Terra Nativa. A relação eco-humana na vida e na obra de Ferreira de Castro

A presente investigação teve o apoio financeiro da FCT, através de uma Bolsa de Doutoramento.

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.

Does companionate love express itself unequally in different organizational forms (private companies, hybrid and non-governmental organizations)?

Although, the word “Love” in organizations is seen as a rare concept, but it has gained importance in management theoretical foundation. This study seeks to explore the companionate love in distinct of organizational forms (Private companies; Social organizations; NGO and IPSS) through interviews. The results propose that it is a tensional concept with a complex dynamic: tension of personal behavior, tension of professional behavior; tension of individual impact and tension of community impact. The love dynamic has common points to all organizations, but its expression depends on the specific form of the organization.