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This thesis analyses several contracts which regulate the relationship between organizations which own or operate remote-sensing satellites and the organizations which receive satellite transmitted data. / The first part is a descriptive part which stresses the importance of the national environment. / The second part deals with the study of the contracts. Those which are commercially oriented are very elaborated in order to create a team spirit with the local organization. It starts with a study of the evolution of the Landsat contracts when this satellite was alone of its kind in the Western world. Then it studies the impact on the contracts of the early commercialization process and compares the new contracts with those established by newly arrived and competing organizations in the market. Finally, it studies similar provisions set by the European system and by the Canadian system. / The third part focuses on the impact of the copyright conventions on remote-sensing data protection. It shows that even though this protection is expressed by means of various warnings and "ad-hoc" clauses, this protection is still mostly formal.

In the present study, the microwave interferogram is digitized and analyzed using computer software developed to facilitate the extraction of velocity information from the microwave Doppler interference signals by applying digital signal processing techniques. / The waveguide or detonation tube of the present microwave interferometer consisted of a copper tube 38.4 mm in diameter, 3.5 m long, with a thin wire stretched along the center axis acting as a center conductor for the coaxial configuration. The system was tested at microwave frequencies of 6.70GHz and 9.21GHz by performing a number of detonation experiments in explosive gaseous mixtures of C$ sb2$H$ sb2$ + 2.5O$ sb2$ and C$ sb3$H$ sb8$ + 5O$ sb2$, at low initial pressures (6torr to 80torr). Average velocity measurements obtained by the microwave method generally agreed with independent photodetector measurements to within 2%. / In this study, the present technique has been used to explore unstable detonations near the limit. This demonstrates that the improved microwave Doppler interferometer is particularly well suited for unstable detonations where the large scale velocity fluctuations must be monitored continuously. It may be concluded that the present coaxial configuration microwave Doppler interferometry technique shows promise as a useful diagnostic tool for studying unstable detonations. (Abstract shortened by UMI.)

<p> Semi-arid forests are in a period of rapid transition as a result of unprecedented landscape scale fires, insect outbreaks, drought, and anthropogenic land use practices. Understanding how historically episodic disturbances led to coherent forest structural and spatial patterns that promoted resilience and resistance is a critical part of addressing change. Here my coauthors and I apply metabolic scaling theory (MST) to examine scaling behavior and structural patterns of semi-arid conifer forests in Arizona and New Mexico. We conceptualize a linkage to mechanistic drivers of forest assembly that incorporates the effects of low-intensity disturbance, and physiologic and resource limitations as an extension of MST. We use both aerial LiDAR data and field observations to quantify changes in forest structure from the sub-meter to landscape scales. We found: (1) semi-arid forest structure exhibits MST-predicted behaviors regardless of disturbance and that MST can help to quantitatively measure the level of disturbance intensity in a forest, (2) the application of a power law to a forest overstory frequency distribution can help predict understory presence/absence, (3) local indicators of spatial association can help to define first order effects (e.g. topographic changes) and map where recent disturbances (e.g. logging and fire) have altered forest structure. Lastly, we produced a comprehensive set of above-ground biomass and carbon models for five distinct forest types and ten common species of the southwestern US that are meant for use in aerial LiDAR forest inventory projects. This dissertation presents both a conceptual framework and applications for investigating local scales (stands of trees) up to entire ecosystems for diagnosis of current carbon balances, levels of departure from historical norms, and ecological stability. These tools and models will become more important as we prepare our ecosystems for a future characterized by increased climatic variability with an associated increase in frequency and severity of ecological disturbances. </p>

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<p> A better understanding of the environmental controls on current plant species distribution is essential if the impacts of such diverse challenges as invasive species, changing fire regimes, and global climate change are to be predicted and important diversity conserved. Climate, soil, hydrology, various biotic factors fire, history, and chance can all play a role, but disentangling these factors is a daunting task. Increasingly sophisticated statistical models relying on existing distributions and mapped climatic variables, among others, have been developed to try to answer these questions. Any failure to explain pattern with existing mapped climatic variables is often taken as a referendum on climate as a whole, rather than on the limitations of the particular maps or models. <i>Every</i> location has a unique and constantly changing climate so that <i>any</i> distribution <i> could</i> be explained by some aspect of climate. </p><p> Chapter 1 of this dissertation reviews some of the major flaws in species distribution modeling and addresses concerns that climate may therefore not be predictive of, or even relevant to, species distributions. Despite problems with climate-based models, climate and climate-derived variables still have substantial merit for explaining species distribution patterns. Additional generation of relevant climate variables and improvements in other climate and climate-derived variables are still needed to demonstrate this more effectively. Satellite data have a long history of being used for vegetation mapping and even species distribution mapping. They have great potential for being used for additional climatic information, and for improved mapping of other climate and climate-derived variables. </p><p> Improving the characterization of cloud cover frequency with satellite data is one way in which the mapping of important climate and climate-derived variables can be improved. An important input to water balance models, solar radiation maps could be vastly improved with a better mapping of spatial and temporal patterns in cloud cover. Chapter 2 of this dissertation describes the generation of custom daily cloud cover maps from Advanced Very High Resolution Radiometer (AVHRR) satellite data from 1981-1999 at ~5 km resolution and Moderate Resolution Imagine Spectroradiomter (MODIS) satellite reflectance data at ~500 meter resolution for much of the western U.S., from 2000 to 2012. Intensive comparisons of reflectance spectra from a variety of cloud and snow-covered scenes from the southwestern United States allowed the generation of new rules for the classification of clouds and snow in both the AVHRR and MODIS data. The resulting products avoid many of the problems that plague other cloud mapping efforts, such as the tendency for snow cover and bright desert soils to be mapped as cloud. This consistency in classification across cover types is critically important for any distribution modeling of a plant species that might be dependent on cloud cover. </p><p> In Chapter 3, monthly cloud frequencies derived from the daily classifications were used directly in species distribution models for giant sequoia and were found to be the strongest predictors of giant sequoia distribution. A high frequency of cloud cover, especially in the spring, differentiated the climate of the west slope of the southern Sierra Nevada, where giant sequoia are prolific, from central and northern parts of the range, where the tree is rare and generally absent. Other mapped cloud products, contaminated by confusion with high elevation snow, would likely not have found this important result. The result illustrates the importance of accuracy in mapping as well as the importance of previously overlooked aspects of climate for species distribution modeling. But it also raises new questions about why the clouds form where they do and whether they might be associated with other aspects of climate important to giant sequoia distribution. What are the exact climatic mechanisms governing the distribution? Detailed aspects of the local climate warranted more investigation. </p><p> Chapter 4 investigates the climate associated with the frequent cloud formation over the western slopes of the southern Sierra Nevada: the "sequoia belt". This region is climatically distinct in a number of ways, all of which could be factors in influencing the distribution of giant sequoia and other species. Satellite and micrometeorological flux tower data reveal characteristics of the sequoia belt that were not evident with surface climate measurements and maps derived from them. Results have implications for species distributions everywhere, but especially in rugged mountains, where climates are complex and poorly mapped. </p><p> Chapter 5 summarizes some of the main conclusions from the work and suggests directions for related future research. (Abstract shortened by UMI.) </p>

<p> The Radar-based Quantitative Precipitation Estimates (QPE) is one of the NEXRAD products that are available in a high temporal and spatial resolution compared with gauges. Radar-based QPEs have been widely used in many hydrological and meteorological applications; however, a few studies have focused on using radar QPE products in deriving of Precipitation Frequency Estimates (PFE). Accurate and regionally specific information on PFE is critically needed for various water resources engineering planning and design purposes. This study focused first on examining the data quality of two main radar products, the near real-time Stage IV QPE product, and the post real-time RFC/MPE product. Assessment of the Stage IV product showed some alarming data artifacts that contaminate the identification of rainfall maxima. Based on the inter-comparison analysis of the two products, Stage IV and RFC/MPE, the latter was selected for the frequency analysis carried out throughout the study. The precipitation frequency analysis approach used in this study is based on fitting Generalized Extreme Value (GEV) distribution as a statistical model for the hydrologic extreme rainfall data that based on Annual Maximum Series (AMS) extracted from 11 years (2002-2012) over a domain covering Louisiana. The parameters of the GEV model are estimated using method of linear moments (L-moments). Two different approaches are suggested for estimating the precipitation frequencies; Pixel-Based approach, in which PFEs are estimated at each individual pixel and Region-Based approach in which a synthetic sample is generated at each pixel by using observations from surrounding pixels. The region-based technique outperforms the pixel based estimation when compared with results obtained by NOAA Atlas 14; however, the availability of only short record of observations and the underestimation of radar QPE for some extremes causes considerable reduction in precipitation frequencies in pixel-based and region-based approaches. </p>