Thematische Bibliographien / Laboratory for Applications of Remote Sensing / Dissertationen

Dissertationen zum Thema „Laboratory for Applications of Remote Sensing“

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1

Philipson, née Ammenberg Petra. „Environmental Applications of Aquatic Remote Sensing“. Doctoral thesis, Uppsala University, Centre for Image Analysis, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3328.

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Many lakes, coastal zones and oceans are directly or indirectly influenced by human activities. Through the outlet of a vast amount of substances in the air and water, we are changing the natural conditions on local and global levels.

Remote sensing sensors, on satellites or airplanes, can collect image data, providing the user with information about the depicted area, object or phenomenon. Three different applications are discussed in this thesis. In the first part, we have used a bio-optical model to derive information about water quality parameters from remote sensing data collected over Swedish lakes. In the second part, remote sensing data have been used to locate and map wastewater plumes from pulp and paper industries along the east coast of Sweden. Finally, in the third part, we have investigated to what extent satellite data can be used to monitor coral reefs and detect coral bleaching.

Regardless of application, it is important to understand the limitations of this technique. The available sensors are different and limited in terms of their spatial, spectral, radiometric and temporal resolution. We are also limited with respect to the objects we are monitoring, as the concentration of some substances is too low or the objects are too small, to be identified from space. However, this technique gives us a possibility to monitor our environment, in this case the aquatic environment, with a superior spatial coverage. Other advantages with remote sensing are the possibility of getting updated information and that the data is collected and distributed in digital form and therefore can be processed using computers.

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Philipson, Petra. „Environmental applications of aquatic remote sensing /“. Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2003. http://publications.uu.se/theses/91-554-5542-5/.

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3

Saraf, Arun Kumar. „Remote sensing applications in geobotanical exploration : some applications of remote sensing to geological surveying in vegetated areas“. Thesis, University of Dundee, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.276975.

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4

Egido, Egido Alejandro. „GNSS reflectometry for land remote sensing applications“. Doctoral thesis, Universitat Politècnica de Catalunya, 2013. http://hdl.handle.net/10803/129090.

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Soil moisture and vegetation biomass are two essential parameters from a scienti c and economical point of view. On one hand, they are key for the understanding of the hydrological and carbon cycle. On the other hand, soil moisture is essential for agricultural applications and water management, and vegetation biomass is crucial for regional development programs. Several remote sensing techniques have been used to measure these two parameters. However, retrieving soil moisture and vegetation biomass with the required accuracy, and the appropriate spatial and temporal resolutions still remains a major challenge. The use of Global Navigation Satellite Systems (GNSS) reflected signals as sources of opportunity for measuring soil moisture and vegetation biomass is assessed in this PhD Thesis. This technique, commonly known as GNSS-Reflectometry (GNSS-R), has gained increasing interest among the scienti c community during the last two decades due to its unique characteristics. Previous experimental works have already shown the capabilities of GNSS-R to sense small reflectivity changes on the surface. The use of the co- and cross-polarized reflected signals was also proposed to mitigate nuisance parameters, such as soil surface roughness, in the determination of soil moisture. However, experimental evidence of the suitability of that technique could not be demonstrated. This work analyses from a theoretical and an experimental point of view the capabilities of polarimetric observations of GNSS reflected signals for monitoring soil moisture and vegetation biomass. The Thesis is structured in four main parts. The fi rst part examines the fundamental aspects of the technique and provides a detailed review of the GNSS-R state of the art for soil moisture and vegetation monitoring. The second part deals with the scattering models from land surfaces. A comprehensive description of the formation of scattered signals from rough surfaces is provided. Simulations with current state of the art models for bare and vegetated soils were performed in order to analyze the scattering components of GNSS reflected signals. A simpli ed scattering model was also developed in order to relate in a straightforward way experimental measurements to soil bio-geophysical parameters. The third part reviews the experimental work performed within this research. The development of a GNSS-R instrument for land applications is described, together with the three experimental campaigns carried out in the frame of this PhD Thesis. The analysis of the GNSS-R and ground truth data is also discussed within this part. As predicted by models, it was observed that GNSS scattered signals from natural surfaces are a combination of a coherent and an incoherent scattering components. A data analysis technique was proposed to separate both scattering contributions. The use of polarimetric observations for the determination of soil moisture was demonstrated to be useful under most soil conditions. It was also observed that forests with high levels of biomass could be observed with GNSS reflected signals. The fourth and last part of the Thesis provides an analysis of the technology perspectives. A GNSS-R End-to-End simulator was used to determine the capabilities of the technique to observe di erent soil reflectivity conditions from a low Earth orbiting satellite. It was determined that high accuracy in the estimation of reflectivity could be achieved within reasonable on-ground resolution, as the coherent scattering component is expected to be the predominant one in a spaceborne scenario. The results obtained in this PhD Thesis show the promising potential of GNSS-R measurements for land remote sensing applications, which could represent an excellent complementary observation for a wide range of Earth Observation missions such as SMOS, SMAP, and the recently approved ESA Earth Explorer Mission Biomass.
La humedad del suelo y la biomasa de la vegetaci on son dos parametros clave desde un punto de vista tanto cient co como econ omico. Por una parte son esenciales para el estudio del ciclo del agua y del carbono. Por otra parte, la humedad del suelo es esencial para la gesti on de las cosechas y los recursos h dricos, mientras que la biomasa es un par ametro fundamental para ciertos programas de desarrollo. Varias formas de teledetección se han utilizado para la observaci on remota de estos par ametros, sin embargo, su monitorizaci on con la precisi on y resoluci on necesarias es todav a un importante reto tecnol ogico. Esta Tesis evalua la capacidad de medir humedad del suelo y biomasa de la vegetaci on con señales de Sistemas Satelitales de Posicionamiento Global (GNSS, en sus siglas en ingl es) reflejadas sobre la Tierra. La t ecnica se conoce como Reflectometr í a GNSS (GNSS-R), la cual ha ganado un creciente inter es dentro de la comunidad científ ca durante las dos ultimas d ecadas. Experimentos previos a este trabajo ya demostraron la capacidad de observar cambios en la reflectividad del terreno con GNSS-R. El uso de la componente copolar y contrapolar de la señal reflejada fue propuesto para independizar la medida de humedad del suelo de otros par ametros como la rugosidad del terreno. Sin embargo, no se pudo demostrar una evidencia experimental de la viabilidad de la t ecnica. En este trabajo se analiza desde un punto de vista te orico y experimental el uso de la informaci on polarim etrica de la señales GNSS reflejadas sobre el suelo para la determinaci on de humedad y biomasa de la vegetaci on. La Tesis se estructura en cuatro partes principales. En la primera parte se eval uan los aspectos fundamentales de la t ecnica y se da una revisi on detallada del estado del arte para la observaci on de humedad y vegetaci on. En la segunda parte se discuten los modelos de dispersi on electromagn etica sobre el suelo. Simulaciones con estos modelos fueron realizadas para analizar las componentes coherente e incoherente de la dispersi on de la señal reflejada sobre distintos tipos de terreno. Durante este trabajo se desarroll o un modelo de reflexi on simpli cado para poder relacionar de forma directa las observaciones con los par ametros geof sicos del suelo. La tercera parte describe las campañas experimentales realizadas durante este trabajo y discute el an alisis y la comparaci on de los datos GNSS-R con las mediciones in-situ. Como se predice por los modelos, se comprob o experimentalmente que la señal reflejada est a formada por una componente coherente y otra incoherente. Una t ecnica de an alisis de datos se propuso para la separacióon de estas dos contribuciones. Con los datos de las campañas experimentales se demonstr o el bene cio del uso de la informaci on polarim etrica en las señales GNSS reflejadas para la medici on de humedad del suelo, para la mayor a de las condiciones de rugosidad observadas. Tambi en se demostr o la capacidad de este tipo de observaciones para medir zonas boscosas densamente pobladas. La cuarta parte de la tesis analiza la capacidad de la t ecnica para observar cambios en la reflectividad del suelo desde un sat elite en orbita baja. Los resultados obtenidos muestran que la reflectividad del terreno podr a medirse con gran precisi on ya que la componente coherente del scattering ser a la predominante en ese tipo de escenarios. En este trabajo de doctorado se muestran la potencialidades de la t ecnica GNSS-R para observar remotamente par ametros del suelo tan importantes como la humedad del suelo y la biomasa de la vegetaci on. Este tipo de medidas pueden complementar un amplio rango de misiones de observaci on de la Tierra como SMOS, SMAP, y Biomass, esta ultima recientemente aprobada para la siguiente misi on Earth Explorer de la ESA.
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5

Hong, Guowei. „Satellite image processing for remote sensing applications“. Thesis, University of Central Lancashire, 1995. http://clok.uclan.ac.uk/1878/.

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This thesis investigates areas of image compression with particular reference to remote sensing imagery. The research described was carried out in four specific areas, namely, discrete cosine transform (DCT) for remote sensing imagery, lossless image compression based on conditional statistics, exploiting interband redundancy for remote sensing imagery, neural networks for lossless image compression. The effect of using standard compression algorithm (JPEG's DCT) on the remote sensing image data is investigated. This involves visual and statistical assessment of the errors produced, both in the data itself, and with reference to the results of the processing (i. e., classification) normally performed using such data. It has been reported that the DCT characteristics can be modified to achieve a trade-off between compression ratio and pixel value error. It is feasible therefore that the user of remote sensing data could find a suitable compromise that could offer some of the compression benefits offered by the DCT, while. retaining sufficient accuracy of image data for the required applications. An approach for lossless image compression using conditional statistics is investigated. That is encoding each pixel value with one of several variable-length codes depending on previous pixel values (context). The author's method achieved its aim by approximating the probability distribution function (PDF) for each context and coding the image data using arithmetic coding. Experimental results are included to show that this method has achieved some improvement in lossless image compression and can achieve an average bits per pixel lower than the zero-order entropy of the prediction-error image. In the area of exploiting interband correlation for remote sensing imagery, two new techniques, namely joint entropy coding and interband prediction, are described. Joint entropy coding is based on the idea that to code a pair of pixel values from two different bands is more effective than to code them individually if there is interband correlation among them. Interband prediction is based on the fact that the structure of one band data can generally give some information about the structure of other bands. The results demonstrate and compare the usefulness of both techniques in improving the overall lossless compression ratio for remote sensing imagery. The idea of using neural networks for lossless image coding is introduced. A novel approach to pixel prediction based on a three-layer perceptron neural network using a backpropagation learning algorithm is described, which is aimed at improving the pixel prediction accuracy, thus improving the lossless compression ratio. Experimental results show this neural network approach consistently achieves better prediction than conventional linear prediction techniques in terms of minimizing the mean square error, although the results for the overall compression ratio are not significantly improved.
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Boudreau, Sylvain. „Applications of frequency combs in remote sensing“. Doctoral thesis, Université Laval, 2014. http://hdl.handle.net/20.500.11794/25325.

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Cette thèse a pour objectif l’exploration des applications potentielles des peignes de fréquences en télédétection. Pour ce faire, trois configurations expérimentales sont étudiées. Pour chacune des configurations, une analyse de divers aspects de leur fonctionnement est faite et les avantages et les inconvénients qui y sont propres sont discutés. Des montages expérimentaux basés sur ces configurations ont été fabriqués en laboratoire. Des mesures expérimentales viennent démontrer les capacités de détection des différentes techniques. La première configuration étudiée concerne l’échantillonnage passif d’une source optique externe. Cette technique permet d’évaluer le spectre de la source d’intérêt en la combinant interférométriquement avec les impulsions d’une paire de peignes de fréquences. Une étude probabiliste de la technique est effectuée afin d’en évaluer les limites de performance. Des mesures de sources cohérentes et incohérentes à haute résolution spectrale sont présentées. La deuxième technique étudiée exploite la configuration dite incohérente permettant de faire la caractérisation active d’une cible. Cette technique rend possible la mesure hyperspectrale résolue en distance d’une scène observée. Un montage expérimental de lidar hyperspectral a été conçu et fabriqué en laboratoire dans le but de faire des mesures extérieures de cibles à une distance allant jusqu’à 175 m. Les capacités de détection de plusieurs caractéristiques de cibles sont démontrées pour des cibles dures et distribuées, sous forme de nuages d’aérosols. Des mesures de raies d’absorption moléculaire, ainsi que d’épaisseur d’échantillons transparents et translucides, sont présentées. La troisième configuration étudiée, dite cohérente, permet de faire de la mesure active d’une cible en utilisant un des trains d’impulsions comme oscillateur local. L’utilisation d’un oscillateur local ouvre la porte à des mesures de vibrométrie à haute sensibilité, ce qui est impossible en configuration incohérente. Un modèle analytique de collecte de puissance pour les systèmes à un seul mode transversal, permettant de prédire les puissances en jeu en configuration cohérente, est développé et validé expérimentalement. La technique de référencement habituelle, permettant de corriger les erreurs causées par les fluctuations des paramètres des peignes, est modifiée et adaptée aux mesures de vibrométrie cohérente. Des mesures de vibrométrie résolue en distance sont présentées, où la capacité du système à démoduler une voix humaine à partir des vibrations d’un mur est démontrée.
The goal of this thesis is to explore the potential applications of frequency combs for remote sensing. For this purpose, three comb-based configurations are studied. For each of these configurations, an analysis of their workings is performed and their advantages and disadvantages are discussed. Experimental setups based on those configurations were built in laboratory. The detection capabilities of the techniques are demonstrated through experimental measurements. The first configuration that is studied enables passive sampling of an external optical source. Using this technique, it is possible to compute the spectrum of the considered source by interferometrically combining it with the pulses from a pair of frequency combs. A stochastic study of the technique is performed to assess its performance limits. Coherent and incoherent sources with high-resolution spectral content are measured. The second technique uses a configuration called incoherent that enables active characterization of a target. Using this technique, it is possible to perform range-resolved hyperspectral measurements of an observed scene. A hyperspectral lidar setup was designed and assembled in laboratory with the goal of performing outdoors measurements of targets at distances up to 175 m. The sensing capabilities of the system are shown for hard and distributed targets, in the form of aerosol clouds. Molecular absorption measurements, as well as thickness measurements for both transparent and translucent targets, are shown. Using the coherent configuration, which is the third one that was considered, it is possible to make active measurements of a target by using one of the pulse trains as a local oscillator. The use of a local oscillator opens the door to high sensitivity vibrometry, which is impossible with the incoherent configuration. An analytical model for the power collection capabilities of a single-transverse-mode system, which has to be used for coherent measurements, is developed and experimentally validated. The usual referencing technique, which is used to correct for fluctuations in comb parameters, is modified and adapted to the case of coherent vibrometry. Range-resolved vibrometry measurements are performed, demonstrating the capability of the system to extract a human voice signal from the vibrations of a wall.
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Teterukovskiy, Alexei. „Computational statistics with environmental and remote sensing applications /“. Umeå : Dept. of Forest Economics, Swedish Univ. of Agricultural Sciences, 2003. http://epsilon.slu.se/s277.pdf.

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8

Chon, Suet-ling, und 莊雪玲. „Remote sensing applications in studying marine biological processes“. Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31255826.

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9

Miller, S. T. „Remote sensing applications to flood hydrology in Belize“. Thesis, Aston University, 1986. http://publications.aston.ac.uk/14242/.

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The research compares the usefullness of four remote sensing information sources, these being LANDSAT photographic prints, LANDSAT computer compatible tapes, Metric Camera and SIR-A photographic prints. These sources provide evaluations of the catchment characteristics of the Belize and Sibun river basins in Central America. Map evaluations at 1:250,000 scale are compared to the results of the same scale, remotely sensed information sources. The values of catchment characteristics for both maps and LANDSAT prints are used in multiple regression analysis, providing flood flow formulae, after investigations to provide a suitable dependent variable discharge series are made for short term records. The use of all remotely sensed information sources in providing evaluations of catchment characteristics IS discussed. LANDSAT prints and computer compatible tapes of a post flood scene are used to estimate flood distributions and volumes. These are compared to values obtained from unit hydrograph analysis, using the dependent discharge series and evaluate the probable losses from the Belize river to the floodplain, thereby assessing the accuracy of LANDSAT estimates. Information relating to flood behaviour is discussed in terms of basic image presentation as well as image processing. A cost analysis of the purchase and use of all materials is provided. Conclusions of the research indicate that LANDSAT print material may provide information suitable for regression analysis at levels of accuracy as great as those of topographic maps, that the differing information sources are uniquely applicable and that accurate estimates of flood volumes may be determined even by post flood imagery.
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Bahadori, Keyvan. „Spaceborne reflector antennas for advanced remote sensing applications“. Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1562125061&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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11

Oppenheimer, Clive. „Volcanology from space : applications of infrared remote sensing“. Thesis, Open University, 1991. http://oro.open.ac.uk/57337/.

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Remote sensing techniques are being used increasingly to address volcanological problems. This thesis is concerned with the interpretation of multispectral infrared data of volcanic thermal features. Data from the two short wavelength infrared (SWIR) bands of the Landsat Thematic Mapper (TM) are used to constrain sizes and temperatures of subpixel resolution hot spots. Analysis of a 1989 TM scene of Lonquimay volcano suggests a cooling from 250 to 170°C of the crust of an active lava flow down 1.5 km of its length. Estimates of the summed radiative and convective heat losses from the flow top fall from 6 to 3 MW per 30 x 30 m pixel downflow. Thermal data were collected at volcanoes in Chile, Nicaragua and Italy to test assumptions explicit in such calculations. These surveys suggest that SWIR emission from fumarole fields is dominated by that from the interior walls of vents, and that surface temperatures around fumarole vents are lower than those of typical active lava bodies. The relative response of the two SWIR sensors of the TM is sensitive to such differences and therefore provides a basis for the interpretation of thennal anomalies known only from satellite data. Comparison of measurements in the two SWIR bands is petfonned with fourteen TM scenes recorded between 1984 and 1991, of a persistent hot spot at Lascar volcano, Chile. Evolution of the thennal source is charted by comparing the summed spectral radiance in each of the SWIR bands. Thus it appears that Lascar has experienced at least two periods of lava dome growth punctuated by the explosive eruptions of 1986 and 1990. Infrared sensors to be deployed on forthcoming remote sensing platfonns, including the Japanese Earth Resources Satellite and NASA's Earth Observing System, promise to constrain thennal emissions from volcanoes more effectively than possible with existing orbital systems. These investigations will improve understanding of the physical processes that influence the emplacement of lavas, as well as the potential for detecting eruption precursors and evaluating volcanic hazards.
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Tadros, Antoine. „Statistical background modeling and applications in remote sensing“. Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASM031.

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Cette thèse aborde certains problèmes de télédétection et de modélisation statistique de fond en utilisant la théorie a-contrario et des modèles de réseaux neuronaux artificiels. Le travail est motivé par deux applications en télédétection où le contrôle des fausses alarmes est un problème en raison de la large échelle des problèmes.L'identification et la mesure des sites de dépôts pétroliers à l'aide d'images satellites ont une valeur commerciale et stratégique importante. Nous nous intéressons ici au premier aspect : la détection de sites de stockage de pétrole par l'analyse de grandes quantités d'images satellite couvrant un pays ou un continent entier. Dans ce contexte, pour être utile, un algorithme doit atteindre un taux de rappel élevé tout en contrôlant le nombre de fausses détections et avec un coût de calcul réduit. La première méthode proposée ici commence par la détection d'objets circulaires, qui sont ensuite regroupés à l'aide de méthodes a-contrario ; en effet, les dépôts pétroliers correspondent souvent à un groupe dense de bâtiments cylindriques. L'approche est complétée par une procédure de patch-matching a-contrario pour récupérer les réservoirs manquants. Comme la méthode repose fortement sur la détection d'objets circulaires, plusieurs algorithmes de détection de cercles dans des images satellite à faible résolution sont comparés. L'algorithme a-contrario est également comparé à deux architectures de réseaux neuronaux pour la segmentation sémantique.La deuxième application de la télédétection est la détection des points chauds de jour à l'aide d'images satellites multibandes qui ne comportent pas de bandes thermiques. Cela permet de surveiller l'activité des raffineries de pétrole, des cimenteries et des aciéries, ainsi que l'activité des volcans.La première méthode proposée est basée sur un algorithme de détection d'anomalies.Une deuxième approche repose sur la mesure de l'adéquation des radiances mesurées dans les bandes spectrales sélectionnées au modèle du corps noir.Enfin, cette thèse traite de la détection d'éléments hors distribution, en anglais "Out-of-Distribion'' (OOD) detection, dans les méthodes d'apprentissage profond. Une première approche consiste à compléter l'ensemble de données d'apprentissage par des données étrangères affectées à une classe supplémentaire hors distribution. L'entraînement du modèle sur un ensemble de données séparé aide ce dernier à discriminer les échantillons hors distribution, y compris ceux auxquels le modèle n'a jamais été exposé pendant l'entraînement. Une approche non supervisée de la détection des OOD est également présentée. Pour ce faire, une nouvelle couche de réseau neuronal est proposée, qui impose une représentation gaussienne pour une classe donnée. Grâce à cette nouvelle couche, chaque classe cible peut être représentée par une distribution gaussienne. Les nouveaux échantillons sont ensuite évalués pour déterminer s'ils appartiennent ou non à une classe cible en effectuant un test du chi-2 pour chacun d'entre eux. Les échantillons rejetés par tous les tests sont considérés comme OOD. Cette méthodologie permet également d'identifier les échantillons ambigus lorsqu'ils sont validés par plus d'une classe
This thesis addresses some problems in remote sensing and statistical background modeling using the a-contrario theory and artificial neural network models. The work is motivated by two applications in remote sensing where the control of false alarms is an issue due to the large-scale nature of the problems.The identification and measuring of oil depots using satellite images has important commercial and strategic value. Here is addressed the former: the detection of oil storage sites while analyzing vast quantities of satellite images covering a whole country or continent. In this context, to be useful an algorithm needs to achieve a high recall while controlling the number of false detections and with a reduced computational cost. The first method proposed here starts by detecting circular objects, which are then clustered using the a-contrario framework; indeed, oil depots often correspond to a dense group of cylindrical buildings. The approach is completed by an a-contrario patch-matching procedure to recover the missing tanks. Since the method relies heavily on the detection of circular objects, several algorithms for detecting circles in low-resolution satellite images are compared. The a-contrario algorithm is also compared to two neural-network architectures for oil depot segmentation.The second remote sensing application is the detection of hot spots in the daytime using multi-band satellite images that do not have thermal bands. This allows the monitoring of the activity of oil refineries, cement works, and steel mills as well as the activities of volcanoes.The first proposed method is based on an anomaly detection algorithm.A second approach relies on measuring the fitness of the measured radiances in the selected spectral bands to the black body model.Finally, this thesis deals with out-of-distribution (OOD) detection in deep learning methods. A first approach is to supplement the training dataset with extraneous data assigned to an additional out-of-distribution class. Training the model on a segregated dataset helps the model to discriminate out-of-distribution samples, including those the model was never exposed to during training. An unsupervised approach to OOD detection is also presented. For that, a new neural network layer is proposed that enforces a Gaussian embedding for each class. Using this new layer, each target class can be represented by a Gaussian distribution. New samples are then evaluated as belonging to a target class or not by performing a chi-square test for each one. Samples rejected by all tests are considered OOD. This methodology also allows to identify ambiguous samples when validated by more than one class
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Ali, Khalid A. „PREDICTION OF WATER QUALITY PARAMETERS FROM VIS-NIR RADIOMETRY: USING LAKE ERIE AS A NATURAL LABORATORY FOR ANALYSIS OF CASE 2 WATERS“. Kent State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=kent1309980508.

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14

Brewer, Charles Kenneth. „Remote Sensing Applications to Support Sustainable Natural Resource Management“. The University of Montana, 2007. http://etd.lib.umt.edu/theses/available/etd-12282007-164513/.

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The original design of this dissertation project was relatively simple and straightforward. It was intended to produce one single, dynamic, classification and mapping system for existing vegetation that could rely on commonly available inventory and remote sensing data. This classification and mapping system was intended to provide the analytical basis for resource planning and management. The problems encountered during the first phase of the original design transformed this project into an extensive analysis of the nature of these problems and a decade-long remote sensing applications development endeavor. What evolved from this applications development process is a portion of what has become a "system of systems" to inform and support natural resource management. This dissertation presents the progression of work that sequentially developed a suite of remote sensing applications designed to address different aspects of the problems encountered with the original project. These remote sensing applications feature different resource issues, and resource components and are presented in separate chapters. Chapter one provides an introduction and description of the project evolution and chapter six provides a summary of the work and concluding discussion. Chapters two through five describe remote sensing applications that represent related, yet independent studies that are presented essentially as previously published. Chapter two evaluates different approaches to classifying and mapping fire severity using multi-temporal Landsat TM data. The recommended method currently represents the analytical basis for fire severity data produced by the USDA Forest Service and the US Geological Survey. Chapter three also uses multi-temporal Landsat data and compares quantitative, remote-sensing-based change detection methods for forest management related canopy change. The recommended method has been widely applied for a variety of forest health and disaster response applications. Chapter four presents a method for multi-source and multi-classifier regional land cover mapping that is currently incorporated in the USDA Forest Service Existing Vegetation Classification and Mapping Technical Guide. Chapter five presents a study using nearest neighbor imputation methods to generate geospatial data surfaces for simulation modeling of vegetation through time and space. While these results have not yet been successful enough to support widespread adoption and implementation, it is possible that these general methods can be adapted to perform adequately for simulation modeling data needs.
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15

Tooke, Thoreau Rory. „Remote sensing applications for vegetation management in urban environments“. Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/11502.

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Vegetation has been identified as an essential component of healthy urban environments, and the benefits of urban vegetation range widely from influences on the physical conditions of the city to the social well-being of the people who reside in these areas. As a result, ongoing research is important to understand the dynamic spatial components of urban vegetation to help urban planners and scholars manage this valuable resource. Advanced remote sensing technologies, such as high spatial resolution sensors and laser scanning devices, are useful tools for examining urban environments since they can capture detailed information regarding the material and structural composition of the urban surface. By providing a complete coverage of urban environments remote sensing technologies enable new possibilities to quantify the contributions of urban vegetation for a wealth of active processes in urban areas. The studies in this thesis examine several remote sensing devices to demonstrate the influence of urban vegetation on both physical and social aspects of urban environments. Three studies comprise the body of this work. They present new geographic techniques using remote sensing for: 1) the detailed classification of urban vegetation conditions; 2) quantifying the contribution of trees to solar radiation available for building rooftops; and 3) examining socioeconomic disparities related to urban green-space.
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Buehler, Stefan. „Remote sensing of atmospheric composition for climate applications : Habilitationschrift“. Doctoral thesis, Bremen : University of Bremen, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-18528.

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17

Rambat, Shuib. „A low-cost remote sensing system for agricultural applications“. Thesis, Aston University, 2012. http://publications.aston.ac.uk/16472/.

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This research develops a low cost remote sensing system for use in agricultural applications. The important features of the system are that it monitors the near infrared and it incorporates position and attitude measuring equipment allowing for geo-rectified images to be produced without the use of ground control points. The equipment is designed to be hand held and hence requires no structural modification to the aircraft. The portable remote sensing system consists of an inertia measurement unit (IMU), which is accelerometer based, a low-cost GPS device and a small format false colour composite digital camera. The total cost of producing such a system is below GBP 3000, which is far cheaper than equivalent existing systems. The design of the portable remote sensing device has eliminated bore sight misalignment errors from the direct geo-referencing process. A new processing technique has been introduced for the data obtained from these low-cost devices, and it is found that using this technique the image can be matched (overlaid) onto Ordnance Survey Master Maps at an accuracy compatible with precision agriculture requirements. The direct geo-referencing has also been improved by introducing an algorithm capable of correcting oblique images directly. This algorithm alters the pixels value, hence it is advised that image analysis is performed before image georectification. The drawback of this research is that the low-cost GPS device experienced bad checksum errors, which resulted in missing data. The Wide Area Augmented System (WAAS) correction could not be employed because the satellites could not be locked onto whilst flying. The best GPS data were obtained from the Garmin eTrex (15 m kinematic and 2 m static) instruments which have a highsensitivity receiver with good lock on capability. The limitation of this GPS device is the inability to effectively receive the P-Code wavelength, which is needed to gain the best accuracy when undertaking differential GPS processing. Pairing the carrier phase L1 with the pseudorange C/A-Code received, in order to determine the image coordinates by the differential technique, is still under investigation. To improve the position accuracy, it is recommended that a GPS base station should be established near the survey area, instead of using a permanent GPS base station established by the Ordnance Survey.
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Johnson, Jennifer Erin. „Remote sensing applications of uncooled long-wave infrared thermal imagers“. Thesis, Montana State University, 2012. http://etd.lib.montana.edu/etd/2012/johnson/JohnsonJ0812.pdf.

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The commercial development of microbolometer uncooled long-wave thermal infrared imagers in conjuncture with advanced radiometric calibration methods developed at Montana State University has led to new uses of thermal imagery in remote sensing applications. As a result of being uncooled, microbolometer imagers are notably lighter and cheaper than typical cooled imagers, making them ideal for remote sensing. Two novel uses are discussed in the work presented here. The first is the imaging of beehives in order to remotely determine the hive vitality. Bees thermally regulate their hives to a narrow range of temperatures that creates a thermal signature seen in thermal infrared images. For each of the hives imaged, frame counts (or the number of full frames of bees in each hive) were found by manual inspection. Linear regressions of the normalized frame counts of the hives were performed versus the measured hive thermal radiance values. The resulting plots showed a strong relationship between the normalized frame count and the mean radiance of each hive, particularly in images taken just prior to dawn. The second novel use was imaging vegetation exposed to large ground concentrations of CO ����� over a four-week period in summer for use in leak detection. A CO ����� leak was simulated in a test field run by the Zero Emissions Research and Technology Center. Thermal infrared images were acquired along with visible and near-infrared reflectance images of the exposed vegetation and healthy control vegetation. Thermal radiance statistics were measured and a regression was performed versus the day of the experiment. The infrared data were found to have a strong R ² value and clearly show the effect of the CO ����� on the vegetation. An additional regression was run on the infrared data combined with the reflectance data, and this was found to not add any unique information to the vegetation reflectance data. Both methods were found to independently indicate the potential of a CO ����� leak before it was detected visually.
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Reed, Jamie. „Development of long life minature cooler for remote sensing applications“. Thesis, University of Oxford, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409765.

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Murnion, Shane D. „Neural and genetic algorithm applications in GIS and remote sensing“. Thesis, Queen's University Belfast, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337024.

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21

Weeks, Scarla Jeanne. „Specific applications of satelite remote sensing to the Benguela ecosystem“. Doctoral thesis, University of Cape Town, 2005. http://hdl.handle.net/11427/11574.

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Bibliography: p. 111-115.
The objective of this thesis was to utilise high resolution satellite data, from the NOAA AVHRR and OrbView-2 SeaWiFS sensors, to investigate the upper layer dynamics of the Benguela ecosystem in more detailed space and time scales than previously undertaken. The standard for SeaWiFS bio-optical algorithms and processing parameters are not ideal for the highly productive Benguela waters. Hence, a detailed investigation was undertaken, and the processing parameters modified for more optical application to Benguela waters. Examination of the individual radiances used in the bio-optical algorithm revealed that constituents, other than chlorophyll, were at times contributing significantly to the in-water light field. The approach adopted in this thesis was that the application of satellite data to Benguela waters should be considered either as qualitative, for event scale phenomena, or quantitative, for the longterm study.
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Cassidy, Scott L. „Millimetre-wave FMCW radar for remote sensing and security applications“. Thesis, University of St Andrews, 2015. http://hdl.handle.net/10023/7856.

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This thesis presents a body of work on the theme of millimetre-wave FMCW radar, for the purposes of security screening and remote sensing. First, the development of an optimised software radar signal processor will be outlined. Through use of threading and GPU acceleration, high data processing rates were achieved using standard PC hardware. The flexibility of this approach, compared to specialised hardware (e.g. DSP, FPGA etc…), allowed the processor to be rapidly adapted and has produced a significant performance increase in a number of advanced real-time radar systems. An efficient tracker was developed and was successfully deployed in live trials for the purpose of real-time wave detection in an autonomous boat control system. Automated radar operation and remote data telemetry functions were implemented in a terrain mapping radar to allow continuous monitoring of the Soufrière Hills volcano on the Caribbean island of Montserrat. This work concluded with the installation of the system 3 km from the volcano. Hardware modifications were made to enable coherent measurement in a number of existing radar systems, allowing phase sensitive measurements, including range-Doppler, to be performed. Sensitivity to displacements of less than 200 nm was demonstrated, which is limited by the phase noise of the system. Efficient compensation techniques are presented which correct for quadrature mixer imbalance, FMCW chirp non-linearity, and scanner drive distortions. In collaboration with the Home Office, two radar systems were evaluated for the stand-off detection of concealed objects. Automatic detection capability, based on polarimetric signatures, was developed using data gathered under controlled conditions. Algorithm performance was assessed through blind testing across a statistically significant number of subjects. A detailed analysis is presented, which evaluates the effect of clothing and object type on detection efficiency.
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Sihra, Kamaljit S. „Laboratory measurements of near-infrared methane bands for remote sensing of the Jovian atmosphere“. Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299388.

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Matthews, Amy L. „Applications of infrared fibers in temperature sensing“. Thesis, Virginia Tech, 1988. http://hdl.handle.net/10919/45909.

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As attenuation in silica based fibers approaches its ultimate theoretical limit, investigation is in progress to develop new materials which exhibit lower losses than silica. These bulk materials could then be used to fabricate ultralow loss optical fibers which operate farther out in the infrared than do silica fibers. Such infrared fibers could be used in long, repeaterless telecommunications links, the transmission of CO and CO2 laser power, and in several sensing mechanisms. This thesis presents an overview of these new fibers and how they can be applied in noncontact temperature measurement. Fiber optic temperature sensing is thus reviewed, and an optical fiber pyrometer is discussed.


Master of Science
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Stefanou, Marcus S. „Spectral image utility for target detection applications /“. Online version of thesis, 2008. http://hdl.handle.net/1850/7043.

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McLean, Andrew Lister. „Applications of maximum entropy data analysis“. Thesis, University of Southampton, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.319161.

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27

Solomon, Semere. „Remote Sensing and GIS : Applications for Groundwater Potential Assessment in Eritrea“. Doctoral thesis, KTH, Civil and Architectural Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3491.

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An integrated approach with remote sensing, GeographicInformation Systems (GIS) and more traditional fieldworktechniques was adopted to assess the groundwater potential inthe central highlands of Eritrea. Digitally enhanced colorcomposites and panchromatic images of Landsat TM and Spot wereinterpreted to produce thematic maps such as lithology andlineaments. The potential of the Advanced Spaceborne ThermalEmission and Reflection Radiometer (ASTER) data forlithological and lineament mapping was evaluated. Topographicparameters such as surface curvature, slope and drainagesystems were derived from digital elevation models and used tomap landforms. Digital elevation models (DEM) derived fromcontours and acquired in the Shuttle Radar Topographic Mission(SRTM) were compared in relation to location, drainage networksand lineament extraction. Fracture patterns and spacing weremeasured in the field in different rock types and compared withlineaments. Selected springs and wells were visited to studytheir topographic and hydrogeological setting. Well logs,pumping tests, water table depth in dry and wet season as wellas location of wells were collected. All thematic layersincluding hydrogeological data were integrated and analysed ina geographic information system. A groundwater potential mapwas generated and compared with yield data. Groundwaterrecharge was estimated based on water level fluctuations inlarge dug wells and chloride mass-balance method.

Principal component analysis for rock type mapping providedbetter results with ASTER than with Landsat TM data. DEM datapermitted to create detailed landform maps useful torgroundwater potential assessment. DEM derived from SRTM dataare better for detection of drainage systems and linearfeatures than those derived from contours. Most of the fracturesystems corresponding to lineaments are either extensionalrelated to normal faults and dykes, or shear fractures relatedto strike-slip faults. N-S, NW-SE, WNW-ESE, NE-SW and ENE-WSWare dominant fracture orientations with often very densespacing. High yielding wells and springs are often related tolarge lineaments and corresponding structural features such asdykes. Typically wells and springs in basaltic areas havehigher yields mainly due to primary joints. Young alluvialsediments with high permeability and deeply weathered rocklayers are important for water supply especially in hydraulicconnection with fracture systems in crystalline bedrock.Groundwater potential zones demarcated through the model are inagreement with bore well yield data. The spatial distributionof groundwater potential zones shows regional patterns relatedto lithologies, lineaments, drainage systems and landforms.Recharge rates of 10 - 50 mm were estimated in this region. Theresults demonstrate that the integration of remote sensing,GIS, traditional fieldwork and models provide a powerful toolin the assessment and management of water resources anddevelopment of groundwater exploration plans.

Key words:Remote sensing, Geographic InformationSystems, groundwater, geomorphology, Digital elevation model,lithology, hard rock, lineament, structures, hydrogeology,Eritrea

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Ross, Timothy J. „Remote sensing applications in an alfalfa capability assessment of saline soils“. Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28330.

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In the Cariboo-Chilcotin region of British Columbia, two types of soil salinity have been recognized; natural salinity (Solonetzic soils) and secondary salinity. Soil salinity of either type can be a significant limiting factor in alfalfa (Medicago sp.) production. Stress-related changes in individual plant colour and plant morphology and invasion of the stand by salt-tolerant forbs and grasses affect the amount and direction of the radiation reflected and/or emitted by growing plants. Remote sensing techniques are capable of measuring that radiation and, therefore, offer the potential for quantitative assessment of plant stress caused by saline soils. A remote sensing study was initiated to develop a computer-assisted classification of categories of salt-affected soils. Site biophysical data and reflectance data from digitized infrared diapositives collected from a 50m x 50m grid of "training sites", were integrated to produce a series of digital numbers representative of different classes of salt-affected soils. The possible confounding effects of exposure, processing, geometric and atmospheric effects, and image window position on the interpretation of reflectance patterns were first evaluated. Alfalfa exposure fell on the linear portion of the Density-log Exposure curve indicating a satisfactory exposure. The IR balance of the film (22) was more appropriate to higher altitude use (12000 ft asl) than the altitude of the photographic flights (5500 ft asl) resulting in a slightly narrower range of near infrared reflectance values. Variation between four distinct images was not significantly different (P<0.05) so the complete data set was used for analysis. Sites positioned near photograph borders were avoided as decreased reflectance was noted at these locations. Parameters used in classification were selected on the strength of their correlation with other parameters in the system. The spectral-plant-soil model was developed using a correlation threshold (r > +0.35) to select parameters followed by a morphological systems analysis to devise the component systems. The key system parameters were; Spectral: Yellow(Green), Magenta(Red), Cyan(NIR), Ratio R3(M/C) and Ratio R4(M/Y); Plant: ALF(alfalfa), SALT(salt-tolerant grasses), GRASS(domestic grasses) and PUNU (Puccinellia nuttalli); Soil: PHW(pH water), EC (electrical conductivity), ECa (exchangeable Ca), ENa (exchangeable Na⁺), EK (exchangeable K⁺) BD (Bulk density) and E (elevation). Spectral parameters C and R4 were most strongly correlated with ALF (r = +0.40 and r = -0.35, respectively) and were selected as grouping parameters for cluster analysis. The training sites were clustered into three groups. The spectral data for these groups was used to devise digital numbers in the Y,M and C dye-layers for use in the Meridian-PC image analysis system. The plant and soil parameter trends (x + 1 sd and % CV) were used to determine continuous classifications representing LOW ALF (low alfalfa capability on saline and/or sodic soils), MED ALF (medium alfalfa capability, including areas of developing salinity with intermediate values for soil parameters) and HIGH ALF (high alfalfa capability which may include areas with high populations of domestic grass species in lieu of alfalfa which had declined for reasons unrelated to salinity). Parameter means were significantly different (P<0.05) for LOW ALF vs MED ALF, LOW ALF vs HIGH ALF and in some, but not all cases for MED ALF vs HIGH ALF. The BIOM (biomass) data set reflected higher production in the HIGH ALF class. Total nitrogen (TN) and organic matter (ORGC) showed negative correlations with saline soil indicators and positive trends with alfalfa. Total N levels were low to medium in comparison to common ratings for effective alfalfa production. More available phosphorus (PHTOS) was present in the LOW ALF than in the HIGH ALF, although all areas would require supplemental phosphorus to improve productivity. The spectral signatures supplied to the Meridian-PC image analysis system were used to produce capability maps of the study site depicting three alfalfa production classes and an unclassified category comprising values outside the spectral ranges established for the three classes. The training sites were grouped into LOW ALF (18%), MED ALF (43%) and HIGH ALF (37%). Computer-assisted supervised classification of the data improved the discrimination of the groups to produce a distribution of LOW ALF (31%), MED ALF (42%) and HIGH ALF (28%). This study successfully discriminated digital numbers which were indicative of classes of vegetation which are, in turn, reflective of gradations in saline soil conditions. Computer-based analysis of digitized CIR aerial photographs may, therefore, be a valuable tool in the identification and evaluation of the impact of saline soils on crop productivity.
Land and Food Systems, Faculty of
Graduate
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29

Ao, Chi On 1970. „Electromagnetic wave scattering by discrete random media with remote sensing applications“. Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/16782.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2001.
Includes bibliographical references (p. 171-182).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
The scattering of electromagnetic waves in medium with randomly distributed discrete scatterers is studied. Analytical and numerical solutions to several problems with implications for the active and passive remote sensing of the Earth environment are obtained. The quasi-magnetostatic (QMS) solution for a conducting and permeable spheroid under arbitrary excitation is presented. The spheroid is surrounded by a weakly conducting background medium. The magnetic field inside the spheroid satisfies the vector wave equation, while the magnetic field outside can be expressed as the gradient of the Laplace solution. We solve this problem exactly using the separation of variables method in spheroidal coordinates by expanding the internal field in terms of vector spheroidal wavefunctions. The exact formulation works well for low to moderate frequencies; however, the solution breaks down at high frequency due to numerical difficulty in computing the spheroidal wavefunctions. To circumvent this difficulty, an approximate theory known as the small penetration-depth approximation (SPA) is developed. The SPA relates the internal field in terms of the external field by making use of the fact that at high frequency, the external field can only penetrate slightly into a thin skin layer below the surface of the spheroid. For spheroids with general permeability, the SPA works well at high frequency and complements the exact formulation. However, for high permeability, the SPA is found to give accurate broadband results. By neglecting mutual interactions, the QMS frequency response from a collection of conducting and permeable spheroids is also studied.
(cont.) In a dense medium, the failure to properly take into account of multiple scattering effects could lead to significant errors. This has been demonstrated in the past from extensive theoretical, numerical, and experimental studies of electromagnetic wave scattering by densely packed dielectric spheres. Here, electromagnetic wave scattering by dense packed dielectric spheroids is studied both numerically through Monte Carlo simulations and analytically through the quasi-crystalline approximation (QCA) and QCA with coherent potential (QCA-CP). We assume that the spheroids are electrically small so that single-particle scattering is simple. In the numerical simulations, the Metropolis shuffling method is used to generate realizations of configurations for non-interpenetrable spheroids. The multiple scattering problem is formulated with the volume integral equation and solved using the method of moments with electrostatic basis functions. General expressions for the self-interaction elements are obtained using the low-frequency expansion of the dyadic Green's function, and radiative correction terms are included. Results of scattering coefficient, absorption coefficient, and scattering matrix for spheroids in random and aligned orientation configurations are presented. It is shown that independent scattering approximation can give grossly incorrect results when the fractional volume of the spheroids is appreciable.
(cont.) In the analytical approach, only spheroids in the aligned configuration are solved. Low-frequency QCA and QCA-CP solutions are obtained for the average Green's function and the effective permittivity tensor. For QCA-CP, the low-frequency expansion of the uniaxial dyadic Green's function is required. The real parts of the effective permittivities from QCA and QCA-CP are compared with the Maxwell-Garnett mixing formula. ...
by Chi On Ao.
Ph.D.
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Reichle, Rolf H. (Rolf Helmut) 1968. „Variational assimilation of remote sensing data for land surface hydrologic applications“. Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/28220.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2000.
Includes bibliographical references (p. 283-192).
Soil moisture plays a major role in the global hydrologic cycle. Most importantly, soil moisture controls the partitioning of available energy at the land surface into latent and sensible heat fluxes. We investigate the feasibility of estimating large-scale soil moisture profiles and related land surface variables from low-frequency (L-band) passive microwave remote sensing observations using weak-constraint variational data assimilation. We extend the iterated indirect representer method, which is based on the adjoint of the hydrologic model, to suit our application. The four-dimensional (space and time) data assimilation algorithm takes into account model and measurement uncertainties and provides optimal estimates by implicitly propagating the full error covariances. Explicit expressions for the posterior error covariances are also derived. We achieve a dynamically consistent interpolation and extrapolation of the remote sensing data in space and time, or equivalently, a continuous update of the model predictions from the data. Our hydrologic model of water and energy exchange at the land surface is expressly designed for data assimilation. It captures the key physical processes while remaining computationally efficient. The assimilation algorithm is tested with a series of experiments using synthetically generated system and measurement noise. In a realistic environment based on the Southern Great Plains 1997 (SGP97) hydrology experiment, we assess the performance of the algorithm under ideal and non ideal assimilation conditions. Specifically, we address five topics which are crucial to the design of an operational soil moisture assimilation system. (1) We show that soil moisture can be satisfactorily estimated at scales finer than the resolution of the brightness images (downscaling), provided sufficiently accurate fine-scale model inputs are available. (2) The satellite repeat cycle should be shorter than the average interstorm period. (3) The loss of optimality by using shorter assimilation intervals is offset by a substantial gain in computational efficiency. (4) Soil moisture can be satisfactorily estimated even if quantitative precipitation data are not available. (5) The assimilation algorithm is only weakly sensitive to inaccurate specification of the soil hydraulic properties. In summary, we demonstrate the feasibility of large-scale land surface data assimilation from passive microwave observations.
by Rolf H. Reichle.
Ph.D.
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Chesney, James R., und Roger Bakos. „AFFORDABLE GROUND STATION EQUIPMENT FOR COMMERCIAL AND SCIENTIFIC REMOTE SENSING APPLICATIONS“. International Foundation for Telemetering, 1995. http://hdl.handle.net/10150/608539.

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International Telemetering Conference Proceedings / October 30-November 02, 1995 / Riviera Hotel, Las Vegas, Nevada
The remote sensing industry is experiencing an unprecedented rush of activity to deploy commercial and scientific satellites. NASA and its international partners are leading the scientific charge with The Earth Observation System (EOS) and the International Space Station Alpha (ISSA). Additionally, there are at least ten countries promoting scientific/commercial remote sensing satellite programs. Within the United States, commercial initiatives are being under taken by a number of companies including Computer Technology Associates, Inc., EarthWatch, Inc., Space Imaging, Inc., Orbital Imaging Corporation and TRW, Inc. This activity is due to factors including: technological advances which have lead to significant reductions in the costs to build and deploy satellites; an awareness of the importance of understanding human impact on the ecosystem; and a desire to collect and sell data some believe will be worth $1.5 billion (USD) per year within five years. The success and usefulness of these initiatives, both scientific and commercial, depends largely on the ease and cost of providing remotely sensed data to value added resellers and end-users. A number of these spacecraft will provide an interface directly to users. To provide these data to the largest possible user base, ground station equipment must be affordable and the data must be distributed in a timely manner (meaning seconds or minutes, not days) over commercial network and communications equipment. TSI TelSys, Inc. is developing ground station equipment that will perform both traditional telemetry processing and the bridging and routing functions required to seamlessly interface commercial local- and wide-area networks and satellite communication networks. These products are based on Very Large Scale Integration (VLSI) components and pipelined, multi-processing architectures. This paper describes TelSys’ product family and its envisioned use within a ground station.
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Westin, Benjamin Alexander. „Applications in Remote Sensing Using the Method of Ordered Multiple Interactions“. Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/19346.

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The Method of Ordered Multiple Interactions provides a numerical solution to the integral
equations describing surface scattering which is both computationally efficient and reliably
convergent. The method has been applied in a variety of ways to solving the electromagnetic
scattering from perfectly-conducting rough surfaces. A desire to more accurately predict
the scattering from natural terrain has led to the representation of the surface material as
penetrable instead of conductive.

For this purpose, the Method of Ordered Multiple Interactions is applied to numerically
solve the electromagnetic scattering from randomly-rough dielectric surfaces. A primary
consequence of the penetrable surface material is the introduction of a pair of coupled integral equations in place of the single integral equation used to solve the problem with a perfectly conducting surface. The method is tested and analyzed by developing independent scattering solutions for canonical cases in a transform domain and by comparing results with solutions from other techniques.

The dielectric implementation of the Method of Ordered Multiple Interactions is used to solve
the electromagnetic scattering from a class of randomly-rough dielectric surfaces. This allows
for the characterization of the effect of a number of transmitter and surface parameters in the
scattering problem, observing bistatically and also specifically in the backscatter direction.

MOMI is then applied as a method to examine subsurface penetration characteristics from
a similar family of rough surfaces. Characteristics of the environment parameters and the
scattered field itself are examined, and the numerical challenges associated with observing
beneath the surface are identified and addressed.

The Method of Ordered Multiple Interactions is then incorporated as a major component of
a larger solution which computes the total scattering when a dielectric object is buried just
beneath the rough surface. This hyrid approach uses MOMI and the Method of Moments to
iteratively account for multiple interactions between the target and the dielectric interface,
enabling the study of scattering from the combined environment of a rough surface and the
embedded object, as well as the individual scattering events which combine to form the
steady-state solution.
Ph. D.
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Peng, Yuxiang. „GNSS-based Spacecraft Formation Flying Simulation and Ionospheric Remote Sensing Applications“. Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/79594.

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The Global Navigation Satellite System (GNSS) is significantly advantageous to absolute and relative navigation for spacecraft formation flying. Ionospheric remote sensing, such as Total Electron Content (TEC) measurements or ionospheric irregularity studies are important potential Low Earth Orbit (LEO) applications. A GNSS-based Hardware-in-the-loop (HIL) simulation testbed for LEO spacecraft formation flying has been developed and evaluated. The testbed infrastructure is composed of GNSS simulators, multi-constellation GNSS receiver(s), the Navigation & Control system and the Systems Tool Kit (STK) visualization system. A reference scenario of two LEO spacecraft is simulated with the initial in-track separation of 1000-m and targeted leader-follower configuration of 100-m along-track offset. Therefore, the feasibility and performance of the testbed have been demonstrated by benchmarking the simulation results with past work. For ionospheric remote sensing, multi-constellation multi-frequency GNSS receivers are used to develop the GNSS TEC measurement and model evaluation system. GPS, GLONASS, Galileo and Beidou constellations are considered in this work. Multi-constellation GNSS TEC measurements and the GNSS-based HIL simulation testbed were integrated and applied to design a LEO satellite formation flying mission for ionospheric remote sensing. A scenario of observing sporadic E is illustrated and adopted to demonstrate how to apply GNSS-based spacecraft formation flying to study the ionospheric irregularities using the HIL simulation testbed. The entire infrastructure of GNSS-based spacecraft formation flying simulation and ionospheric remote sensing developed at Virginia Tech is capable of supporting future ionospheric remote sensing mission design and validation.
Master of Science
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Brooks, Evan B. „Fourier Series Applications in Multitemporal Remote Sensing Analysis using Landsat Data“. Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/23276.

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Researchers now have unprecedented access to free Landsat data, enabling detailed monitoring of the Earth's land surface and vegetation.  There are gaps in the data, due in part to cloud cover. The gaps are aperiodic and localized, forcing any detailed multitemporal analysis based on Landsat data to compensate.   Harmonic regression approximates Landsat data for any point in time with minimal training images and reduced storage requirements.  In two study areas in North Carolina, USA, harmonic regression approaches were least as good at simulating missing data as STAR-FM for images from 2001.  Harmonic regression had an R^2"0.9 over three quarters of all pixels. It gave the highest R_Predicted^2 values on two thirds of the pixels.  Applying harmonic regression with the same number of harmonics to consecutive years yielded an improved fit, R^2"0.99 for most pixels.   We next demonstrate a change detection method based on exponentially weighted moving average (EWMA) charts of harmonic residuals. In the process, a data-driven cloud filter is created, enabling use of partially clouded data.  The approach is shown capable of detecting thins and subtle forest degradations in Alabama, USA, considerably finer than the Landsat spatial resolution in an on-the-fly fashion, with new images easily incorporated into the algorithm.  EWMA detection accurately showed the location, timing, and magnitude of 85% of known harvests in the study area, verified by aerial imagery.   We use harmonic regression to improve the precision of dynamic forest parameter estimates, generating a robust time series of vegetation index values.  These values are classified into strata maps in Alabama, USA, depicting regions of similar growth potential.  These maps are applied to Forest Service Forest Inventory and Analysis (FIA) plots, generating post-stratified estimates of static and dynamic forest parameters.  Improvements to efficiency for all parameters were such that a comparable random sample would require at least 20% more sampling units, with the improvement for the growth parameter requiring a 50% increase. These applications demonstrate the utility of harmonic regression for Landsat data.  They suggest further applications in environmental monitoring and improved estimation of landscape parameters, critical to improving large-scale models of ecosystems and climate effects.
Ph. D.
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Ashcraft, Ivan S. „Microwave Remote Sensing of the Greenland Ice Sheet: Models and Applications“. Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd532.pdf.

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Yoshioka, Hiroki 1967. „Applications of transport theory in optical remote sensing of land surfaces“. Diss., The University of Arizona, 1999. http://hdl.handle.net/10150/284824.

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A particle/radiative transport theory widely used in nuclear engineering was applied to investigate photon transport in layers of land surfaces which consist of vegetation and soil for application to optical remote sensing. A numerical simulation code has been developed for three dimensional vegetation canopies to compute reflected radiation by the canopy-soil systems. The code solves a discretized form of the linear Boltzmann transport equation using an Adaptive Weighted Diamond-Differencing and source iteration method. Sample problems demonstrate variations of reflectance spectra of vegetation canopies as a function of soil brightness and leaf area index, and also indicate a pattern of spectral variations induced by the soil brightness changes. Special attention has been paid to the variation patterns of canopy reflectances, known as vegetation isolines. Mathematical expressions of vegetation isolines, called vegetation isoline equations, are derived in terms of canopy optical properties and two parameters that characterize soil optical properties called soil line parameters. Behavior of vegetation isolines is analyzed using the derived equations as a function of leaf area index and fractional area covered by green-vegetation. The analyses show certain trends of the behavior of vegetation isolines. The vegetation isoline equations are then applied to investigate the performance of two-band vegetation indices and to estimate the effects of the soil line parameters. It is concluded that the vegetation isoline equations are useful for investigating patterns of canopy reflectance variations and the effects of these patterns on vegetation indices.
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Strutt, Michael A. „Rediscovering the Dead: Practical Applications of Remote Sensing in Historic Cemeteries“. W&M ScholarWorks, 1991. https://scholarworks.wm.edu/etd/1539625656.

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Gudex-Cross, David James. „Remote Sensing Methods and Applications for Detecting Change in Forest Ecosystems“. ScholarWorks @ UVM, 2018. https://scholarworks.uvm.edu/graddis/966.

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Forest ecosystems are being altered by climate change, invasive species, and additional stressors. Our ability to detect these changes and quantify their impacts relies on detailed data across spatial and temporal scales. This dissertation expands the ecological utility of long-term satellite imagery by developing high quality forest mapping products and examining spatiotemporal changes in tree species abundance and phenology across the northeastern United States (US; the ‘Northeast’). Species/genus-level forest composition maps were developed by integrating field data and Landsat images to model abundance at a sub-pixel scale. These abundance maps were then used to 1) produce a more detailed, accurate forest classification compared to similar products and 2) construct a 30-year time-series of abundance for eight common species/genera. Analyzing the time-series data revealed significant abundance trends in notable species, including increases in American beech (Fagus grandifolia) at the expense of sugar maple (Acer saccharum). Climate was the dominant predictor of abundance trends, indicating climate change may be altering competitive relationships. Spatiotemporal trends in deciduous forest phenology – start and end of the growing season (SOS/EOS) – were examined based on MODIS imagery from 2001-2015. SOS exhibited a slight advancing trend across the Northeast, but with a distinct spatial pattern: eastern ecoregions showed advance and western ecoregions delay. EOS trended substantially later almost everywhere. SOS trends were linked to winter-spring temperature and precipitation trends; areas with higher elevation and fall precipitation anomalies had negative associations with EOS trends. Together, this work demonstrates the value of remote sensing in furthering our understanding of long-term forest responses to changing environmental conditions. By highlighting potential changes in forest composition and function, the research presented here can be used to develop forest conservation and management strategies in the Northeast.
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Darling, Paul Simon. „SAR modelling for ecological applications“. Thesis, University of Reading, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297315.

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40

Mtshemla, Kanyisa Sipho. „Mission design of a CubeSat constellation for in-situ monitoring applications“. Thesis, Cape Peninsula University of Technology, 2017. http://hdl.handle.net/20.500.11838/2633.

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Thesis (MEng (Electrical Engineering))--Cape Peninsula University of Technology, 2017.
Real-time remote monitoring of Africa’s resources, such as water quality, by using terrestrial sensors is impeded by the limited connectivity over the vast rural areas of the continent. Without such monitoring, the effective management of natural resources, and the response to associated disasters such as flooding, is almost impossible. A constellation of nanosatellites could provide near real-time connectivity with ground-based sensors that are distributed across the continent. This study evaluates the high level development of a mission design for a near real-time remote monitoring CubeSat constellation and ground segment for in-situ monitoring in regions of interest on the African continent. This would facilitate management of scarce resources using a low-cost constellation. To achieve this, the design concept and operation of a Walker constellation are examined as a means of providing connectivity to a low bit rate sensor network distributed across geographic areas of interest in South Africa, Algeria, Kenya and Nigeria. The mission requirements include the optimisation of the constellation to maintain short revisit times over South Africa and an investigation of the required communications link to perform the operations effectively. STK software is used in the design and evaluation of the constellations and the communications system. The temporal performance parameters investigated are access and revisit times of the constellations to the geographic areas mentioned. The types of constellation configurations examined, involved starting with a system level analysis of one satellite. This seed satellite has known orbital parameters. Then a gradual expansion of two to twelve satellites in one, two and three orbital planes follows. VHF, UHF and S-band communication links are considered for low data rate in-situ monitoring applications. RF link budgets and data budgets for typical applications are determined. For South Africa, in particular, a total of 12 satellites evenly distributed in a two-plane constellation at an inclination of 39° provide the optimal solution and offer an average daily revisit time of about 5 minutes. This constellation provides average daily access time of more than 16 hours per day. A case study is undertaken that decribes a constellation for the provision of maritime vessel tracking in the Southern African oceans using the Automated Information System (AIS). This service supports the Maritime Domain Awareness (MDA) initiative implemented by the South African Government, under its Operation Phakisa.
National Research Foundation (NRF) French South African Institute of Technology (F’SATI)
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Ouellette, Karli J. „Hydrologic applications of GPS site-position observations in the Western U.S“. Thesis, University of California, Irvine, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3605189.

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Permanent Global Positioning System (GPS) networks have been established around the globe for a variety of uses, most notably to monitor the activity of fault lines and tectonic plate motion. A model for utilizing GPS as a tool for hydrologic monitoring is also developed.

First, observations of the recent movement of the land surface throughout California by the Scripps Orbit and Permanent Array Center (SOPAC) GPS network are explored. Significant seasonal cycles and long term trends are related to historical observations of land subsidence. The pattern of deformation throughout the state appears to be caused by the occurrence of poroelastic deformation of the aquifer in the Central Valley, and elastic crustal loading by surface water and the winter snowpack in the Sierra Nevada Mountains. The result is a sort of teeter-totter motion between the Valley and the mountains where the Valley sinks in the dry season while the mountains lift, and the mountains sink in the wet season while the Valley lifts.

Next, the elastic crustal deformation caused by the winter snowpack is explored more thoroughly at 6 high elevations throughout the Western United States. Expected annual deformation as a result of thermoelastic and snow water equivalent are calculated using SNOTEL observations and an elastic half-space model. The results demonstrate the dominance of snow loading on the seasonal vertical land surface deformation at all 6 GPS stations. The model is then reversed and applied to the GPS vertical site-position observations in order to predict snow water equivalent. The results are compared to SNOTEL observations of snow water equivalent and soil moisture. The study concludes that GPS site-position observations are able to predict variations in snow water equivalent and soil moisture with good accuracy.

Then a model which incorporates both elastic crustal loading and poroelastic deformation was used to predict groundwater storage variations at 54 GPS stations throughout the Central Valley, CA. The results are compared to USGS water table observations from 43 wells. The predictions and observations show a similar magnitude and spatial pattern of groundwater depletion on both a seasonal and long term timescales. Depletion is focused on the southernmost part of the Valley where GPS reveals seasonal fluctuation of the water table around 2 m and 8 m/yr of water table decline during the study period. GPS also appears to respond to deformation from peat soils and changing reservoir storage in the northern parts of the Valley.

Finally, preliminary work exploring the potential for using GPS as a tool for monitoring snowmelt runoff and infiltration is explored at one station in Eastern Idaho. Taking the difference between the change in GPS water storage estimates with time and the change in SNOTEL observed snow water equivalent with time produces a time series of infiltration, or the amount of water added to storage in the geologic profile. Then subtracting the estimated infiltration and snow water equivalent from the total precipitation observed by SNOTEL produces a time series of runoff. The estimated runoff at the GPS site was compared to observations from a nearby stream gauge and the foundation for a more extensive comparison is laid out.

The overall impact of this work is to introduce the unique hydrologic information and monitoring capabilities which can be accessed through monitoring of the land surface position using GPS. As GPS networks grow and expand worldwide, the available data should be harnessed by the hydrologic community for the benefit of local water management as well as improvements to data assimilated models. The work presented here represents only a small fraction of the wealth of knowledge that could result from a budding field of GPS hydrologic remote sensing. (Abstract shortened by UMI.)

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Buyuksalih, Gurcan. „Geometric and radiometric calibration of video infrared imagers for photogrammetric applications“. Thesis, University of Glasgow, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284703.

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Voytenko, Denis. „Glaciological Applications of Terrestrial Radar Interferometry“. Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5856.

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Terrestrial Radar Interferometry (TRI) is a relatively new ground-based technique that combines the precision and spatial resolution of satellite interferometry with the temporal resolution of GPS. Although TRI has been applied to a variety of fields including bridge and landslide monitoring, it is ideal for studies of the highly-dynamic terminal zones of marine-terminating glaciers, some of which are known to have variable velocities related to calving and/or ocean-forced melting. My TRI instrument is the Gamma Portable Radar Interferometer, which operates at 17.2 GHz (1.74 cm wavelength), has two receiving antennas for DEM (digital elevation model) generation, and images the scenes at minute-scale sampling rates. Most of this TRI work has focused on two glaciers: Breiðamerkurjökull in Iceland and Helheim in Greenland. Monitoring the displacement of stationary points suggests velocity measurement uncertainties related to the instrument and atmosphere of less than 0.05 m/d. I show that the rapid sampling rate of the TRI can be used to observe velocity variations at the glacier terminus and assess the impact and spatial distribution of tidal forcing. Additionally, iceberg tracking in the amplitude imagery may provide insight about ocean currents near the terminus.
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Magee, Kevin S. „Segmentation, Object-Oriented Applications for Remote Sensing Land Cover and Land Use Classification“. University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1298040118.

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O'Bree, Terry Adam, und s9907681@student rmit edu au. „Investigations of light scattering by Australian natural waters for remote sensing applications“. RMIT University. Applied Sciences, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080110.140055.

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Remote sensing is the collection of information about an object from a distance without physically being in contact with it. The type of remote sensing of interest here is in the form of digital images of water bodies acquired by satellite. The advantage over traditional sampling techniques is that data can be gathered quickly over large ranges, and be available for immediate analysis. Remote sensing is a powerful technique for the monitoring of water bodies. To interpret the remotely sensed data, however, knowledge of the optical properties of the water constituents is needed. One of the most important of these is the volume scattering function, which describes the angular distribution of light scattered by a sample. This thesis presents the first measurements of volume scattering functions for Australian waters. Measurements were made on around 40 different samples taken from several locations in the Gippsland lakes and the Great Barrier Reef. The measurements were made by modifying an existing static light scattering spectrometer in order to accurately measure the volume scattering functions. The development of the apparatus, its calibration and automation, and the application of a complex series of post-acquisition data corrections, are all discussed. In order to extrapolate the data over the full angular range, the data was analysed using theoretical curves calculated for multi-modal size distributions using Mie light scattering theory applied to each data set. From the Mie fits the scattering and backscattering coefficients were calculated. These were compared with scattering coefficients measured using in situ sensors ac-9 and Hydroscat-6, and with values from the literature. The effect of chlorophyll a concentrations on the scattering coefficients was examined, and a brief investigation of the polarisation properties of the samples was also undertaken. Finally the angular effects on the relationship between the backscattering coefficient and the volume scattering function were investigated. This is important as in situ backscattering sensors often assume that measuring at a single fixed-angle is a good approximation for calculating the backscattering coefficient. This assumption is tested, and the optimal measurement angle determined.
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Marzahn, Philip. „Multi-dimensional characterization of soil surface roughness for microwave remote sensing applications“. Diss., lmu, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-154318.

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47

Donado, Morcillo Carlos Alberto. „Development of lightweight and low-cost microwave components for remote-sensing applications“. Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47532.

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The objective of the proposed research is to design, implement, and characterize low-cost, lightweight front-end components and subsystems in the microwave domain through innovative packaging architectures for remote sensing applications. Particular emphasis is placed on system-on-package (SoP) solutions implemented in organic substrates as a low-cost alternative to conventional, expensive, rigid, and fragile radio- frequency substrates. To this end, the dielectric properties of organic substrates RT/duroid 5880, 6002 and 6202 are presented from 30 GHz to 70 GHz, covering most of the Ka and V radar bands, giving also a thorough insight on the uncertainty of the microstrip ring resonator method by means of the Monte Carlo uncertainty analysis. Additionally, an ultra-thin, high-power antenna-array technology, with transmit/ receive (T/R) functionality is introduced for mobile applications in the X band. Two lightweight SoP T/R array panels are presented in this work using novel technologies such as Silicon Germanium integrated circuits and microelectromechanical system switches on a hybrid organic package of liquid crystal polymer and RT/duroid 5880LZ. A maximum power of 47 dBm is achieved in a package with a thickness of 1.8 mm without the need of bulky thermal management devices. Finally, to address the thermal limitations of thin-film substrates of interest (liquid crystal polymer, RT/duroid 6002, alumina and Aluminum Nitride), a thermal assessment of microstrip structures is presented in the X band, along with the thermal characterization of the dielectric properties of RT/duroid 6002 from 20 C to 200 C and from 30 GHz to 70 GHz. Additional high-power, X-band technologies presented in this work include: a novel and compact topology for evanescent mode filters, and low-profile Wilkinson power dividers implemented on Aluminum Nitride using Tantalum Nitride thin-film resistors.
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Hassan, Bukar. „Applications of remote sensing to arid grasslands : experimental and Nigerian case studies“. Thesis, Bangor University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.329703.

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Donado, Morcillo Carlos Alberto. „Development of lightweight and low-cost microwave components for remote-sensing applications“. Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/51733.

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The objective of the proposed research is to design, implement, and characterize low-cost, lightweight front-end components and subsystems in the microwave domain through innovative packaging architectures for remote sensing applications. Particular emphasis is placed on system-on-package (SoP) solutions implemented in organic substrates as a low-cost alternative to conventional, expensive, rigid, and fragile radio- frequency substrates. To this end, the dielectric properties of organic substrates RT/duroid 5880, 6002 and 6202 are presented from 30 GHz to 70 GHz, covering most of the Ka and V radar bands, giving also a thorough insight on the uncertainty of the microstrip ring resonator method by means of the Monte Carlo uncertainty analysis. Additionally, an ultra-thin, high-power antenna-array technology, with transmit/ receive (T/R) functionality is introduced for mobile applications in the X band. Two lightweight SoP T/R array panels are presented in this work using novel technologies such as Silicon Germanium integrated circuits and microelectromechanical system switches on a hybrid organic package of liquid crystal polymer and RT/duroid 5880LZ. A maximum power of 47 dBm is achieved in a package with a thickness of 1.8 mm without the need of bulky thermal management devices. Finally, to address the thermal limitations of thin-film substrates of interest (liquid crystal polymer, RT/duroid 6002, alumina and Aluminum Nitride), a thermal assessment of microstrip structures is presented in the X band, along with the thermal characterization of the dielectric properties of RT/duroid 6002 from 20 ºC to 200 ºC and from 30 GHz to 70 GHz. Additional high-power, X-band technologies presented in this work include: a novel and compact topology for evanescent mode filters, and low-profile Wilkinson power dividers implemented on Aluminum Nitride using Tantalum Nitride thin-film resistors.
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50

El, Vilaly Mohamed Abd salam Mohamdy. „Drought Monitoring with Remote Sensing Based Land Surface Phenology Applications and Validation“. Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/301553.

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Droughts are a recurrent part of our climate, and are still considered to be one of the most complex and least understood of all natural hazards in terms of their impact on the environment. In recent years drought has become more common and more severe across the world. For more than a decade, the US southwest has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources. The focus of this work is achieving a better understanding of the impact of drought on the lands of the Hopi Tribe and Navajo Nation, situated in the Northeastern corner of Arizona. This research explores the application of remote sensing data and geospatial tools in two studies to monitor drought impacts on vegetation productivity. In both studies we used land surface phenometrics as the data tool. In a third related study, I have compared satellite-derived land surface phenology (LSP) to field observations of crop stages at the Maricopa Agricultural Center to achieve a better understanding of the temporal sensitivity of satellite derived phenology of vegetation and understand their accuracy as a tool for monitoring change. The first study explores long-term vegetation productivity responses to drought. The paper develops a framework for drought monitoring and assessment by integrating land cover, climate, and topographical data with LSP. The objective of the framework is to detect long-term vegetation changes and trends in the Normalized Difference Vegetation Index (NDVI) related productivity. The second study examines the major driving forces of vegetation dynamics in order to provide valuable spatial information related to inter-annual variability in vegetation productivity for mitigating drought impacts. The third study tests the accuracy of remote sensing-derived LSP by comparing them to the actual seasonal phases of crop growth. This provides a way to compare and validate the various LSP algorithms, and more crucially, helps to characterize the remote sensing-based metrics that contrast with the actual biological phenophases of the crops. These studies demonstrate how remote sensing data and simple statistical tools can be used to assess drought effects on vegetation productivity and to inform about land conditions, as well as to better understand the accuracy of satellite derived LSP.
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