Cotton crop condition was assessed from an analysis of multispectral aerial video imagery. Visible-near infrared imagery of two cotton fields was collected towards the end of the 1990 crop. The digital analysis was based on image classification, and the accuracies were assessed using the Kappa coefficient of agreement. The earliest of three images proved to be best for distinguishing plant variety. Vegetation index images were better for estimating potential yield than the original multispectral image; so too were multi-channel images that were transformed using vegetation indices or principal component analysis. The seedbed preparation rig used, the nitrogen application rate and three plant varieties, a weed species and two cotton cultivars, could all be discriminated from the imagery. Accuracies were moderate for the discrimination of plant variety, tillage treatment and nitrogen treatment, and low for the estimation of potential yield.

Water is a major factor limiting cotton production and farmers must aim to optimise crop water use through timely irrigation scheduling decisions. Airborne video imagery when calibrated with a low density of ground based observations, offers the potential for near real time monitoring of crop condition, through sequential coverages of entire cotton fields. Using commercially available video equipment mounted on a light aircraft images were acquired of field experiments that were established in commercial cotton fields to test if the imagery could monitor changes in crop condition. Ground data collected from these experiments were used to evaluate green, red, near infrared and thermal band imagery for irrigated crop management. Prior to acquiring imagery, a ground radiometer study was conducted to investigate if canopy reflectance changed with the onset of crop water stress. Canopy reflectance decreased in the near infrared and green bands during the five day period prior to the crop's normal irrigation date. Red reflectance increased only after the crop irrigation was due, when the crop was suffering from water stress. The greatest change in canopy reflectance was in the near infrared region, attributable in part to a decrease in ground cover caused by canopy architectural changes including leaf wilting. The results of this experiment were used to select spectral filters for the video cameras. A range of crop conditions were identified in the imagery including; crop waterlogging, wheeltrack soil compaction, crop nitrogen status, different varieties, crop maturity, canopy development, soil moisture status, cotton yield and nutgrass weeds. Thermal imagery was the most successful for distinguishing differences in the crop soil moisture status. Near infrared imagery was most closely related to crop canopy development and is recommended for monitoring crop growth. Linear relationships were found between spectral responses in the imagery, crop reflectance (%) and crop temperature measured on the ground. Near infrared reflectance linearly increased, while spectral responses in the green, red and thermal bands exhibited an inverse relationship with plant height and ground cover. Imagery collected early in the season was affected by the soil background. Final lint yield was related to imagery in the red band. As the soil moisture level declined, crop temperature increased while reflectance in the green band decreased. To ensure an accurate relationship between soil moisture and thermal imagery, separate calibration equations are recommended for different stages in the season. Green, red and near infrared imagery were affected by the sun angle that caused one side of the imagery to appear brighter than the other. This problem was greatest in the green and red bands, but was not evident in the thermal imagery. Changes in solar radiation and air temperature on some occasions caused greater variation to the imagery between flights, than changes in crop condition per se. Therefore, it is not aIways possible to directly determine the soil moisture status from canopy temperature. Further research is required to correct imagery for environmental variables such as solar radiation, air temperature and vapour pressure deficit. Thermal imagery offers many improvements to current irrigation scheduling techniques including the facilitation of locating more representative ground sampling points. Thermal imagery also enables cotton fields on a farm to be ranked according to their soil moisture status. This then provides farmers with a visual picture of the crop water status across the whole farm, which is not possible using conventional ground scheduling techniques. At this stage, airborne video imagery will not replace soil moisture data collected for irrigation scheduling, however offers potential to enhance irrigation scheduling methods by addressing the problem of crop variability within cotton fields.

This research assesses the design and track operation of a track crawler robot (TCR) for practical and easy inspection of stationary railcars' undercarriages in an effort to detect any pending failures or assess any security risk of out-of-sight objects. The research leverages against a robot available at the Railway Technologies Laboratory (RTL) of Virginia Tech and offers improvements to the structure, drive system, imaging devices, and operator remote control to improve the speed, track maneuverability, and duty cycle of the robot. The TCR includes a drive system consisting of two AC motors that operate a track (like tank tracks). It further includes two GoPro® cameras, light system, and onboard power for approximately one hour of maximum power operation. The details of the TCR design are introduced through its operational requirements, which guided its initial design. The specific design configurations are used to derive the applicable parameters essential for track operation of the robot. The TCR's subsystems are evaluated individually to assess their strengths and weaknesses, which are then used to guide the specific tasks in improving the overall system's performance. The details of the required modifications are included for the imaging, lighting, control, frame structure, and mobility subsystems. For each subsystem, test results are used to engineer workable solutions for overcoming the shortcomings or implementing additional functionality. The redesigned system is further evaluated through testing to assess the improvements due to modifications. Beyond laboratory tests, a final assessment of the system was done on a branch line and mainline track, both with great success. The recorded images and operational evaluation of the TCR prove it to be a valuable inspection tool for the railroads to inspect out-of-sight undercarriage components of stationary trains in a railyard or siding, to identify any failed or nearly-failed equipment before they develop into a major or out-of-compliance issue. The TCR also promises to be useful for security agencies to easily and efficiently inspect trains entering secured areas to uncover any suspicious devices. / Master of Science / This study aims to develop a Track Crawler Robot (TCR) that can assist train operators and security agencies to inspect the undercarriage of trains efficiently and effectively, to detect any pending failure, or to uncover suspicious devices that are not visible train-side. Every day in railyards across the U.S., trains are assembled out of railcars loaded with cargo. The Federal Railroad Administration (FRA) stipulates that each train must be visually inspected before they are allowed to depart to their destination. The undercarriage is difficult, time-consuming, and hazardous to inspect, requiring the inspector to stoop down and partially climb beneath the train. Additionally, the extended length of the trains—some, as long as two miles—and the many components that are part of each railcar makes the inspection an arduous task, and at times leads to missed failures particularly for out-of-site components underneath the carriage. Highly advanced track-mounted vision systems are offered as the means for inspecting trains while in revenue-service operation. Although effective, such systems are expensive and can only inspect the trains passing by their location. Not all trains would pass by the inspection site, and it is possible for a train to pass the site and develop a failure afterward that goes undetected until the next inspection. This research develops a cost-effective, mobile platform, called TCR, that can aid in the undercarriage inspection of stationary railcars. The TCR includes a drive system consisting of two AC motors that operate a track (like tank tracks). It further includes two GoPro® cameras, light system, and onboard power for approximately one hour of maximum power operation. The system gives the inspector a bird's eye view of the undercarriage without the need for a person to crawl in between the tracks. Many tests are conducted to assess the operation of the TCR and make improvements to it to make its captured images clearer and increase its agility and maneuverability. The tests prove to be remarkably successfully, and they confirm TCR's utility for the FRA-mandated train inspections required from the railroads and security inspections desired by the law enforcement and military.

As part of a beach erosion field experiment conducted at Cape Hatteras, NC in February 2010, this study focuses on quantifying longshore currents, which are the basic mechanism that drives longshore sediment transport. Using video imagery, the longshore currents in view of a video camera are estimated with the Optical Current Meter technique and the nearshore morphology is estimated by analyzing breaking wave patterns in standard deviation images. During a Nor‟easter storm event on February 12 and 13, 2010, the video longshore currents are compared to in situ data and it is found that the currents are most affected by the angle of incidence of incoming waves, increasing in magnitude as the angle becomes more oblique due to a larger component of radiation stress forcing in the longshore direction. The magnitude of the radiation stress forcing, which is at least an order of magnitude larger than the surface wind stress, increases as wave height increases or tide level decreases, which causes more wave breaking to occur. The normalized standard deviation images show wave breaking occurring at an inshore and offshore location, corresponding closely to the locations of an inner and outer bar indicated in survey data. Using two profiles from the survey data, one profile that intersects a trough and one that intersects a terrace, the video currents are also compared to currents simulated in one-dimension using the circulation module, SHORECIRC, and the wave module, REF/DIF-S, as part of the NearCoM system. Although the simulated currents greatly underpredict the video currents when the flow is only driven by radiation stresses, a mean water level difference between the two profiles creates a longshore pressure gradient. Superimposing a pressure gradient forcing term into the longshore momentum balance that assumes an equilibrium state of the flow, the magnitude of the simulated currents are much larger than the magnitude of the video estimated currents. Using analytical solutions of simplified forms of the mass and momentum equations to determine the effects of accelerations on the flow, it is seen that the acceleration term greatly affects the flow due to the relatively large mean water level difference that acts over a relatively short distance. Therefore, the pressure gradient forcing term is modified to include the effects of accelerations. By including the two-dimensional effects of the acceleration in the one-dimensional model through the modified pressure gradient, the quasi two-dimensional model simulated currents are very similar to the video estimated currents, indicating that the currents observed in the video may be pressure gradient driven.

No description available.

Ces dernières années, de nouvelles stratégies ciblant un accompagnement de la mobilité du trait de côte plutôt que sa fixation ont vu le jour. Parmi celles-ci, les ouvrages atténuateur de houle visent à protéger la côte en dissipant l’énergie des vagues par déferlement bathymétrique, tout en restant invisibles depuis la plage. Leur utilisation a toutefois eu des effets contrastés et les processus hydro-sédimentaires induits par ces structures restent mal connus. L’objectif général de ce travail est de mieux comprendre les effets de ces atténuateurs de houle sur la morphodynamique littorale, notamment sur des sites où l’évolution de l’avant-côte est complexe et dynamique. L’observation des effets induits par un atténuateur de houle installé au lido de Sète (Golfe du Lion), sur la dynamique littorale est réalisée via un dispositif vidéo qui permet de caractériser l’évolution morphologique du système. En s’appuyant sur une méthode automatique de correction des images développée dans le cadre de cette thèse, l’estimation de la bathymétrie par inversion de la célérité des vagues et ses erreurs associées sont évaluées pour la première fois en Méditerranée. Les observations montrent que l’atténuateur de houle impacte de manière importante la morphologie et la dynamique des barres sableuses pré-littorales et révèlent que l’élargissement de la plage résulte principalement de son couplage avec la nouvelle forme de barre plus linéaire. Le modèle morphodynamique 2DBeach est ensuite implémenté sur Sète et sur un second site atelier en Australie où un récif artificiel de taille et de forme différente a été mis en place. Les simulations réalisées permettent de déterminer les circulations induites par ces ouvrages ainsi que les évolutions sédimentaires associées. Enfin, ce travail met en lumière les différents processus physiques contrôlant l’influence d’un atténuateur de houle sur les évolutions morphologiques des barres sableuses pré-littorales et du trait de côte, et renforce des connaissances essentielles à la gestion durable des plages sableuses. / In recent years, traditional coastal defense strategy has become increasingly unpopular as it is costly and lastingly scars the landscape with sometimes limited effectiveness or even adverse impact. Mimicking natural reefs, submerged breakwaters aims to protect the coast, decreasing wave energy through wave breaking offshore with the advantage of remaining invisible from the beach. The general objective of this work is to better understand the different morphodynamic processes that interact in the presence of these structures, especially for complex beach morphology with highly dynamic sandbars. The observation of the effects induced by a submerged breakwater deployed at the Lido of Sète (Gulf of Lions) on the morphological response is performed using a video monitoring system. Based on an automatic method for image correction developed in this thesis, a video-derived depth inversion algorithm was tested to infer nearshore bathymetry from remotely-sensed wave parameters. Our observations show that the submerged breakwater had a profound impact on the shoreline-sandbar system and suggest that, on barred beaches, the role of the sandbar is critical to shoreline response to the implementation of such a structure. The expected salient formation was not observed and, instead, shoreline coupled to the modified sandbar geometry, which resulted in a slight seaward migration of the shoreline in the lee of the structure. In order to characterize the nearshore circulation induced by these structures and to better assess sediment transport, the morphodynamic model 2DBeach was then implemented on Sète and at another beach in Australia where an artificial reef of different size and shape has been deployed. This work allows a better understanding of the influence of a submerged breakwater on the morphological evolution of sandbars and shoreline on time scales from storm to years, and provides new insight into nearshore system response to better design sustainable management of sandy beaches.

Video based remote sensing techniques are well suited to collect spatially resolved wave images in the surf zone with breaking waves and dynamic bathymetric changes. An advanced video-based depth inversion method is developed to remotely survey bathymetry in the surf zone. The present method involves image processing of original wave image sequences, wave property estimation based on linear feature extraction from the processed image sequences, and is combined with a nonlinear depth inversion model. The original wave image sequences are processed through video image frame differencing and directional low-pass filtering schemes to remove wave-breaking-induced foam noise having high frequencies in the surf zone. The features of individual crest trajectories are extracted from the processed and rectified image sequences, i.e. processed image cross-shore timestacks, by tracking pixels of high intensity within an interrogation window of a Radon-transform-based line-detection algorithm. The wave celerity is computed using space-time information of the extracted trajectories of individual wave crests in the cross-shore timestack domain. The presented retrieval of nearshore bathymetry from video image sequences is based on a nonlinear depth inversion using the nonlinear shallow water wave theory. The nonlinear wave amplitude dispersion effects at the breaker points are determined by combining the nonlinear shallow water celerity equation with a wave breaker criterion, thereby computing water depths iteratively from the celerity measured from the video data. The water depths estimated at the breaker points present initial bathymetric anchor points. Bathymetric profiles in the surf zone are inverted by calculating wave heights dissipated after wave breaking with a wave dissipation model and wave heights shoaled before wave breaking with a wave shoaling model. The continuous wave amplitude dispersion effects are subtracted from the measured celerity profiles, resulting in nearshore bathymetric profiles. The nonlinear depth inversion derived bathymetric estimates from nearshore imagery match the measured values with a biased mean depth error of about +0.06m in the depth range of 0.1 to 3m. In addition, the wave height estimates by the depth inversion model are comparable to the in-situ measured wave heights with a biased mean wave height error of about +0.14m. The present depth inversion method based on optical remote-sensing supports coastal management, navigation, and amphibious operations.

Cette thèse présente une plateforme d'assimilation de données issues de l'imagerie vidéo et intégrée au modèle numérique d'évolution de profil de plage 1DBEACH. Le manque de jeux de données bathymétriques haute-fréquence est un des problèmes récurrents pour la modélisation morphodynamique littorale. Pourtant, des relevés topographiques réguliers sont nécessaires non seulement pour la validation de nos modèles hydro-sédimentaires mais aussi dans une perspective de prévision d'évolution morphologique de nos plages sableuses et d'évolution de la dynamique des courants de baïnes en temps réel. Les récents progrès dans le domaine de l'imagerie vidéo littorale ont permis d'envisager un moyen de suivi morphologique quasi-quotidien et bien moins coûteux que les traditionnelles campagnes de mesure. En effet, les images dérivées de la vidéo de type timex ou timestack rendent possible l'extraction de proxys bathymétriques qui permettent de caractériser et de reconstruire la morphologie de plage sous-jacente. Cependant, ces méthodes d'inversion bathymétrique directes sont limitées au cas linéaire et nécessitent, selon les conditions hydrodynamiques ambiantes, l'acquisition de données vidéo sur plusieurs heures voire plusieurs jours pour caractériser un état de plage. En réponse à ces différents points bloquants, ces travaux de thèse proposaient l'implémentation puis la validation de méthodes d'inversion bathymétrique basées sur l'assimilation dans notre modèle de différentes sources d'observations vidéo disponibles et complémentaires. A partir d'informations hétérogènes et non redondantes, ces méthodes permettent la reconstruction rapide et précise d'une morphologie de plage dans son intégralité pour ainsi bénéficier de relevés bathymétriques haute fréquence réguliers. / This thesis presents data-model assimilation techniques using video-derived beach information to improve the modelling of beach profile evolution.The acquisition of accurate and recurrent nearshore bathymetric data is a difficult and challenging task which limits our understanding of nearshore morphological changes. This is particularly true in the surf zone which exhibits the largest degree of morphological variability. In addition, surfzone bathymetric data are crucial from many perspectives such as numerical model validation, operational rip current prediction or real-time nearshore evolution modelling. In parallel, video imagery recently arose as a low-cost alternative to direct measurement in order to daily monitor beach morphological changes. Indeed, bathymetry proxies can be extracted from video-derived images such as timex or timestacks. These data can be then used to estimate underlying beach morphologies. However, simple linear depth inversion techniques still suffer from some restrictions and require up to a 3-day dataset to completely characterize a given beach morphology. As an alternative, this thesis presents and validates data-assimilation methods that combine multiple sources of available video-derived bathymetry proxies to provide a rapid, complete and accurate estimation of the underlying bathymetry and prevent from excessive information.