As well as the many benefits associated with the evolution of multispectral sensors into hyperspectral sensors there is also a considerable increase in storage space and the computational load to process the data. Consequently the remote sensing ommunity is investigating and developing statistical methods to alleviate these problems. / The research presented here investigates several approaches to reducing the dimensionality of hyperspectral remotely sensed data while maintaining the levels of accuracy achieved using the full dimensionality of the data. It was conducted with an emphasis on applications in maximum likelihood classification (MLC) of hyperspectral image data. An inherent characteristic of hyperspectral data is that adjacent bands are typically highly correlated and this results in a high level of redundancy in the data. The high correlations between adjacent bands can be exploited to realise significant reductions in the dimensionality of the data, for a negligible reduction in classification accuracy. / The high correlations between neighbouring bands is related to their response functions overlapping with each other by a large amount. The spectral band filter functions were modelled for the HyMap instrument that acquires hyperspectral data used in this study. The results were compared with measured filter function data from a similar, more recent HyMap instrument. The results indicated that on average HyMap spectral band filter functions exhibit overlaps with their neighbouring bands of approximately 60%. This is considerable and partly accounts for the high correlation between neighbouring spectral bands on hyperspectral instruments. / A hyperspectral HyMap image acquired over an agricultural region in the south west of Western Australia has been used for this research. The image is composed of 512 × 512 pixels, with each pixel having a spatial resolution of 3.5 m. The data was initially reduced from 128 spectral bands to 82 spectral bands by removing the highly overlapping spectral bands, those which exhibit high levels of noise and those bands located at strong atmospheric absorption wavelengths. The image was examined and found to contain 15 distinct spectral classes. Training data was selected for each of these classes and class spectral mean and covariance matrices were generated. / The discriminant function for MLC makes use of not only the measured pixel spectra but also the sample class covariance matrices. This thesis first examines reducing the parameterization of these covariance matrices for use by the MLC algorithm. The full dimensional spectra are still used for the classification but the number of parameters needed to describe the covariance information is significantly reduced. When a threshold of 0.04 was used in conjunction with the partial correlation matrices to identify low values in the inverse covariance matrices, the resulting classification accuracy was 96.42%. This was achieved using only 68% of the elements in the original covariance matrices. / Both wavelet techniques and cubic splines were investigated as a means of representing the measured pixel spectra with considerably fewer bands. Of the different mother wavelets used, it was found that the Daubechies-4 wavelet performed slightly better than the Haar and Daubechies-6 wavelets at generating accurate spectra with the least number of parameters. The wavelet techniques investigated produced more accurately modelled spectra compared with cubic splines with various knot selection approaches. A backward stepwise knot selection technique was identified to be more effective at approximating the spectra than using regularly spaced knots. A forward stepwise selection technique was investigated but was determined to be unsuited to this process. / All approaches were adapted to process an entire hyperspectral image and the subsequent images were classified using MLC. Wavelet approximation coefficients gave slightly better classification results than wavelet detail coefficients and the Haar wavelet proved to be a more superior wavelet for classification purposes. With 6 approximation coefficients, the Haar wavelet could be used to classify the data with an accuracy of 95.6%. For 11 approximation coefficients this figure increased to 96.1%. / First and second derivative spectra were also used in the classification of the image. The first and second derivatives were determined for each of the class spectral means and for each band the standard deviations were calculated of both the first and second derivatives. Bands were then ranked in order of decreasing standard deviation. Bands showing the highest standard deviations were identified and the derivatives were generated for the entire image at these wavelengths. The resulting first and second derivative images were then classified using MLC. Using 25 spectral bands classification accuracies of approximately 96% and 95% were achieved using the first and second derivative images respectively. These results are comparable with those from using wavelets although wavelets produced higher classification accuracies when fewer coefficients were used.

Thesis--Auburn University, 2007. / Abstract. Vita. Includes bibliographic references (p.148-150).

Thesis (M.A. in Security Studies (Homeland Security and Defense))--Naval Postgraduate School, December 2008. / Thesis Advisor(s): Wirtz, James J. "December 2008." Description based on title screen as viewed on January 30, 2009. Includes bibliographical references (p. 99-108). Also available in print.

Thesis(M.S.)--Auburn University, 2007. / Abstract. Vita. Includes bibliographic references (p.72-74).

Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008. / Committee Chair: Vela, Patricio; Committee Member: Collins, Thomas; Committee Member: Howard, Ayanna

Thesis (M.M.A.S.)--School of Advanced Airpower Studies, 1995. / Subject: An analysis of whether Special Operations Forces should use Unmanned Aerial Vehicles to support intelligence, surveillance, reconnaissance, communications and re-supply capability deficiencies. Cover page date: June 1995. Vita. Includes bibliographical references.

Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2007. / Includes bibliographical references (p. 81-84).

Το μεγαλύτερο μέρος της επιφάνεια του πλανήτη καλύπτεται από τους ωκεανούς. Η περιέργεια του ανθρώπου να εξερευνήσει και να καταλάβει το πώς λειτουργεί το περιβάλλον του, σε συνδυασμό με την αναζήτηση νέων πόρων, ώθησε τον άνθρωπο στον υδάτινο κόσμο. Δεδομένου του βάθους της θάλασσας, οι αρχικές αυτόνομες καταδύσεις, αλλά και οι καταδύσεις με την βοήθεια αναπνευστικών συσκευών δεν κάλυψαν παρά στο ελάχιστο την πρόσβαση στον κόσμο αυτό. Η ανάπτυξη κάποιου διαμεσολαβητή ήταν όχι μόνο χρήσιμη αλλά και απαραίτητη για να προσεγγίσουμε μεγάλα βάθη αλλά και επικίνδυνα, για τους δύτες, μέρη. Στην παρούσα εργασία παρουσιάζεται η χρησιμότητα των υποβρύχιων οχημάτων, σε διάφορους τομείς των ανθρώπινων δραστηριοτήτων. Αναπτύσσονται φυσικές έννοιες και βασικοί ορισμοί για την περιγραφή του περιβάλλοντος στο οποίο λειτουργούν τα υποβρύχια οχήματα. Στη συνέχεια γίνεται αναφορά των διαφόρων κατηγοριών των υποβρύχιων οχημάτων που έχουν αναπτυχθεί μέχρι σήμερα. Αναλύονται λεπτομερώς οι τεχνολογικές τους δυσκολίες, τα πλεονεκτήματα και τα μειονεκτήματα του κάθε είδους υποβρύχιου οχήματος, καθώς επίσης και οι τεχνολογικές εξελίξεις στον τομέα αυτό. Για παράδειγμα, οι ακουστικές επικοινωνίες, η υποβρύχια πλοήγηση και η αποφυγή εμποδίων, ώστε να καταστεί εφικτή η υποβρύχια εξερεύνηση. Τέλος, παρουσιάζονται τα σπουδαιότερα υποβρύχια οχήματα που έχουν κατασκευαστεί μέχρι σήμερα και έχουν οδηγήσει σε σημαντικές ανακαλύψεις στον υδάτινο κόσμο. / -

The European project BACCHUS (impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) focuses on aerosol-cloud interactions. Vertical wind velocities near cloud base, and cloud condensation nuclei (CCN) spectra, are the two most important input parameters for aerosol-cloud parcel models in determining cloud microphysical and optical properties. Therefore, the present study focuses on the instrumental development for vertical wind measurements to improve aerosol-cloud closure studies. Enhancements in Remotely Piloted Aircraft Systems (RPAS) have demonstrated their potential as tools in atmospheric research to study the boundary layer dynamics, aerosols and clouds. However, as a relatively new tool for atmospheric research, RPA require instrumental development and validation to address current observational needs. A 5-hole probe is implemented on a remotely piloted aircraft (RPA) platform, with an inertial navigation system (INS) to obtain atmospheric wind vectors. The 5- hole probe is first calibrated in a wind tunnel (at Météo-France, Toulouse, France), and an error analysis is conducted on the vertical wind measurement. Atmospheric wind vectors obtained from RPA flights are compared with wind vectors determined from sonic anemometers located at different levels on a 60 m meteorological mast (Centre de Recherches Atmosphériques, Lannemezan, France). Good agreements between vertical wind velocity probability density functions are obtained. The power spectral density of the three wind components follow the -5/3 line for the established regime of turbulence (Kolmogorov law). Turbulent kinetic energy (TKE) values calculated from the RPA are somewhat higher than TKE compared to the sonic anemometer; however, the results agree with those reported in other experiments that compare RPA platforms and sonic anemometers (Lampert et al. (2016), Båserud et al. (2016)). As the RPA equipped with a 5-hole probe (defined as the ``wind-RPA'') is developed for aerosol-cloud observations, updraft velocities near cloud base are compared with cloud radar data during a BACCHUS field campaign (Mace Head Research Station, Ireland). Three case studies illustrate the similarity of in-cloud updrafts measured between the wind-RPA and the cloud radar. A good agreement between vertical velocities of both instruments over a range of different meteorological conditions is found. Updraft velocity measurements from the wind-RPA are implemented in the aerosol-cloud parcel model to conduct a closure study for stratocumulus case with convection sampled during a BACCHUS field campaign in Cyprus. Aerosol size distributions and CCN were measured at a ground-site, which served as input to the aerosol-cloud parcel model along with the updraft velocities at cloud base measured by the RPA. In addition, the RPA conducted a vertical profile through the cloud layer and measured the shortwave transmission of solar irradiance during the ascent. The aerosol-cloud parcel model also shows that entrainment has a greater impact on cloud optical properties than variability in updraft velocity and aerosol particle concentration. Results of the case study for the Cyprus field experiment are consistent with results for similar closure studies conducted during the Mace Head field campaign (Sanchez et al., 2017), and reinforce the significance of including entrainment processes in cloud models to reduce uncertainties in aerosol-cloud interactions.

Unmanned aircrafts represent one of the fastest growing technologies of the last years. Although historically not completely unknown, only recently have they acquired the long-deserved attention. However, it focuses almost exclusively on their use in combat operations, whereas their capabilities in civilian sphere remain relatively unexplored. Analysis of these abilities is the main focus of this thesis, which describes and analyses current applicable legislation, points out different issues of both its interpretation and application and tries to offer solutions. This thesis is divided into 4 chapters and a conclusion. The first chapter deals with the introduction to this topic, including history of unmanned aircrafts and clarification of the term unmanned aircraft itself. Then it moves on to describe the possible classification of unmanned aircrafts and the terminology used, which remains unsettled even to this day. The main aim of this is to try to help the reader to find his way in this complicated area. The second chapter includes the analysis of the applicable legislation in the Czech republic, starting with the general approach and then continuing with special emphasis on particular issues, such as operating limitations of unmanned aircrafts in certain areas or liability of aircraft operators...