Robust thermal face recognition using region classifiers

This paper presents a robust approach for recognition of thermal face images based on decision level fusion of 34 different region classifiers. The region classifiers concentrate on local variations. They use singular value decomposition (SVD) for feature extraction. Fusion of decisions of the region classifier is done by using majority voting technique. The algorithm is tolerant against false exclusion of thermal information produced by the presence of inconsistent distribution of temperature statistics which generally make the identification process difficult. The algorithm is extensively evaluated on UGC-JU thermal face database, and Terravic facial infrared database and the recognition performance are found to be 95.83% and 100%, respectively. A comparative study has also been made with the existing works in the literature.

Definición de un Modelo Edafogeomorfológico para la Identificación de Necesidades de Manejo y Recuperación de Suelos a Nivel Local. Caso Cuenca Cañada La Gorda, Machiques Colón, Estado Zulia, Venezuela.

El objetivo de este trabajo es generar un modelo Edafogeomorfológico útil en la identificación de necesidades de manejo de suelos, se realizó un estudio en el área de la cuenca Cañada La Gorda Machiques-Colón, estado Zulia, Venezuela, caracterizada por un clima tropical de condición subhúmeda, con duración del periodo de crecimiento (DPC) de 230 días, régimen de humedad Ustic y de temperatura Isohipertémico. Se empleó el enfoque de la ecuación factorial de formación de suelos para el análisis y descripción biofísica de los factores a lo largo de una carena. El relieve caracterizado a partir de fotografías aéreas, imágenes de satélites y de chequeos sistemático mediante transectos en el sentido del flujo del escurrimiento; la vegetación a través del uso de la tierra, la cobertura vegetal, la identificación de las especies dominantes a partir de sus nombres vernáculos y la definición de indicadores de vegetales (Iv). Los suelos fueron descritos y clasificados según la Taxonomía de suelos y valorados mediante el modelo paramétricode Riquier et al. (1970) para determinar el índice de productividad (Ip). Se caracterizaron dos paisajes gemorfológicos: Colinar (C) y Valle (V), seis posiciones geomorfológicas entre ambos paisajes definidas por la sucesión de relieves en el sentido de la pendiente: Tope de colina-loma (TC), mesa conservada (MC), vertientes de mesa alta (VA), media (VM), baja (VB) y valle intracolinar (VI); e igual número de perfiles de suelos representativos, los cuales mostraron edafogénesis muy avanzada con Ip inferiores a 8% en todas las posiciones, exceptuando la VB, con una productividad de 13%. El uso de la tierra es a base de pastoreo semi-intensivo de plantas forrajeras introducidas. Las formaciones vegetales predominante fueron los matorrales y arbustales dispersos, acompañados con restos de una selva tropófila fuertemente afectada por la extracción forestal y la conversión en áreas de pastoreo. Se identificaron 8 Iv, asociados fuertemente con condiciones de físicas e hidrológicas del suelo. El alto impacto de las actividades humanas sobre el suelo y vegetación, expresado a través de los procesos de erosión activa, la ausencia de áreas boscosas y la baja productividad de los sistemas de ganadería reportada para la zona, señalan la necesidad de reorientación del uso actual de la tierra, para lo cual se plantean alternativas como la incorporación de bosques protectores y sistemas agrosilvopastoriles In order to generate an Edaphogeomorphological model to be used for the identification of management requirements of soils, a study was carried out in the area of the Cañada La Gorda watershed, Machiques Colon, Zulia State with a tropical climate, subsumid conditions with a growing period of 230 days, an Ustic soil moisture and Isohypertermic regimes. The soils factorial equation approach was used for the analisis and description of the factors of soil formation throughout a soil catena. Relief was characterized through aerial photographs, satellite images and systematic checks of transects drawn in the sense of surface runoff and also taking into account geomorphological features. Vegetation cover and land use were described and vegetation components were indified by its local names to defined vegetations indicators (VI) for the local conditions. Soils were described and classified according to soil taxonomy and valued by means of a parametric model proposed by Riquier et al, (1970) for determining the productivity index (PI). Two geomorphological landscapes were defined: Hilly and Valley with six positions within the landscapes: hilltop (round or elongated), preserved tableland summit, slopes of high, medium and low tableland and valleys between hills. Representative soils of each position were studied showing a highly advanced degree of edaphogenesis with PI values below 8% in all positions except the valleys with a PI of 13%. Land use type is based on semi intensive pasturing of introduced forage species, with a vegetation of brushwood and scattered shrubs, with some trees relicts of woods affected by timber extraction and turn to grassland Eight VI were identified, highly associated to local physical and hidrological soil conditions. The enormous impact of human activity on soils and vegetation as shown by active erosion processes and absence of wooded areas and the low productivity of livestock systems reported for the area, indicates the necessity of a reorientation of the present land use introducing alternatives like the incorporation of protective woods and agrosilvopastoral management systems.

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.

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.

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.

Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

Rapid prototyping framework for visual control of autonomous micro aerial vehicles

Rapid prototyping environments can speed up the research of visual control algorithms. We have designed and implemented a software framework for fast prototyping of visual control algorithms for Micro Aerial Vehicles (MAV). We have applied a combination of a proxy-based network communication architecture and a custom Application Programming Interface. This allows multiple experimental configurations, like drone swarms or distributed processing of a drone’s video stream. Currently, the framework supports a low-cost MAV: the Parrot AR.Drone. Real tests have been performed on this platform and the results show comparatively low figures of the extra communication delay introduced by the framework, while adding new functionalities and flexibility to the selected drone. This implementation is open-source and can be downloaded from www.vision4uav.com/?q=VC4MAV-FW

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.

Visual Tracking, Pose Estimation, and Control for Aerial Vehicles

El principal objetivo de esta tesis es dotar a los vehículos aéreos no tripulados (UAVs, por sus siglas en inglés) de una fuente de información adicional basada en visión. Esta fuente de información proviene de cámaras ubicadas a bordo de los vehículos o en el suelo. Con ella se busca que los UAVs realicen tareas de aterrizaje o inspección guiados por visión, especialmente en aquellas situaciones en las que no haya disponibilidad de estimar la posición del vehículo con base en GPS, cuando las estimaciones de GPS no tengan la suficiente precisión requerida por las tareas a realizar, o cuando restricciones de carga de pago impidan añadir sensores a bordo de los vehículos. Esta tesis trata con tres de las principales áreas de la visión por computador: seguimiento visual y estimación visual de la pose (posición y orientación), que a su vez constituyen la base de la tercera, denominada control servo visual, que en nuestra aplicación se enfoca en el empleo de información visual para controlar los UAVs. Al respecto, esta tesis se ocupa de presentar propuestas novedosas que permitan solucionar problemas relativos al seguimiento de objetos mediante cámaras ubicadas a bordo de los UAVs, se ocupa de la estimación de la pose de los UAVs basada en información visual obtenida por cámaras ubicadas en el suelo o a bordo, y también se ocupa de la aplicación de las técnicas propuestas para solucionar diferentes problemas, como aquellos concernientes al seguimiento visual para tareas de reabastecimiento autónomo en vuelo o al aterrizaje basado en visión, entre otros. Las diversas técnicas de visión por computador presentadas en esta tesis se proponen con el fin de solucionar dificultades que suelen presentarse cuando se realizan tareas basadas en visión con UAVs, como las relativas a la obtención, en tiempo real, de estimaciones robustas, o como problemas generados por vibraciones. Los algoritmos propuestos en esta tesis han sido probados con información de imágenes reales obtenidas realizando pruebas on-line y off-line. Diversos mecanismos de evaluación han sido empleados con el propósito de analizar el desempeño de los algoritmos propuestos, entre los que se incluyen datos simulados, imágenes de vuelos reales, estimaciones precisas de posición empleando el sistema VICON y comparaciones con algoritmos del estado del arte. Los resultados obtenidos indican que los algoritmos de visión por computador propuestos tienen un desempeño que es comparable e incluso mejor al de algoritmos que se encuentran en el estado del arte. Los algoritmos propuestos permiten la obtención de estimaciones robustas en tiempo real, lo cual permite su uso en tareas de control visual. El desempeño de estos algoritmos es apropiado para las exigencias de las distintas aplicaciones examinadas: reabastecimiento autónomo en vuelo, aterrizaje y estimación del estado del UAV. Abstract The main objective of this thesis is to provide Unmanned Aerial Vehicles (UAVs) with an additional vision-based source of information extracted by cameras located either on-board or on the ground, in order to allow UAVs to develop visually guided tasks, such as landing or inspection, especially in situations where GPS information is not available, where GPS-based position estimation is not accurate enough for the task to develop, or where payload restrictions do not allow the incorporation of additional sensors on-board. This thesis covers three of the main computer vision areas: visual tracking and visual pose estimation, which are the bases the third one called visual servoing, which, in this work, focuses on using visual information to control UAVs. In this sense, the thesis focuses on presenting novel solutions for solving the tracking problem of objects when using cameras on-board UAVs, on estimating the pose of the UAVs based on the visual information collected by cameras located either on the ground or on-board, and also focuses on applying these proposed techniques for solving different problems, such as visual tracking for aerial refuelling or vision-based landing, among others. The different computer vision techniques presented in this thesis are proposed to solve some of the frequently problems found when addressing vision-based tasks in UAVs, such as obtaining robust vision-based estimations at real-time frame rates, and problems caused by vibrations, or 3D motion. All the proposed algorithms have been tested with real-image data in on-line and off-line tests. Different evaluation mechanisms have been used to analyze the performance of the proposed algorithms, such as simulated data, images from real-flight tests, publicly available datasets, manually generated ground truth data, accurate position estimations using a VICON system and a robotic cell, and comparison with state of the art algorithms. Results show that the proposed computer vision algorithms obtain performances that are comparable to, or even better than, state of the art algorithms, obtaining robust estimations at real-time frame rates. This proves that the proposed techniques are fast enough for vision-based control tasks. Therefore, the performance of the proposed vision algorithms has shown to be of a standard appropriate to the different explored applications: aerial refuelling and landing, and state estimation. It is noteworthy that they have low computational overheads for vision systems.

Multiple Hashing Integration for Real-Time Large Scale Part-to-Part Video Matching

A real-time large scale part-to-part video matching algorithm, based on the cross correlation of the intensity of motion curves, is proposed with a view to originality recognition, video database cleansing, copyright enforcement, video tagging or video result re-ranking. Moreover, it is suggested how the most representative hashes and distance functions - strada, discrete cosine transformation, Marr-Hildreth and radial - should be integrated in order for the matching algorithm to be invariant against blur, compression and rotation distortions: (R; _) 2 [1; 20]_[1; 8], from 512_512 to 32_32pixels2 and from 10 to 180_. The DCT hash is invariant against blur and compression up to 64x64 pixels2. Nevertheless, although its performance against rotation is the best, with a success up to 70%, it should be combined with the Marr-Hildreth distance function. With the latter, the image selected by the DCT hash should be at a distance lower than 1.15 times the Marr-Hildreth minimum distance.

A vision-based strategy for autonomous aerial refueling tasks

Autonomous aerial refueling is a key enabling technology for both manned and unmanned aircraft where extended flight duration or range are required. The results presented within this paper offer one potential vision-based sensing solution, together with a unique test environment. A hierarchical visual tracking algorithm based on direct methods is proposed and developed for the purposes of tracking a drogue during the capture stage of autonomous aerial refueling, and of estimating its 3D position. Intended to be applied in real time to a video stream from a single monocular camera mounted on the receiver aircraft, the algorithm is shown to be highly robust, and capable of tracking large, rapid drogue motions within the frame of reference. The proposed strategy has been tested using a complex robotic testbed and with actual flight hardware consisting of a full size probe and drogue. Results show that the vision tracking algorithm can detect and track the drogue at real-time frame rates of more than thirty frames per second, obtaining a robust position estimation even with strong motions and multiple occlusions of the drogue.

Time required to stabilize thermographic images at rest

Thermography for scientific research and practical purposes requires a series of procedures to obtain images that should be standardized; one of the most important is the time required for acclimatization in the controlled environment. Thus, the objective of this study was to identify the appropriate acclimatization time in rest to reach a thermal balance on young people skin. Forty-four subjects participated in the study, 18 men (22.3 ± 3.1 years) and 26 women (21.7 ± 2.5 years). Thermographic images were collected using a thermal imager (Fluke ®), totaling 44 images over a period of 20 minutes. The skin temperature (TSK) was measured at the point of examination which included the 0 minute, 2, 4, 6, 8, 10, 12, 14, 16, 18 and 20. The body regions of interest (ROI) analyzed included the hands, forearms, arms, thighs, legs, chest and abdomen. We used the Friedman test with post hoc Dunn?s in order to establish the time at rest required to obtain a TSK balance and the Mann-Whitney test was used to compare age, BMI, body fat percentage and temperature variations between men and women, considering always a significance level of pmenor que0.05. Results showed that women had significantly higher temperature variations than men (pmenor que0.01) along the time. In men, only the body region of the abdomen obtained a significant variance (pmenor que0.05) on the analyzed period, both in the anterior and posterior part. In women, the anterior abdomen and thighs, and the posterior part of the hands, forearms and abdomen showed significant differences (pmenor que0.05). Based on our results, it can be concluded that the time in rest condition required reaching a TSK balance in young men and women is variable, but for whole body analysis it is recommended at least 10 minutes for both sexes.

Evaluation of cover crops based on characteristics of nitrogen use, and aerial and root growth

La caracterización de los cultivos cubierta (cover crops) puede permitir comparar la idoneidad de diferentes especies para proporcionar servicios ecológicos como el control de la erosión, el reciclado de nutrientes o la producción de forrajes. En este trabajo se estudiaron bajo condiciones de campo diferentes técnicas para caracterizar el dosel vegetal con objeto de establecer una metodología para medir y comparar las arquitecturas de los cultivos cubierta más comunes. Se estableció un ensayo de campo en Madrid (España central) para determinar la relación entre el índice de área foliar (LAI) y la cobertura del suelo (GC) para un cultivo de gramínea, uno de leguminosa y uno de crucífera. Para ello se sembraron doce parcelas con cebada (Hordeum vulgare L.), veza (Vicia sativa L.), y colza (Brassica napus L.). En 10 fechas de muestreo se midieron el LAI (con estimaciones directas y del LAI-2000), la fracción interceptada de la radiación fotosintéticamente activa (FIPAR) y la GC. Un experimento de campo de dos años (Octubre-Abril) se estableció en la misma localización para evaluar diferentes especies (Hordeum vulgare L., Secale cereale L., x Triticosecale Whim, Sinapis alba L., Vicia sativa L.) y cultivares (20) en relación con su idoneidad para ser usadas como cultivos cubierta. La GC se monitorizó mediante análisis de imágenes digitales con 21 y 22 muestreos, y la biomasa se midió 8 y 10 veces, respectivamente para cada año. Un modelo de Gompertz caracterizó la cobertura del suelo hasta el decaimiento observado tras las heladas, mientras que la biomasa se ajustó a ecuaciones de Gompertz, logísticas y lineales-exponenciales. Al final del experimento se determinaron el C, el N y el contenido en fibra (neutrodetergente, ácidodetergente y lignina), así como el N fijado por las leguminosas. Se aplicó el análisis de decisión multicriterio (MCDA) con objeto de obtener un ranking de especies y cultivares de acuerdo con su idoneidad para actuar como cultivos cubierta en cuatro modalidades diferentes: cultivo de cobertura, cultivo captura, abono verde y forraje. Las asociaciones de cultivos leguminosas con no leguminosas pueden afectar al crecimiento radicular y a la absorción de N de ambos componentes de la mezcla. El conocimiento de cómo los sistemas radiculares específicos afectan al crecimiento individual de las especies es útil para entender las interacciones en las asociaciones, así como para planificar estrategias de cultivos cubierta. En un tercer ensayo se combinaron estudios en rhizotrones con extracción de raíces e identificación de especies por microscopía, así como con estudios de crecimiento, absorción de N y 15N en capas profundas del suelo. Las interacciones entre raíces en su crecimiento y en el aprovisionamiento de N se estudiaron para dos de los cultivares mejor valorados en el estudio previo: uno de cebada (Hordeum vulgare L. cv. Hispanic) y otro de veza (Vicia sativa L. cv. Aitana). Se añadió N en dosis de 0 (N0), 50 (N1) y 150 (N2) kg N ha-1. Como resultados del primer estudio, se ajustaron correctamente modelos lineales y cuadráticos a la relación entre la GC y el LAI para todos los cultivos, pero en la gramínea alcanzaron una meseta para un LAI>4. Antes de alcanzar la cobertura total, la pendiente de la relación lineal entre ambas variables se situó en un rango entre 0.025 y 0.030. Las lecturas del LAI-2000 estuvieron correlacionadas linealmente con el LAI, aunque con tendencia a la sobreestimación. Las correcciones basadas en el efecto de aglutinación redujeron el error cuadrático medio del LAI estimado por el LAI-2000 desde 1.2 hasta 0.5 para la crucífera y la leguminosa, no siendo efectivas para la cebada. Esto determinó que para los siguientes estudios se midieran únicamente la GC y la biomasa. En el segundo experimento, las gramíneas alcanzaron la mayor cobertura del suelo (83-99%) y la mayor biomasa (1226-1928 g m-2) al final del mismo. Con la mayor relación C/N (27-39) y contenido en fibra digestible (53-60%) y la menor calidad de residuo (~68%). La mostaza presentó elevadas GC, biomasa y absorción de N en el año más templado en similitud con las gramíneas, aunque escasa calidad como forraje en ambos años. La veza presentó la menor absorción de N (2.4-0.7 g N m-2) debido a la fijación de N (9.8-1.6 g N m-2) y escasa acumulación de N. El tiempo térmico hasta alcanzar el 30% de GC constituyó un buen indicador de especies de rápida cubrición. La cuantificación de las variables permitió hallar variabilidad entre las especies y proporcionó información para posteriores decisiones sobre la selección y manejo de los cultivos cubierta. La agregación de dichas variables a través de funciones de utilidad permitió confeccionar rankings de especies y cultivares para cada uso. Las gramíneas fueron las más indicadas para los usos de cultivo de cobertura, cultivo captura y forraje, mientras que las vezas fueron las mejor como abono verde. La mostaza alcanzó altos valores como cultivo de cobertura y captura en el primer año, pero el segundo decayó debido a su pobre actuación en los inviernos fríos. Hispanic fue el mejor cultivar de cebada como cultivo de cobertura y captura, mientras que Albacete como forraje. El triticale Titania alcanzó la posición más alta como cultiva de cobertura, captura y forraje. Las vezas Aitana y BGE014897 mostraron buenas aptitudes como abono verde y cultivo captura. El MCDA permitió la comparación entre especies y cultivares proporcionando información relevante para la selección y manejo de cultivos cubierta. En el estudio en rhizotrones tanto la mezcla de especies como la cebada alcanzaron mayor intensidad de raíces (RI) y profundidad (RD) que la veza, con valores alrededor de 150 cruces m-1 y 1.4 m respectivamente, comparados con 50 cruces m-1 y 0.9 m para la veza. En las capas más profundas del suelo, la asociación de cultivos mostró valores de RI ligeramente mayores que la cebada en monocultivo. La cebada y la asociación obtuvieron mayores valores de densidad de raíces (RLD) (200-600 m m-3) que la veza (25-130) entre 0.8 y 1.2 m de profundidad. Los niveles de N no mostraron efectos claros en RI, RD ó RLD, sin embargo, el incremento de N favoreció la proliferación de raíces de veza en la asociación en capas profundas del suelo, con un ratio cebada/veza situado entre 25 a N0 y 5 a N2. La absorción de N de la cebada se incrementó en la asociación a expensas de la veza (de ~100 a 200 mg planta-1). Las raíces de cebada en la asociación absorbieron también más nitrógeno marcado de las capas profundas del suelo (0.6 mg 15N planta-1) que en el monocultivo (0.3 mg 15N planta-1). ABSTRACT Cover crop characterization may allow comparing the suitability of different species to provide ecological services such as erosion control, nutrient recycling or fodder production. Different techniques to characterize plant canopy were studied under field conditions in order to establish a methodology for measuring and comparing cover crops canopies. A field trial was established in Madrid (central Spain) to determine the relationship between leaf area index (LAI) and ground cover (GC) in a grass, a legume and a crucifer crop. Twelve plots were sown with either barley (Hordeum vulgare L.), vetch (Vicia sativa L.), or rape (Brassica napus L.). On 10 sampling dates the LAI (both direct and LAI-2000 estimations), fraction intercepted of photosynthetically active radiation (FIPAR) and GC were measured. A two-year field experiment (October-April) was established in the same location to evaluate different species (Hordeum vulgare L., Secale cereale L., x Triticosecale Whim, Sinapis alba L., Vicia sativa L.) and cultivars (20) according to their suitability to be used as cover crops. GC was monitored through digital image analysis with 21 and 22 samples, and biomass measured 8 and 10 times, respectively for each season. A Gompertz model characterized ground cover until the decay observed after frosts, while biomass was fitted to Gompertz, logistic and linear-exponential equations. At the end of the experiment C, N, and fiber (neutral detergent, acid and lignin) contents, and the N fixed by the legumes were determined. Multicriteria decision analysis (MCDA) was applied in order to rank the species and cultivars according to their suitability to perform as cover crops in four different modalities: cover crop, catch crop, green manure and fodder. Intercropping legumes and non-legumes may affect the root growth and N uptake of both components in the mixture. The knowledge of how specific root systems affect the growth of the individual species is useful for understanding the interactions in intercrops as well as for planning cover cropping strategies. In a third trial rhizotron studies were combined with root extraction and species identification by microscopy and with studies of growth, N uptake and 15N uptake from deeper soil layers. The root interactions of root growth and N foraging were studied for two of the best ranked cultivars in the previous study: a barley (Hordeum vulgare L. cv. Hispanic) and a vetch (Vicia sativa L. cv. Aitana). N was added at 0 (N0), 50 (N1) and 150 (N2) kg N ha-1. As a result, linear and quadratic models fitted to the relationship between the GC and LAI for all of the crops, but they reached a plateau in the grass when the LAI > 4. Before reaching full cover, the slope of the linear relationship between both variables was within the range of 0.025 to 0.030. The LAI-2000 readings were linearly correlated with the LAI but they tended to overestimation. Corrections based on the clumping effect reduced the root mean square error of the estimated LAI from the LAI-2000 readings from 1.2 to less than 0.50 for the crucifer and the legume, but were not effective for barley. This determined that in the following studies only the GC and biomass were measured. In the second experiment, the grasses reached the highest ground cover (83- 99%) and biomass (1226-1928 g/m2) at the end of the experiment. The grasses had the highest C/N ratio (27-39) and dietary fiber (53-60%) and the lowest residue quality (~68%). The mustard presented high GC, biomass and N uptake in the warmer year with similarity to grasses, but low fodder capability in both years. The vetch presented the lowest N uptake (2.4-0.7 g N/m2) due to N fixation (9.8-1.6 g N/m2) and low biomass accumulation. The thermal time until reaching 30% ground cover was a good indicator of early coverage species. Variable quantification allowed finding variability among the species and provided information for further decisions involving cover crops selection and management. Aggregation of these variables through utility functions allowed ranking species and cultivars for each usage. Grasses were the most suitable for the cover crop, catch crop and fodder uses, while the vetches were the best as green manures. The mustard attained high ranks as cover and catch crop the first season, but the second decayed due to low performance in cold winters. Hispanic was the most suitable barley cultivar as cover and catch crop, and Albacete as fodder. The triticale Titania attained the highest rank as cover and catch crop and fodder. Vetches Aitana and BGE014897 showed good aptitudes as green manures and catch crops. MCDA allowed comparison among species and cultivars and might provide relevant information for cover crops selection and management. In the rhizotron study the intercrop and the barley attained slightly higher root intensity (RI) and root depth (RD) than the vetch, with values around 150 crosses m-1 and 1.4 m respectively, compared to 50 crosses m-1 and 0.9 m for the vetch. At deep soil layers, intercropping showed slightly larger RI values compared to the sole cropped barley. The barley and the intercropping had larger root length density (RLD) values (200-600 m m-3) than the vetch (25-130) at 0.8-1.2 m depth. The topsoil N supply did not show a clear effect on the RI, RD or RLD; however increasing topsoil N favored the proliferation of vetch roots in the intercropping at deep soil layers, with the barley/vetch root ratio ranging from 25 at N0 to 5 at N2. The N uptake of the barley was enhanced in the intercropping at the expense of the vetch (from ~100 mg plant-1 to 200). The intercropped barley roots took up more labeled nitrogen (0.6 mg 15N plant-1) than the sole-cropped barley roots (0.3 mg 15N plant-1) from deep layers.

Aerial Coverage Path Planning applied to Mapping

In the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the off-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a fleet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with different shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies different computational geometry approaches, providing a unique way to deal with workspaces with different shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-off and landing positions as well as a safety distance between elements of the fleet. Moreover, it has to avoid forbidden zones to y. Three different algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of field experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the findings attained from this thesis improve ACPP mission for mapping purpose in an efficient and safe manner.