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.

Application of NMR RDC’s, relaxation and self-diffusion for the study of dynamic processes of small molecules in solution

Spin-lattice Relaxation, self-Diffusion coefficients and Residual Dipolar Couplings (RDC’s) are the basis of well established Nuclear Magnetic Resonance techniques for the physicochemical study of small molecules (typically organic compounds and natural products with MW < 1000 Da), as they proved to be a powerful and complementary source of information about structural dynamic processes in solution. The work developed in this thesis consists in the application of the earlier-mentioned NMR techniques to explore, analyze and systematize patterns of the molecular dynamic behavior of selected small molecules in particular experimental conditions. Two systems were chosen to investigate molecular dynamic behavior by these techniques: the dynamics of ion-pair formation and ion interaction in ionic liquids (IL) and the dynamics of molecular reorientation when molecules are placed in oriented phases (alignment media). The application of NMR spin-lattice relaxation and self-diffusion measurements was applied to study the rotational and translational molecular dynamics of the IL: 1-butyl-3-methylimidazolium tetrafluoroborate [BMIM][BF4]. The study of the cation-anion dynamics in neat and IL-water mixtures was systematically investigated by a combination of multinuclear NMR relaxation techniques with diffusion data (using by H1, C13 and F19 NMR spectroscopy). Spin-lattice relaxation time (T1), self-diffusion coefficients and nuclear Overhauser effect experiments were combined to determine the conditions that favor the formation of long lived [BMIM][BF4] ion-pairs in water. For this purpose and using the self-diffusion coefficients of cation and anion as a probe, different IL-water compositions were screened (from neat IL to infinite dilution) to find the conditions where both cation and anion present equal diffusion coefficients (8% water fraction at 25 ºC). This condition as well as the neat IL and the infinite dilution were then further studied by 13C NMR relaxation in order to determine correlation times (c) for the molecular reorientational motion using a mathematical iterative procedure and experimental data obtained in a temperature range between 273 and 353 K. The behavior of self-diffusion and relaxation data obtained in our experiments point at the combining parameters of molar fraction 8 % and temperature 298 K as the most favorable condition for the formation of long lived ion-pairs. When molecules are subjected to soft anisotropic motion by being placed in some special media, Residual Dipolar Couplings (RDCs), can be measured, because of the partial alignment induced by this media. RDCs are emerging as a powerful routine tool employed in conformational analysis, as it complements and even outperforms the approaches based on the classical NMR NOE or J3 couplings. In this work, three different alignment media have been characterized and evaluated in terms of integrity using 2H and 1H 1D-NMR spectroscopy, namely the stretched and compressed gel PMMA, and the lyotropic liquid crystals CpCl/n-hexanol/brine and cromolyn/water. The influence that different media and degrees of alignment have on the dynamic properties of several molecules was explored. Different sized sugars were used and their self-diffusion was determined as well as conformation features using RDCs. The results obtained indicate that no influence is felt by the small molecules diffusion and conformational features studied within the alignment degree range studied, which was the 3, 5 and 6 % CpCl/n-hexanol/brine for diffusion, and 5 and 7.5 % CpCl/n-hexanol/brine for conformation. It was also possible to determine that the small molecules diffusion verified in the alignment media presented close values to the ones observed in water, reinforcing the idea of no conditioning of molecular properties in such media.

UAV - based imagery processing using structure from motion and remote sensing technology

With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.

Fatigue life assessment of endodontic instruments subjected to multi planar curvature

This present study aimed to investigate the fatigue life of unused (new) endodontic instruments made of NiTi with control memory by Coltene™ and subjected to the multi curvature of a mandibular first molar root canal. Additionally, the instrument‟s structural behaviour was analysed through non-linear finite element analysis (FEA). The fatigue life of twelve Hyflex™ CM files was assessed while were forced to adopt a stance with multiple radius of curvature, similar to the ones usually found in a mandibular first molar root canal; nine of them were subjected to Pecking motion, a relative movement of axial type. To achieve this, it was designed an experimental setup with the aim of timing the instruments until fracture while worked inside a stainless steel mandibular first molar model with relative axial motion to simulate the pecking motion. Additionally, the model‟s root canal multi-curvature was confirmed by radiography. The non-linear finite element analysis was conducted using the computer aided design software package SolidWorks™ Simulation, in order to define the imposed displacement required by the FEA, it was necessary to model an endodontic instrument with simplified geometry using SolidWorks™ and subsequently analyse the geometry of the root canal CAD model. The experimental results shown that the instruments subjected to pecking motion displayed higher fatigue life values and higher lengths of fractured tips than those with only rotational relative movement. The finite element non-linear analyses shown, for identical conditions, maximum values for the first principal stress lower than the yield strength of the material and those were located in similar positions to the instrument‟s fracture location determined by the experimental testing results.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.