Analysis of Thematic Classified Aerial Images Trough Multispectral and LIDAR Data

The application of thematic maps obtained through the classification of remote images needs the obtained products with an optimal accuracy. The registered images from the airplanes display a very satisfactory spatial resolution, but the classical methods of thematic classification not always give better results than when the registered data from satellite are used. In order to improve these results of classification, in this work, the LIDAR sensor data from first return (Light Detection And Ranging) registered simultaneously with the spectral sensor data from airborne are jointly used. The final results of the thematic classification of the scene object of study have been obtained, quantified and discussed with and without LIDAR data, after applying different methods: Maximum Likehood Classification, Support Vector Machine with four different functions kernel and Isodata clustering algorithm (ML, SVM-L, SVM-P, SVM-RBF, SVM-S, Isodata). The best results are obtained for SVM with Sigmoide kernel. These allow the correlation with others different physical parameters with great interest like Manning hydraulic coefficient, for their incorporation in a GIS and their application in hydraulic modeling.

Aerial video geo-registration using terrain models from dense and coherent stereo matching

In the context of aerial imagery, one of the first steps toward a coherent processing of the information contained in multiple images is geo-registration, which consists in assigning geographic 3D coordinates to the pixels of the image. This enables accurate alignment and geo-positioning of multiple images, detection of moving objects and fusion of data acquired from multiple sensors. To solve this problem there are different approaches that require, in addition to a precise characterization of the camera sensor, high resolution referenced images or terrain elevation models, which are usually not publicly available or out of date. Building upon the idea of developing technology that does not need a reference terrain elevation model, we propose a geo-registration technique that applies variational methods to obtain a dense and coherent surface elevation model that is used to replace the reference model. The surface elevation model is built by interpolation of scattered 3D points, which are obtained in a two-step process following a classical stereo pipeline: first, coherent disparity maps between image pairs of a video sequence are estimated and then image point correspondences are back-projected. The proposed variational method enforces continuity of the disparity map not only along epipolar lines (as done by previous geo-registration techniques) but also across them, in the full 2D image domain. In the experiments, aerial images from synthetic video sequences have been used to validate the proposed technique.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

La evolución del paisaje fluvial en la confluencia de los ríos Tajo y Jarama

La tesis doctoral que se presenta realiza un análisis de la evolución del paisaje fluvial de las riberas de los ríos Tajo y Jarama en el entorno de Aranjuez desde una perspectiva múltiple. Contempla y conjuga aspectos naturales, tales como los hidrológicos, geomorfológicos y ecológicos; también culturales, como la regulación hidrológica y la gestión del agua, las intervenciones en cauce y márgenes, la evolución de la propiedad y los cambios de usos del suelo, fundamentalmente. Este análisis ha permitido identificar el sistema de factores, dinámico y complejo, que ha creado este paisaje, así como las interrelaciones, conexiones, condicionantes y dependencias de los descriptores paisajísticos considerados. Por ejemplo, se han estudiado las relaciones cruzadas observadas entre dinámica fluvial-propiedad de la tierra-estado de conservación, cuestiones que hasta la fecha no habían sido tratadas, evaluadas o cuantificadas en otros trabajos dedicados a esta zona. La investigación se ha organizado en tres fases fundamentales que han dado lugar a los capítulos centrales del documento (capítulos 2, 3 y 4). En primer lugar, se ha realizado una caracterización de los factores, naturales y culturales, que organizan el paisaje de este territorio eminentemente fluvial (geomorfología, factores climáticos e hidrológicos, vegetación, propiedad de la tierra y elementos culturales de significación paisajística). A continuación, se ha realizado el estudio de la evolución del paisaje fluvial mediante el análisis de diversos elementos, previamente identificados y caracterizados. Para ello se han procesado imágenes aéreas correspondientes a cinco series temporales así como varios planos antiguos, obteniendo una amplia base de datos que se ha analizado estadísticamente. Finalmente, se han contrastado los resultados parciales obtenidos en los capítulos anteriores, lo que ha permitido identificar relaciones causales entre los factores que organizan el paisaje y la evolución de los elementos que lo constituyen. También, interconexiones entre factores o entre elementos. Este método de trabajo ha resultado muy útil para la comprensión del funcionamiento y evolución de un sistema complejo, como el paisaje de la vega de Aranjuez, un territorio con profundas y antiguas intervenciones culturales donde lo natural, en cualquier caso, siempre subyace. Es posible que la principal aportación de este trabajo, también su diferencia más destacada respecto a otros estudios de paisaje, haya sido mostrar una visión completa y exhaustiva de todos los factores que han intervenido en la conformación y evolución del paisaje fluvial, destacando las relaciones que se establecen entre ellos. Esta manera de proceder puede tener una interesante faceta aplicada, de tal manera que resulta un instrumento muy útil para el diseño de planes de gestión de este territorio fluvial. No en vano, una parte sustancial de la vega del Tajo-Jarama en Aranjuez es un Lugar de Importancia Comunitaria (LIC) y su posterior e ineludible declaración como Zona de Especial Conservación (ZEC) de la Red Natura 2000, de acuerdo con lo establecido en la Directiva 92/43/CE, exige la elaboración de un Plan de Gestión que, en gran medida, podría nutrirse de lo presentado, analizado e interpretado en este trabajo. En este sentido, conviene señalar la conciencia ya asumida de considerar, por su carácter integrador de la realidad territorial, el paisaje como elemento clave para la gestión adecuada de la naturaleza y el territorio. Por otra parte, se considera que los resultados de esta Tesis Doctoral permitirían plantear medidas para la puesta en valor de un paisaje sobresaliente, cuyos límites sobrepasan con creces los que en la actualidad conforman el Paisaje Cultural declarado por la UNESCO. En suma, el análisis de este espacio fluvial realizado con la profundidad y amplitud que permite el método de trabajo seguido puede utilizarse para el diseño de estrategias que dirijan la evolución de este territorio en una línea que garantice su conservación global en términos paisajísticos, patrimoniales y ecológicos, permitiendo además, de este modo, su uso equilibrado como recurso económico, cultural o educativo. This doctoral thesis shows an analysis of fluvial landscape evolution from multiple perspectives on the banks of Tagus and Jarama rivers, around Aranjuez. The thesis contemplates and combines natural features, such as hydrological, geomorphological and ecological features, as well as cultural features, like hydrological regulation and water management, interventions in channels and margins, changes in ownership and land use changes, mainly. This analysis has allowed to identify the factors system, dynamic and complex, that this landscape has created, as well as the interrelationships, connections, constraints and dependencies among considered landscape descriptors. For example, we have studied the relationships observed among fluvial dynamics- land ownership -conservation status, issues not addressed, assessed or quantified up to now in other works about this area. The research is organized into three major phases that led to the paper's central chapters (Chapters 2, 3 and 4). First, there has been a characterization of the factors, both natural and cultural, that organize the landscape of this predominantly fluvial area (geomorphology, climate and hydrological factors, vegetation, land and cultural elements of landscape significance). Then, it was made to study of fluvial landscape evolution by analyzing various elements previously identified and characterized. Aerial images were processed for five series and several old maps, obtaining an extensive database, that has been analyzed statistically. Finally, we have contrasted the partial results obtained in the previous chapters, making it possible to identify causal relationships between the factors that organize the landscape and the evolution of the elements that constitute it. This working method has been very useful for understanding the operation and evolution of a complex system, as the landscape of the Vega de Aranjuez, a territory with deep and ancient cultural interventions where anyway, nature feature always lies. It is possible that the main contribution of this work, also its most prominent difference compared with other studies of landscape, has been to show a complete and exhaustive view of all factors involved in the formation and evolution of the fluvial landscape, highlighting the relationships established among them. This approach could have an interesting applied facet, so that is a very useful tool for designing management plans on this river territory. Not surprisingly, a substantial part of the valley of the Tagus-Jarama in Aranjuez is a Site of Community Importance (SCI) and their subsequent and inevitable declaration as Special Area of Conservation (SAC) of the Natura 2000 network, in accordance with the provisions Directive 92/43/EC, requires the development of a management plan that largely could draw on what was presented, analyzed and interpreted in this paper. In this regard, it should be noted conscience and assumed to consider, on the inclusiveness of territorial reality, the landscape as a key element for the proper management of nature and territory. On the other hand, it is considered that the results of this thesis allow to propose measures for enhancement of outstanding scenery, which go well beyond the boundaries that currently the Cultural Landscape declared by UNESCO. In sum, the analysis of this river area made with the depth and breadth that enables working method can be used to design strategies that address the evolution of this territory in a line that guarantees global conservation landscape terms, heritage and ecological, also, allowing its use as a balancing economic, cultural or educational resource.

Metodología del análisis de imágenes digitales para el estudio del contenido de humedad en vertisoles

Desde finales del siglo pasado, el procesamiento y análisis de imágenes digitales, se ha convertido en una poderosa herramienta para la investigación de las propiedades del suelo a múltiples resoluciones, sin embargo todavía no existen los mejores resultados en cuanto a estos trabajos. El principal problema para investigar el drenaje vertical a partir de la distribución de humedad en un perfil de vertisol es la búsqueda de métodos factibles que usen este procedimiento. El objetivo general es implementar una metodología para el procesamiento y análisis de imágenes digitales, que permita caracterizar la distribución del contenido de humedad de un perfil de vertisol. Para el estudio, doce calicatas fueron excavadas en un Mazic Pellic Vertisol, seis de ellas en mayo 13/2011 y el resto en mayo 19/2011 después de moderados eventos de lluvia. Las imágenes RGB de los perfiles fueron tomadas con una cámara Kodak™; con tamaños seleccionados de 1600 x 945 píxeles cada una fue procesada para homogeneizar el brillo y se aplicaron filtros suavizadores de diferentes tamaños de ventana, hasta obtener el óptimo. Cada imagen se dividió en sus matrices componentes, seleccionando los umbrales de cada una para ser aplicado y obtener el patrón digital binario. Este último fue analizado a través de la estimación de dos exponentes fractales: dimensión de conteo de cajas (DBC) y dimensión fractal de interfase húmedo seco (Di). Además, fueron determinados tres coeficientes prefractales a la máxima resolución: número total de cajas interceptados en el plano del patrón (A), la lagunaridad fractal (λ1) y la entropía de Shannon (S1). Para todas las imágenes obtenidas, basado en la entropía, los análisis de clúster y de histogramas, el filtro espacial de 9x9 resultó ser el de tamaño de ventana óptimo. Los umbrales fueron seleccionados a partir del carácter bimodal de los histogramas. Los patrones binarios obtenidos mostraron áreas húmedas (blancas) y secas (negras) que permitieron su análisis. Todos los parámetros obtenidos mostraron diferencias significativas entre ambos conjuntos de patrones espaciales. Mientras los exponentes fractales aportan información sobre las características de llenado del patrón de humedad, los coeficientes prefractales representan propiedades del suelo investigado. La lagunaridad fractal fue el mejor discriminador entre los patrones de humedad aparente del suelo. ABSTRACT From last century, digital image processing and analysis was converted in a powerful tool to investigate soil properties at multiple resolutions, however, the best final procedure in these works not yet exist. The main problem to study vertical drainage from the moisture distribution, on a vertisol profile, is searching for suitable methods using these procedures. Our aim was to design a digital image processing methodology and its analysis to characterize the moisture content distribution of a vertisol profile. In this research, twelve soil pits were excavated on a bare Mazic Pellic Vertisol, six of them in May 13/2011 and the rest in May 19/2011 after a moderate rainfall event. Digital RGB images were taken from each vertisol pit using a Kodak™ camera selecting a size of 1600x945 pixels. Each soil image was processed to homogenized brightness and then a spatial filter with several window sizes was applied to select the optimum one. The RGB image obtained were divided in each matrix color selecting the best thresholds for each one, maximum and minimum, to be applied and get a digital binary pattern. This one was analyzed by estimating two fractal scaling exponents: box counting dimension (DBC

Land Cover Mapping by an Optimized Object-Oriented Approach. Case of Study Mediterranean Landscapes

Remote sensing information from spaceborne and airborne platforms continues to provide valuable data for different environmental monitoring applications. In this sense, high spatial resolution im-agery is an important source of information for land cover mapping. For the processing of high spa-tial resolution images, the object-based methodology is one of the most commonly used strategies. However, conventional pixel-based methods, which only use spectral information for land cover classification, are inadequate for classifying this type of images. This research presents a method-ology to characterise Mediterranean land covers in high resolution aerial images by means of an object-oriented approach. It uses a self-calibrating multi-band region growing approach optimised by pre-processing the image with a bilateral filtering. The obtained results show promise in terms of both segmentation quality and computational efficiency.

Methodology of image analysis for study of the vertisols moisture content

The main problem to study vertical drainage from the moisture distribution, on a vertisol profile, is searching for suitable methods using these procedures. Our aim was to design a digital image processing methodology and its analysis to characterize the moisture content distribution of a vertisol profile. In this research, twelve soil pits were excavated on a ba re Mazic Pellic Vertisols ix of them in May 13/2011 and the rest in May 19 /2011 after a moderate rainfall event. Digital RGB images were taken from each vertisol pit using a Kodak? camera selecting a size of 1600x945 pixels. Each soil image was processed to homogenized brightness and then a spatial filter with several window sizes was applied to select the optimum one. The RGB image obtained were divided in each matrix color selecting the best thresholds for each one, maximum and minimum, to be applied and get a digital binary pattern. This one was analyzed by estimating two fractal scaling exponents box counting dimension D BC) and interface fractal dimension (D) In addition, three pre-fractal scaling coefficients were determinate at maximum resolution: total number of boxes intercepting the foreground pattern (A), fractal lacunarity (?1) and Shannon entropy S1). For all the images processed the spatial filter 9x9 was the optimum based on entropy, cluster and histogram criteria. Thresholds for each color were selected based on bimodal histograms.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

Computational methods to create and analyze a digital gene expression atlas of embryo development from microscopy images

Abstract The creation of atlases, or digital models where information from different subjects can be combined, is a field of increasing interest in biomedical imaging. When a single image does not contain enough information to appropriately describe the organism under study, it is then necessary to acquire images of several individuals, each of them containing complementary data with respect to the rest of the components in the cohort. This approach allows creating digital prototypes, ranging from anatomical atlases of human patients and organs, obtained for instance from Magnetic Resonance Imaging, to gene expression cartographies of embryo development, typically achieved from Light Microscopy. Within such context, in this PhD Thesis we propose, develop and validate new dedicated image processing methodologies that, based on image registration techniques, bring information from multiple individuals into alignment within a single digital atlas model. We also elaborate a dedicated software visualization platform to explore the resulting wealth of multi-dimensional data and novel analysis algo-rithms to automatically mine the generated resource in search of bio¬logical insights. In particular, this work focuses on gene expression data from developing zebrafish embryos imaged at the cellular resolution level with Two-Photon Laser Scanning Microscopy. Disposing of quantitative measurements relating multiple gene expressions to cell position and their evolution in time is a fundamental prerequisite to understand embryogenesis multi-scale processes. However, the number of gene expressions that can be simultaneously stained in one acquisition is limited due to optical and labeling constraints. These limitations motivate the implementation of atlasing strategies that can recreate a virtual gene expression multiplex. The developed computational tools have been tested in two different scenarios. The first one is the early zebrafish embryogenesis where the resulting atlas constitutes a link between the phenotype and the genotype at the cellular level. The second one is the late zebrafish brain where the resulting atlas allows studies relating gene expression to brain regionalization and neurogenesis. The proposed computational frameworks have been adapted to the requirements of both scenarios, such as the integration of partial views of the embryo into a whole embryo model with cellular resolution or the registration of anatom¬ical traits with deformable transformation models non-dependent on any specific labeling. The software implementation of the atlas generation tool (Match-IT) and the visualization platform (Atlas-IT) together with the gene expression atlas resources developed in this Thesis are to be made freely available to the scientific community. Lastly, a novel proof-of-concept experiment integrates for the first time 3D gene expression atlas resources with cell lineages extracted from live embryos, opening up the door to correlate genetic and cellular spatio-temporal dynamics. La creación de atlas, o modelos digitales, donde la información de distintos sujetos puede ser combinada, es un campo de creciente interés en imagen biomédica. Cuando una sola imagen no contiene suficientes datos como para describir apropiadamente el organismo objeto de estudio, se hace necesario adquirir imágenes de varios individuos, cada una de las cuales contiene información complementaria respecto al resto de componentes del grupo. De este modo, es posible crear prototipos digitales, que pueden ir desde atlas anatómicos de órganos y pacientes humanos, adquiridos por ejemplo mediante Resonancia Magnética, hasta cartografías de la expresión genética del desarrollo de embrionario, típicamente adquiridas mediante Microscopía Optica. Dentro de este contexto, en esta Tesis Doctoral se introducen, desarrollan y validan nuevos métodos de procesado de imagen que, basándose en técnicas de registro de imagen, son capaces de alinear imágenes y datos provenientes de múltiples individuos en un solo atlas digital. Además, se ha elaborado una plataforma de visualization específicamente diseñada para explorar la gran cantidad de datos, caracterizados por su multi-dimensionalidad, que resulta de estos métodos. Asimismo, se han propuesto novedosos algoritmos de análisis y minería de datos que permiten inspeccionar automáticamente los atlas generados en busca de conclusiones biológicas significativas. En particular, este trabajo se centra en datos de expresión genética del desarrollo embrionario del pez cebra, adquiridos mediante Microscopía dos fotones con resolución celular. Disponer de medidas cuantitativas que relacionen estas expresiones genéticas con las posiciones celulares y su evolución en el tiempo es un prerrequisito fundamental para comprender los procesos multi-escala característicos de la morfogénesis. Sin embargo, el número de expresiones genéticos que pueden ser simultáneamente etiquetados en una sola adquisición es reducido debido a limitaciones tanto ópticas como del etiquetado. Estas limitaciones requieren la implementación de estrategias de creación de atlas que puedan recrear un multiplexado virtual de expresiones genéticas. Las herramientas computacionales desarrolladas han sido validadas en dos escenarios distintos. El primer escenario es el desarrollo embrionario temprano del pez cebra, donde el atlas resultante permite constituir un vínculo, a nivel celular, entre el fenotipo y el genotipo de este organismo modelo. El segundo escenario corresponde a estadios tardíos del desarrollo del cerebro del pez cebra, donde el atlas resultante permite relacionar expresiones genéticas con la regionalización del cerebro y la formación de neuronas. La plataforma computacional desarrollada ha sido adaptada a los requisitos y retos planteados en ambos escenarios, como la integración, a resolución celular, de vistas parciales dentro de un modelo consistente en un embrión completo, o el alineamiento entre estructuras de referencia anatómica equivalentes, logrado mediante el uso de modelos de transformación deformables que no requieren ningún marcador específico. Está previsto poner a disposición de la comunidad científica tanto la herramienta de generación de atlas (Match-IT), como su plataforma de visualización (Atlas-IT), así como las bases de datos de expresión genética creadas a partir de estas herramientas. Por último, dentro de la presente Tesis Doctoral, se ha incluido una prueba conceptual innovadora que permite integrar los mencionados atlas de expresión genética tridimensionales dentro del linaje celular extraído de una adquisición in vivo de un embrión. Esta prueba conceptual abre la puerta a la posibilidad de correlar, por primera vez, las dinámicas espacio-temporales de genes y células.

Digital image processing techniques as a tool for evaluating and mapping patinas on granite monuments

Monument conservation is related to the interaction between the original petrological parameters of the rock and external factors in the area where the building is sited, such as weather conditions, pollution, and so on. Depending on the environmental conditions and the characteristics of the materials used, different types of weathering predominate. In all, the appearance of surface crusts constitutes a first stage, whose origin can often be traced to the properties of the material itself. In the present study, different colours of “patinas” were distinguished by defining the threshold levels of greys associated with “pathology” in the histogram. These data were compared to background information and other parameters, such as mineralogical composition, porosity, and so on, as well as other visual signs of deterioration. The result is a map of the pathologies associated with “cover films” on monuments, which generate images by relating colour characteristics to desired properties or zones of interest.

Toward reduction of artifacts in fused images

Most fusion satellite image methodologies at pixel-level introduce false spatial details, i.e.artifacts, in the resulting fusedimages. In many cases, these artifacts appears because image fusion methods do not consider the differences in roughness or textural characteristics between different land covers. They only consider the digital values associated with single pixels. This effect increases as the spatial resolution image increases. To minimize this problem, we propose a new paradigm based on local measurements of the fractal dimension (FD). Fractal dimension maps (FDMs) are generated for each of the source images (panchromatic and each band of the multi-spectral images) with the box-counting algorithm and by applying a windowing process. The average of source image FDMs, previously indexed between 0 and 1, has been used for discrimination of different land covers present in satellite images. This paradigm has been applied through the fusion methodology based on the discrete wavelet transform (DWT), using the à trous algorithm (WAT). Two different scenes registered by optical sensors on board FORMOSAT-2 and IKONOS satellites were used to study the behaviour of the proposed methodology. The implementation of this approach, using the WAT method, allows adapting the fusion process to the roughness and shape of the regions present in the image to be fused. This improves the quality of the fusedimages and their classification results when compared with the original WAT method

A proposal for the metrological characterization of circular features with digital optical machines

This paper aims to analyze the different adjustment methods commonly used to characterize indirect metrology circular features: least square circle, minimum zone circle, maximum inscribed circle and minimum circumscribed circle. The analysis was performed from images obtained by digital optical machines. The calculation algorithms, self-developed, have been implemented in Matlab® and take into consideration as study variables: the amplitude of angular sector of the circular feature, its nominal radio and the magnification used by the optical machine. Under different conditions, it was determined the radius and circularity error of different circular standards. The comparison of the results, obtained by the different methods of adjustments used, with certified values for the standards, has allowed us to determine the accuracy of each method and its scope.

A Multiresolution Image Alignment Technique Based on Direct Methods for Pose Estimation of Aerial Vehicles

In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi-Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles' state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle's state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle's state for more than one minute, at real-time frame rates based, only on visual information.

Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images

Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (Λ1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates