This thesis analyzes the intensity of tourism in Strakonice and a potential for further development. The analysis was performed first, using computer software ArcGIS and through a personal interview visitors Strakonice. Based on the findings of these analytical solutions have been proposed how to increase the attractiveness of the reference region.

La modélisation de processus complexes peut impliquer un grand nombre de variables ayant entre elles une structure de corrélation compliquée. Par exemple, les phénomènes spatiaux possèdent souvent une forte régularité spatiale, se traduisant par une corrélation entre variables d’autant plus forte que les régions correspondantes sont proches. Le formalisme des graphes pondérés permet de capturer de manière compacte ces relations entre variables, autorisant la formalisation mathématique de nombreux problèmes d’analyse de données spatiales. La première partie du manuscrit se concentre sur la résolution efficace de problèmes de régularisation spatiale, mettant en jeu des pénalités telle que la variation totale ou la longueur totale des contours. Nous présentons une stratégie de préconditionnement pour l’algorithme generalized forward-backward, spécifiquement adaptée à la résolution de problèmes structurés par des graphes pondérés présentant une grande variabilité de configurations et de poids. Nous présentons ensuite un nouvel algorithme appelé cut pursuit, qui exploite les relations entre les algorithmes de flots et la variation totale au travers d’une stratégie de working set. Ces algorithmes présentent des performances supérieures à l’état de l’art pour des tâches d’agrégations de données geostatistiques. La seconde partie de ce document se concentre sur le développement d’un nouveau modèle qui étend les chaînes de Markov à temps continu au cas des graphes pondérés non orientés généraux. Ce modèle autorise la prise en compte plus fine des interactions entre noeuds voisins pour la prédiction structurée, comme illustré pour la classification supervisée de tissus urbains. / Modeling complex processes often involve a high number of variables with anintricate correlation structure. For example, many spatially-localized processes display spatial regularity, as variables corresponding to neighboring regions are more correlated than distant ones. The formalism of weighted graphs allows us to capture relationships between interacting variables in a compact manner, permitting the mathematical formulation of many spatial analysis tasks. The first part of this manuscript focuses on optimization problems with graph-structure dregularizers, such as the total variation or the total boundary size. We first present the convex formulation and its resolution with proximal splitting algorithms. We introduce a new preconditioning scheme for the existing generalized forward-backward proximal splitting algorithm, specifically designed for graphs with high variability in neighbourhood configurations and edge weights. We then introduce a new algorithm, cut pursuit, which used the links between graph cuts and total variation in a working set scheme. We also present a variation of this algorithm which solved the problem regularized by the non convex total boundary length penalty. We show that our proposed approaches reach or outperform state-of-the-art for geostatistical aggregation as well as image recovery problems. The second part focuses on the development of a new model, expanding continuous-time Markov chain models to general undirected weighted graphs. This allows us to take into account the interactions between neighbouring nodes in structured classification, as demonstrated for a supervised land-use classification task from cadastral data.

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The Southeastern Lower Coastal Plain wet pine flats include thousands of acres of jurisdictional wetlands that are economically, socially, and environmentally important. These highly productive forests have been intensively managed as pine plantations for the past few decades. More recently, harvesting and site preparation practices have become a concern among natural resource managers because intensive forestry practices may alter soil physical properties and site hydrology. These alterations could decrease seedling survival, growth, and future site productivity. However, the effects of soil disturbance on long-term site productivity and the effects of amelioration techniques on site hydrology are uncertain. The overall objectives of this study were (1) to characterize disturbed forest soil morphology and physical properties, (2) to assess their impact on the processes that control site hydrology and site productivity, (3) to determine effects of harvesting and site preparation on site hydrology, specifically on the overall hydrological balance and on spatial and temporal patterns of surface water storage. The study site is located in an intensively managed loblolly pine (Pinus taeda L.) plantation in the lower coastal plain of South Carolina. This study was established in winter 1991, and dry- and wet-weather harvesting treatments were installed in summer 1993 and winter 1994, respectively. Bedding and mole channel/bedding treatments were installed in both dry- and wet-harvested plots in fall 1995. Soil profiles were described for a recently disturbed, deeply-rutted area, and 2-year-old deeply-rutted and churned areas, bedded and undisturbed areas. Intact soil core samples and composite loose soil samples were collected from each morphological section for soil physical characterizations. Automated weather station and wells were used to collect continuous climatic and surface water level data since 1996. Surface water levels were monitored monthly on a 20 x 20 m grid of 1-m wells since 1992. Total groundwater heads were determined from differential piezometer measurements at high and low elevation places in each treatment plot. Soil profile descriptions and soil physical property measurements indicated that significant amounts of organic debris were incorporated into the surface horizons, and subsurface soil horizons showed significant soil structural changes and increased redoximorphic features caused by soil disturbance. The disturbed soil layers in recently created traffic ruts consisted of exposed and severely disturbed subsurface soils, but this layer was naturally ameliorated 2 years after the disturbance. Bedding site preparation had little amelioration effects on the physical properties of surface soil horizons because the surface horizons already had some incorporation of organic debris. Overall, the main consequence of bedding in a disturbed wet site was to increase the aerated soil volume. The bedding appeared to have little effect on disturbed subsurface horizons. Groundwater head in the study site was constantly higher than -25 cm during the study period, which caused groundwater inflow when the surface water level was low. Frequent fluctuation of the surface water level and constant water supply from the groundwater probably explain the high productivity of the study site. Results of the annual water balance showed that surface soil water storage changes were very small, and annual precipitation and potential evapotranspiration were approximately equal. Silvicultural practices and minor topography on the study site had significant effects on the water balance because they influenced surface water level. Surface water hydraulic gradient evaluation and multivariate cluster analysis indicated that micro-site hydrology and water flow patterns were significantly altered by wet-weather harvesting and bedding site preparation, but overall site hydrology was not altered. Evaluation of predicted surface water level indicated that micro-topography and precipitation patterns had significant influences on surface water levels during the site establishment period. These results revealed that the hydrologic components of wetland delineation are complex in the wet pine flatwoods. / Ph. D.

Foreign Direct Investment (FDI) in the United States, which predominately occurs in the manufacturing sector, remains critically important for a strong regional and local economy, due to the resulting increase in employment, wages, and tax revenue. Traditionally, local economic development strategies have focused on attracting external manufacturing plants or facilities as the primary route to economic growth, through the expansion of the tax base and/or an increase in employment. In comparison, Sustainable Local Economic Development (SLED) emphasizes the establishment of a minimum standard of living for all and an increase in this standard over time; a reduction in the steady growth in inequality among people; a reduction in spatial inequality; and the promotion and encouragement of sustainable resource use and production (Blakely & Leigh, 2010). These essential SLED principles motivate this study, which will seek to develop a better understanding of whether and how FDI contributes to SLED in terms of its spatial patterns and its impact on middle class earnings. By selecting Georgia as a case study area, this research specifically examines whether and how the location of manufacturing FDI has reduced (or increased) spatial inequality at the intra-state and intra-metropolitan levels. It also identifies whether and how manufacturing FDI has reduced (or increased) inequality among people, focusing on its impact on middle class earnings. This study finds a strong spatial concentration of manufacturing FDI employment in metropolitan areas, particularly in a large metropolitan area, at the intra-state spatial pattern analysis. The results of panel regression analysis suggest that presence of agglomeration economies in metropolitan areas has positively influenced the location of manufacturing FDI jobs. The study also finds a suburbanization pattern of manufacturing FDI employment in the intra-metropolitan spatial pattern analysis. This intra-metropolitan suburbanization of FDI in manufacturing jobs is associated with loss of urban industrial land in the central areas within a large metropolitan area. These uneven distribution patterns of manufacturing FDI jobs indicate increased spatial inequality at both intra-state and intra-metropolitan levels, but the implications of this finding are mixed. Using individual earnings data from the American Community Survey Public Use Microdata Sample files, this study also conducts a quantile regression to estimate the earnings distribution effects that a concentration of manufacturing FDI may have on different earnings groups. The findings both from place-of-work and place-of-residence earnings analysis suggest that manufacturing FDI generally has reduced inequality among people. The concentration of manufacturing FDI in a certain area show the largest distribution effects on area workers in the lower earnings group and residents in the middle earnings group.

This project aims to use temporal and spatial data analysis to express the measured air pollutant concentrations as well as their relation with the aerosol traces, indicated by the intensity ratio (IR). The surveying were performed during a field campaign of several days of mobile optical remote sensing measurements in Tianjing city, China. The spectroscopic data were recorded by different spectrometers from which the most two mature techniques are the Differential Optical Absorption Spectroscopy (DOAS) and the Solar Occultation Flux (SOF). Besides, a third measuring approach of using a ‘Flame’ spectrometer was explored to discover the sulphur dioxide (SO2) traces. Except for the different spectrometers, other auxiliary data were taken from the wind meter and the GPS tracker. To construct an integral geographic information, data inspecting, cleaning, merging were heavily applied based on physical modeling. / 本文旨在利用时间-空间域数据分析来探索所测量的大气污染物浓度以及它们与其诱发的气溶胶之间的关联情况。气溶胶痕迹以特定波长的光强度之比（IR）来表征。本文所用到的数据采自于针对天津市工业园区及天津港进行的车载移动光学遥感测量。所关注的大气污染物浓度通过国际上最成熟的差分吸收光谱（DOAS）技术和掩光通量（SOF）测量法计算得出，而光谱数据则通过第三种技术手段，即利用迷你型‘火焰’光谱仪，记录测量。研究表明该小型光谱仪可以发现并记录二氧化硫气体的踪迹。本文在物理建模的基础上大量应用到信号检测、滤波，数据清洗、合并。综合浓度数据，光谱数据以及辅助数据诸如取自测风仪的风速风向信息和取自GPS跟踪器的位置信息，成功构建出完整的区域地理信息。