Investigation of a Space Delta Technology Facility (SDTF) for Spacelab

The Space Data Technology Facility (SDTF) would have the role of supporting a wide range of data technology related demonstrations which might be performed on Spacelab. The SDTF design is incorporated primarily in one single width standardized Spacelab rack. It consists of various display, control and data handling components together with interfaces with the demonstration-specific equipment and Spacelab. To arrive at this design a wide range of data related technologies and potential demonstrations were also investigated. One demonstration concerned with online image rectification and registration was developed in some depth

Neuromorphic perception for greenhouse technology using event-based sensors

Event-Based Cameras (EBCs), unlike conventional cameras, feature independent pixels that asynchronously generate outputs upon detecting changes in their field of view. Short calculations are performed on each event to mimic the brain. The output is a sparse sequence of events with high temporal precision. Conventional computer vision algorithms do not leverage these properties. Thus a new paradigm has been devised. While event cameras are very efficient in representing sparse sequences of events with high temporal precision, many approaches are challenged in applications where a large amount of spatially-temporally rich information must be processed in real-time. In reality, most tasks in everyday life take place in complex and uncontrollable environments, which require sophisticated models and intelligent reasoning. Typical hard problems in real-world scenes are detecting various non-uniform objects or navigation in an unknown and complex environment. In addition, colour perception is an essential fundamental property in distinguishing objects in natural scenes. Colour is a new aspect of event-based sensors, which work fundamentally differently from standard cameras, measuring per-pixel brightness changes per colour filter asynchronously rather than measuring “absolute” brightness at a constant rate. This thesis explores neuromorphic event-based processing methods for high-noise and cluttered environments with imbalanced classes. A fully event-driven processing pipeline was developed for agricultural applications to perform fruits detection and classification to unlock the outstanding properties of event cameras. The nature of features in such data was explored, and methods to represent and detect features were demonstrated. A framework for detecting and classifying features was developed and evaluated on the N-MNIST and Dynamic Vision Sensor (DVS) gesture datasets. The same network was evaluated on laboratory recorded and real-world data with various internal variations for fruits detection such as overlap, variation in size and appearance. In addition, a method to handle highly imbalanced data was developed. We examined the characteristics of spatio-temporal patterns for each colour filter to help expand our understanding of this novel data and explored their applications in classification tasks where colours were more relevant features than shapes and appearances. The results presented in this thesis demonstrate the potential and efficacy of event- based systems by demonstrating the applicability of colour event data and the viability of event-driven classification

Study of spacecraft direct readout meteorological systems

Characteristics are defined of the next generation direct readout meteorological satellite system with particular application to Tiros N. Both space and ground systems are included. The recommended space system is composed of four geosynchronous satellites and two low altitude satellites in sun-synchronous orbit. The goesynchronous satellites transmit to direct readout ground stations via a shared S-band link, relayed FOFAX satellite cloud cover pictures (visible and infrared) and weather charts (WEFAX). Basic sensor data is transmitted to regional Data Utilization Stations via the same S-band link. Basic sensor data consists of 0.5 n.m. sub-point resolution data in the 0.55 - 0.7 micron spectral region, and 4.0 n.m. resolution data in the 10.5 - 12.6 micron spectral region. The two low altitude satellites in sun-synchronous orbit provide data to direct readout ground stations via a 137 MHz link, a 400 Mhz link, and an S-band link

Advanced study of coastal zone oceanographic requirements for ERTS E and F

Earth Resources Technology Satellites E and F orbits and remote sensor instruments for coastal oceanographic data collectio

Teleoperator system man-machine interface requirements for satellite retrieval and satellite servicing. Volume 2: Design criteria

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Photogrammetric suite to manage the survey workflow in challenging environments and conditions

The present work is intended in providing new and innovative instruments to support the photogrammetric survey workflow during all its phases. A suite of tools has been conceived in order to manage the planning, the acquisition, the post-processing and the restitution steps, with particular attention to the rigorousness of the approach and to the final precision. The main focus of the research has been the implementation of the tool MAGO, standing for Adaptive Mesh for Orthophoto Generation. Its novelty consists in the possibility to automatically reconstruct \u201cunrolled\u201d orthophotos of adjacent fa\ue7ades of a building using the point cloud, instead of the mesh, as input source for the orthophoto reconstruction. The second tool has been conceived as a photogrammetric procedure based on Bundle Block Adjustment. The same issue is analysed from two mirrored perspectives: on the one hand, the use of moving cameras in a static scenario in order to manage real-time indoor navigation; on the other hand, the use of static cameras in a moving scenario in order to achieve the simultaneously reconstruction of the 3D model of the changing object. A third tool named U.Ph.O., standing for Unmanned Photogrammetric Office, has been integrated with a new module. The general aim is on the one hand to plan the photogrammetric survey considering the expected precision, computed on the basis of a network simulation, and on the other hand to check if the achieved survey has been collected compatibly with the planned conditions. The provided integration concerns the treatment of surfaces with a generic orientation further than the ones with a planimetric development. After a brief introduction, a general description about the photogrammetric principles is given in the first chapter of the dissertation; a chapter follows about the parallelism between Photogrammetry and Computer Vision and the contribution of this last in the development of the described tools. The third chapter specifically regards, indeed, the implemented software and tools, while the fourth contains the training test and the validation. Finally, conclusions and future perspectives are reported

Application of LANDSAT to the surveillance of lake eutrophication in the Great Lakes basin

The author has identified the following significant results. A step-by-step procedure for establishing and monitoring the trophic status of inland lakes with the use of LANDSAT data, surface sampling, laboratory analysis, and aerial observations were demonstrated. The biomass was related to chlorophyll-a concentrations, water clarity, and trophic state. A procedure was developed for using surface sampling, LANDSAT data, and linear regression equations to produce a color-coded image of large lakes showing the distribution and concentrations of water quality parameters, causing eutrophication as well as parameters which indicate its effects. Cover categories readily derived from LANDSAT were those for which loading rates were available and were known to have major effects on the quality and quantity of runoff and lake eutrophication. Urban, barren land, cropland, grassland, forest, wetlands, and water were included

Nonmechanical parfocal and autofocus features based on wave propagation distribution in lensfree holographic microscopy

Performing long-term cell observations is a non-trivial task for conventional optical microscopy, since it is usually not compatible with environments of an incubator and its temperature and humidity requirements. Lensless holographic microscopy, being entirely based on semiconductor chips without lenses and without any moving parts, has proven to be a very interesting alternative to conventional microscopy. Here, we report on the integration of a computational parfocal feature, which operates based on wave propagation distribution analysis, to perform a fast autofocusing process. This unique non-mechanical focusing approach was implemented to keep the imaged object staying in-focus during continuous long-term and real-time recordings. A light-emitting diode (LED) combined with pinhole setup was used to realize a point light source, leading to a resolution down to 2.76 μm. Our approach delivers not only in-focus sharp images of dynamic cells, but also three-dimensional (3D) information on their (x, y, z)-positions. System reliability tests were conducted inside a sealed incubator to monitor cultures of three different biological living cells (i.e., MIN6, neuroblastoma (SH-SY5Y), and Prorocentrum minimum). Altogether, this autofocusing framework enables new opportunities for highly integrated microscopic imaging and dynamic tracking of moving objects in harsh environments with large sample areas

Extracting scene feature vectors through modeling, volume 3

The remote estimation of the leaf area index of winter wheat at Finney County, Kansas was studied. The procedure developed consists of three activities: (1) field measurements; (2) model simulations; and (3) response classifications. The first activity is designed to identify model input parameters and develop a model evaluation data set. A stochastic plant canopy reflectance model is employed to simulate reflectance in the LANDSAT bands as a function of leaf area index for two phenological stages. An atmospheric model is used to translate these surface reflectances into simulated satellite radiance. A divergence classifier determines the relative similarity between model derived spectral responses and those of areas with unknown leaf area index. The unknown areas are assigned the index associated with the closest model response. This research demonstrated that the SRVC canopy reflectance model is appropriate for wheat scenes and that broad categories of leaf area index can be inferred from the procedure developed

Advanced scanners and imaging systems for earth observations

Assessments of present and future sensors and sensor related technology are reported along with a description of user needs and applications. Five areas are outlined: (1) electromechanical scanners, (2) self-scanned solid state sensors, (3) electron beam imagers, (4) sensor related technology, and (5) user applications. Recommendations, charts, system designs, technical approaches, and bibliographies are included for each area