Mapping the quality of life experience in Alfama: a case study in Lisbon, Portugal.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

The International Multilateral System: Imperatives of Change, Potential Scenarios and Suggestions for the Future

Thesis presented to satisfy the necessary requirements for obtaining a PhD degree in International Relation with specialization in Globalization and the Environment,

Location-based Marketing: the academic framework

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

ISEGI-NOVA AR Project - Augmented Reality Aplied to the Universidade Nova de Lisboa

Project work presented as a partial requirement to obtain a Master Degree in Information Management

Data-centric concurrency control on the java programming language

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Structured products in the current low interest rate environment

Directed Research Internship

The effectiveness of the “Processo Especial de Revitalização” as an instrument of corporate restructuring in the context of the current economic crisis

This work project intends to evaluate the effectiveness of the Portuguese Government’s strategy to promote the orderly deleveraging of the corporate sector in the context of the current economic crisis. The recommendations of the Troika and the commitments assumed under the Memorandum of Understanding signed by the Government in 2011 required the creation of formal processes to avoid disorderly deleveraging. Conclusions and recommendations were drawn based on past experiences of large-scale corporate restructuring strategies in other countries and on the analysis of financial and statistical data on companies applying for “Programa Especial de Revitalização”.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.