<p>The communication systems are changing. Cognitive Radio is an automatic adaptative system to improve the spectrum efficiency. It has intelligence to adapt itself to the environment to improve the transmission performancies. For this system, spectrum sensing function is very important so a signal detector is necessary. In this work a signal detector has been implemented in GNU Radio environment. GNU Radio is a platform that respects the Cognitive Radio aproach. It is flexible, software defined and cheap.</p>

Improvements have been made to the spatial coherence method for automatically determining cloud-free ocean radiances in satellite imagery by incorporating the spectral signatures of reflecting surfaces. The spatial coherence method relies on the fact that small-scale cloud-free regions typically exhibit uniform emission and uniform reflection. While small-scale overcast regions typically exhibit uniform emission, they often exhibit considerable variability in reflectance. On rare occasions the requirements of spatial uniformity are not met and errors are produced in estimated cloud-free radiances. The frequency of errors in identification of cloud-free and overcast pixels was assessed using two years of Advanced Very-High Resolution Radiometer (AVHRR) data from six regions of the globe. Significant improvement in the identification of cloud-free radiances is obtained by including a test of Q, the ratio of the AVHRR channel 2 (0.83-μm) reflectance to channel 1 (0.63-μm) reflectance. Q varies depending on whether the reflecting surface is cloud-free ocean, cloud-free land, or overcast by clouds. A study was conducted to determine the dependence of Q for overcast pixels on changes in season and geography. While some variation is evident due to satellite viewing angle and differences in atmospheric water vapor content, these effects are sufficiently small that constant thresholds may be used to help separate cloud-free and overcast pixels. The modified spatial coherence method uses the threshold for Q and radiance uniformity thresholds at 0.63-μm and 11-μm to identify cloud-free and overcast pixels. A sensitivity study was performed to determine the dependence of cloud-free ocean radiance estimates on the values of the uniformity thresholds. The results of the study indicate that using thresholds of 0.5% for the 0.63-μm reflectivity and 0.5 mWm⁻²sr⁻¹cm for the 11-μm radiance, produces cloud-free radiances that are rarely biased by more than 0.4% for reflectances at 0.63 μm and 0.4 K for the 11-μm brightness temperature. The uniformity and Q thresholds may be used for a large variety of scenes from different seasons and geographic areas. / Graduation date: 2000

Graduation date: 1998

In remotely located forest watersheds, monitoring nitrogen (N) in streams often is not feasible because of the high costs and site inaccessibility. Therefore, modelling tools that can predict N in unmonitored watersheds are urgently needed to support management decisions for these watersheds. Recently, remote sensing (RS) has become a cost-efficient way to evaluate watershed characteristics and obtain model input variables. This study was to develop an artificial neural network (ANN) modelling tool relying solely on public domain climate data and satellite data without ground-based measurements. ANN was successfully applied to simulate N compositions in streams at studied watersheds by using easily accessible input variables, relevant time-lagged inputs and inputs reflecting seasonal cycles. This study was the first effort to take the consideration of vegetation dynamics into N modelling by using RS-derived enhanced vegetation index (EVI) that was capable of describing the differences of vegetation canopy and vegetation dynamics among watersheds. As a further study to demonstrate the applicability of the ANN models to unmonitored watersheds, the calibrated ANN models were used to predict N in other different watersheds (unmonitored watersheds in this perspective) without further calibration. A watershed similarity index was found to show high correlation with the transferability of the models and can potentially guide transferring the trained models into similar unmonitored watersheds. Finally, a framework to incorporate water quantity/quality modelling into forestry management was proposed to demonstrate the application of the developed models to support decision making. The major components of the framework include watershed delineation and classification, database and model development, and scenario-based analysis. The results of scenario analysis can be used to translate vegetation cut into values of EVI that can be fed to the models to predict changes in water quality (e.g. N) in response to harvesting scenarios. The results from this research demonstrated the applicability of ANNs for stream N modelling using easily accessible data, the effectiveness of RS-derived EVI in N model construction, and the transferability of the ANN models. The presented models have high potential to be used to predict N in streams in the real-world and serve forestry management. / Environmental Engineering

This study investigates geographic patterns of genetic variation in aspen spring phenology to understanding how tree population adapts to climatically risk environments. These finding suggest rules to guide seed transfer between regions. I use a classical common garden experiment to reveal genetic differences among populations from western Canada and Minnesota, and present a novel method to seamlessly map the heatsum required for remotely sensed green-up. Both approaches reveal two major geographic patterns: northern and high elevation aspen populations break bud earlier than sources from the boreal plains, and late budbreak is strongly associated with the driest winter and spring environments. This suggests selection pressures for late budbreak due to both frost and drought risks in early spring, and we therefore caution against transfer of seed to drought regions of the boreal plains. Although such transfers have been shown to increase plantation productivity in short-term tests, non-local planting material may be susceptible to exceptional spring droughts. / Forest Biology and Management

Thesis (M.S.)--Oregon State University, 2007. / Printout. Includes bibliographical references (leaves 102-105). Also available on the World Wide Web.

Thesis (Ph. D.)--Florida State University, 2005. / Includes vita. Includes bibliographical references (p. 191-202) Also available online via the Florida State University electronic theses website (http://etd.lib.fsu.edu/).

Thesis (Ph.D.)--University of Nebraska-Lincoln, 2006. / Title from title screen (site viewed on Feb. 6, 2007). PDF text: 163 p. : ill. (some col.). UMI publication number: AAT 3221295. Includes bibliographical references. Also available in microfilm and microfiche format.

Thesis (M.S.)--Rochester Institute of Technology, 2007. / Typescript. Includes bibliographical references (leaves 63-64).

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