Gheorghe Kucsicsa

Urban Growth in the Bucharest Metropolitan Area: Spatial and Temporal Assessment Using Logistic Regression

AbstractThe Bucharest Metropolitan Area (BMA) is witnessing rapid urban growth under the form of urban sprawl, which leads to a continuous expansion of the city over wider territories beyond its ou...

Geomorphic services for landslide risk evaluation in the RO-RISK Project

The paper presents the steps undertaken within the RO-RISK (Disaster Risk Evaluation at National Level) project with the aim of achieving landslide hazard and risk evaluation at the national level, as well as the close interand transdisciplinary collaboration through the involvement of specialists and stakeholders during the whole research process, the results of which can be assigned to geomorphic services. A common methodology to analyze all the selected risks has been followed within the project, mainly focusing on hazard and impact analyses. At the end, three national and two local scale landslide scenarios have been analyzed into detail in order to provide risk figures as estimations on the location and magnitude of possible physical impacts on the population, the built-up environment and the transportation network, as well as economic and sociopsychological impacts, all of which were needed to finally estimate risk acceptability. Keywords— landslides; risk assessment; geomorphic services; environmental changes; RO-RISK; Romania

Predicting the Potential Distribution of Ailanthus altissima, an Invasive Terrestrial Plant Species in Măcin Mountains National Park (Romania)

Under current global change conditions, invasive species show an increasing tendency to spread over larger areas in close relationship with their triggering environmental driving forces. Current research is seeking to assess the potential distribution of the invasive terrestrial plant species (ITPS) Ailanthus altissima in a natural protected area, the Măcin Mountains National Park (II IUCN category). The protected area is located in the southeastern part of Romania, sheltering a combination of Pontic, steppe, and well-preserved sub-Mediterranean and Balkan forest ecosystems. The authors propose a geographic GIS-based quantitative statistical analysis (potential distribution model, ITPS-PODISMOD) of A. altissima using bivariate analysis that takes into consideration the relationship between variables, such as A. altissima as the dependent variable and its driving factors as independent variables. Concurrently, each driving factor was ranked depending on the relationships between the analysed species and its ecological conditions. Thus, an ITPS-PODISMOD map displaying areas with different potential distribution of A. altissima in relationship to the key environmental driving factors has resulted.