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.

Tectónica da região de Sintra

Photo-interpretation of aerial stereopairs of the Sintra region on the approx. 1/32 000 scale together with field work allowed the production of the present Tectonic Map of the Sintra region. It is now possible to separate structures which resulted from two different tectonic events: one, corresponding to the intrusion of the Late Cretaceous Sintra igneous diapir, and the other the Miocene compressive event, the most important tectonic inversion phase of the Lusitanian Basin. The former are present to the south, southeast and east of the intrusion and within the intrusion itself, affecting the peripheral granites and their contacts with the gabbro-syenite core. These structures comprehend: i) faults and conical fractures striking parallel to the massif boundary, which were intruded by dykes, ii) vertical faults and fractures of two conjugate sets, dextral NNW-SSE and sinistral NNE-SSW. These faults are certainly associated with the E-W striking massif's northwards directed thrust and indicate a N-S oriented horizontal maximum compressive stress. The Miocene compressive event reactivated most of the inherited structures as follows. The NNWSSE faults located on the Sintra southern platform were reactivated as dextral strike slip faults and the E-W thrust along the northern boundary of the massif was also reactivated. This thrust propagated to the east. It also enhanced the asymmetry of the rim-syncline, uplifted the massif and reactivated the NNE-SSW faults as sinistral lateral ramps, which also accommodated vertical throw. The present Tectonic Map of Sintra together with the available geophysical data (MOREIRA, 1984, KULLBERG et al., 1991, SILVA & MIRANDA, 1994) allowed reassessment of the models proposed for the emplacement of the Sintra, Sines and Monchique igneous massifs, which intruded during Late Cretaceous times along the deep dextral NNW-SSE oriented strike slip fault (RIBEIRO et al., 1979; TERRINHA, 1998; TERRINHA & KULLBERG, 1998).

Stochastic modelling of the reservoir lithological and petrophysical attributes. A case study of the Middle East carbonate reservoir

Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)