess the probability of wildfire occurrence (PWO) in mainland Portugal was created for the period 1975-2017 (first half of 2017). The PWO was obtained by the superimposition of all layers by adding all the burned areas for the total period. It was observed that the occurrences and extent of the burned areas are highly variable from year to year. The PWO map was cross-referenced with LUC geoinformation to evaluate the LUC types that were more affected by the wildfires. The results presented and the PWO maps are important for the management and planning of forest areas and for the creation of guidelines to implement preventive and reactive actions in case of wildfires.