Variation des biomarqueurs dans le spectre visible non résolu de la Terre

L’évolution rapide des technologies de détection et de caractérisation des exoplanètes depuis le début des années 1990 permet de croire que de nouveaux instruments du type Terrestrial Planet Finder (TPF) pourront prendre les premiers spectres d’exoplanètes semblables à la Terre d’ici une ou deux décennies. Dans ce contexte, l’étude du spectre de la seule planète habitée connue, la Terre, est essentielle pour concevoir ces instruments et analyser leurs résultats. Cette recherche présente les spectres de la Terre dans le visible (390-900 nm), acquis lors de 8 nuits d’observation étalées sur plus d’un an. Ces spectres ont été obtenus en observant la lumière cendrée de la Lune avec le télescope de 1.6 m de l’Observatoire du Mont-Mégantic (OMM). La surface de la Lune réfléchissant de manière diffuse la lumière provenant d’une portion de la Terre, ces spectres sont non résolus spatialement. L’évolution de ces spectres en fonction de la lumière réfléchie à différentes phases de Terre est analogue à celle du spectre d’une exoplanète, dont la phase change selon sa position autour de l’étoile. L'eau, l'oxygène et l'ozone de l’atmosphère, détectés dans tous nos spectres, sont des biomarqueurs dont la présence suggère l’habitabilité de la planète et/ou la présence d’une activité biologique. Le Vegetation Red Edge (VRE), une autre biosignature spectrale, dû aux organismes photosynthétiques à la surface, est caractérisé par l’augmentation de la réflectivité autour de 700 nm. Pour les spectres de 5 nuits, cette augmentation a été évaluée entre -5 et 15% ±~5%, après que les contributions de la diffusion de Rayleigh, des aérosols et d’une large bande moléculaire de l’ozone aient été enlevées. Les valeurs mesurées sont cohérentes avec la présence de végétation dans la phase de la Terre contribuant au spectre, mais s’étendent sur une plage de variations plus large que celles trouvées dans la littérature (0-10%). Cela pourrait s’expliquer par des choix faits lors de la réduction des données et du calcul du VRE, ou encore par la présence d’autres éléments de surface ou de l’atmosphère dont la contribution spectrale autour de 700 nm serait variable.

Étude des propriétés plasmoniques des réseaux de nanotrous

Les réseaux de nanotrous sont des structures plasmoniques ayant un énorme potentiel en tant que transducteurs pour la conception de biocapteurs. De telles structures sont prometteuses pour l’élaboration de biocapteurs capable d’effectuer du criblage à haut débit. L’intérêt de travailler avec des réseaux de nanotrous est dû à la simplicité d’excitation des polaritons de plasmons de surface en transmission directe, à la sensibilité et à la facilité de fabrication de ces senseurs. L’architecture de tels réseaux métalliques permet la conception de nanostructures ayant de multiples propriétés plasmoniques. L’intensité, la signature spectrale et la sensibilité du signal plasmonique sont grandement affectées par l’aspect physique du réseau de nanotrous. L’optimisation du signal plasmonique nécessite ainsi un ajustement du diamètre des trous, de la périodicité et de la composition métallique du réseau. L'agencement de l'ensemble de ces paramètres permet d'identifier une structure optimale possédant une périodicité de 1000 nm, un diamètre des nanotrous de 600-650 nm et un film métallique ayant une épaisseur de 125 nm d'or. Ce type de transducteur a une sensibilité en solution de 500-600 nm/RIU pour des bandes plasmoniques situées entre 600-700 nm. L'intérêt de travailler avec cette structure est la possibilité d'exciter les plasmons de polaritons de surface (SPPs) selon deux modes d'excitation : en transmission exaltée (EOT) ou en réflexion totale interne par résonance des plasmons de surface (SPR). Une comparaison entre les propriétés plasmoniques des senseurs selon les modes d'excitation permet de déterminer expérimentalement que le couplage de la lumière avec les ondes de SPP de Bloch (BW-SPPs) en transmission directe résulte en un champ électromagnétique davantage propagatif que localisé. D'un point de vue analytique, la biodétection de l'IgG en SPR est 6 fois plus sensible par rapport au mode EOT pour une même structure. Une étude du signal plasmonique associé au BW-SPP pour un certain mode de diffraction démontre que la distance de pénétration de ces structures en EOT est d'environ 140 nm. La limite de détection de l'IgG humain pour un réseau de nanotrous de 1000 nm de périodicité est d'environ 50 nM en EOT. Ce mémoire démontre la viabilité des réseaux de nanotrous pour effectuer de la biodétection par criblage à haut débit lors de prochaines recherches. L'investigation de l'effet de l'angle d'excitation en transmission exaltée par rapport au signal plasmonique associé au mode (1,0) d'un réseau de nanotrous de 820 nm d'or démontre que la sensibilité en solution n'est pas proportionnelle à la sensibilité en surface du senseur. En fait, une optimisation de l'angle d'incidence pour le mode (1,0) de diffraction des BW-SPP permet d'amplifier la sensibilité en surface du senseur jusqu'à 3-fois pour un angle de 13,3°. Ce mémoire démontre ainsi la nécessité d'optimiser l'angle d'excitation et les propriétés physiques du senseur afin de développer un transducteur de grande sensibilité basé sur l'excitation en transmission de réseaux de nanotrous.

Frequency Coded Chipless RFID Tag using Spurline Resonators

A novel compact chipless RFID tag using spurline resonators is discussed in this paper. The detection of the tag's ID is using the spectral signature of a spurline resonator circuit. The tag has a data capacity of 8-bits in the range 2.38 to 4.04 GHz. The tag consists of a spurline multiresonating circuit and two cross polarized antennas. The prototype of the tag is fabricated on a substrate CMET/ LK4.3 of dielectric constant 4.3 and loss tangent 0.0018. The measured results show that group delay response can also be used to decode the tag’s identity

Abrasion control on dune colour: Muleshoe Dunes, SW USA

The Muleshoe Dunes, an east-west trending dunefield on the border separating Texas and New Mexico, consist of two distinct components: a white (carbonate rich) component and an overlying pink (quartz rich) component. The pink component exhibits significant spatial variation in redness. The reddest sands, in the western part of the dunefield, decrease in redness towards the east. This gradient is thought to result from abrasion of all iron-rich, red clay coating as the sediments were transported eastward by Late Quaternary aeolian processes. The effects of aeolian abrasion on the spectral signature and surface texture of the sediments were examined using laboratory abrasion experiments. Changes in spectral reflectance of abrasion samples from the laboratory were compared to field samples that were abraded naturally because of sediment transport. The changes resulting from increased time of abrasion are similar to those observed with increased distance downwind in the dunefield. These results suggest that downwind abrasion can explain the pattern of dune colour in the Muleshoe Dunes, although this does not preclude other possible causes. (C) 2008 Elsevier B.V. All rights reserved.

Abrasion control on dune colour: Muleshoe Dunes, SW USA

The Muleshoe Dunes, an east-west trending dunefield on the border separating Texas and New Mexico, consist of two distinct components: a white (carbonate rich) component and an overlying pink (quartz rich) component. The pink component exhibits significant spatial variation in redness. The reddest sands, in the western part of the dunefield, decrease in redness towards the east. This gradient is thought to result from abrasion of all iron-rich, red clay coating as the sediments were transported eastward by Late Quaternary aeolian processes. The effects of aeolian abrasion on the spectral signature and surface texture of the sediments were examined using laboratory abrasion experiments. Changes in spectral reflectance of abrasion samples from the laboratory were compared to field samples that were abraded naturally because of sediment transport. The changes resulting from increased time of abrasion are similar to those observed with increased distance downwind in the dunefield. These results suggest that downwind abrasion can explain the pattern of dune colour in the Muleshoe Dunes, although this does not preclude other possible causes. (C) 2008 Elsevier B.V. All rights reserved.

Characterization of a highly biodiverse floodplain meadow using hyperspectral remote sensing within a plant functional trait framework

We assessed the potential for using optical functional types as effective markers to monitor changes in vegetation in floodplain meadows associated with changes in their local environment. Floodplain meadows are challenging ecosystems for monitoring and conservation because of their highly biodiverse nature. Our aim was to understand and explain spectral differences among key members of floodplain meadows and also characterize differences with respect to functional traits. The study was conducted on a typical floodplain meadow in UK (MG4-type, mesotrophic grassland type 4, according to British National Vegetation Classification). We compared two approaches to characterize floodplain communities using field spectroscopy. The first approach was sub-community based, in which we collected spectral signatures for species groupings indicating two distinct eco-hydrological conditions (dry and wet soil indicator species). The other approach was “species-specific”, in which we focused on the spectral reflectance of three key species found on the meadow. One herb species is a typical member of the MG4 floodplain meadow community, while the other two species, sedge and rush, represent wetland vegetation. We also monitored vegetation biophysical and functional properties as well as soil nutrients and ground water levels. We found that the vegetation classes representing meadow sub-communities could not be spectrally distinguished from each other, whereas the individual herb species was found to have a distinctly different spectral signature from the sedge and rush species. The spectral differences between these three species could be explained by their observed differences in plant biophysical parameters, as corroborated through radiative transfer model simulations. These parameters, such as leaf area index, leaf dry matter content, leaf water content, and specific leaf area, along with other functional parameters, such as maximum carboxylation capacity and leaf nitrogen content, also helped explain the species’ differences in functional dynamics. Groundwater level and soil nitrogen availability, which are important factors governing plant nutrient status, were also found to be significantly different for the herb/wetland species’ locations. The study concludes that spectrally distinguishable species, typical for a highly biodiverse site such as a floodplain meadow, could potentially be used as target species to monitor vegetation dynamics under changing environmental conditions.

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

Reflection of solar wind hydrogen from the lunar surface

The solar wind continuously flows out from the Sun and directly interacts with the surfaces of dust and airless planetary bodies throughout the solar system. A significant fraction of solar wind ions reflect from an object's surface as energetic neutral atoms (ENAs). ENA emission from the Moon was first observed during commissioning of the Interstellar Boundary Explorer (IBEX) mission on 3 December 2008. We present the analysis of 10 additional IBEX observations of the Moon while it was illuminated by the solar wind. For the viewing geometry and energy range (> 250 eV) of the IBEX-Hi ENA imager, we find that the spectral shape of the ENA emission from the Moon is well-represented by a linearly decreasing flux with increasing energy. The fraction of the incident solar wind ions reflected as ENAs, which is the ENA albedo and defined quantitatively as the ENA reflection coefficient RN, depends on the incident solar wind speed, ranging from ~0.2 for slow solar wind to ~0.08 for fast solar wind. The average energy per incident solar wind ion that is reflected to space is 30 eV for slow solar wind and 45 eV for fast solar wind. Once ionized, these ENAs can become pickup ions in the solar wind with a unique spectral signature that reaches 3vSW. These results apply beyond the solar system; the reflection process heats plasmas that have significant bulk flow relative to interstellar dust and cools plasmas having no net bulk flow relative to the dust.

Observations of the northern seasonal polar cap on Mars III: CRISM/HiRISE observations of spring sublimation

We analyze a series of targeted CRISM and HiRISE observations of seven regions of interest at high latitudes in the Northern polar regions of Mars. These data allow us to investigate the temporal evolution of the composition of the seasonal ice cap during spring, with a special emphasis on peculiar phenomena occurring in the dune fields and in the vicinity of the scarps of the North Polar Layered Deposits (NPLDs). The strength of the spectral signature of CO2 ice continuously decreases during spring whereas the one of H2O ice first shows a strong increase until Ls = 50°. This evolution is consistent with a scenario previously established from analysis of OMEGA data, in which a thin layer of pure H2O ice progressively develops at the surface of the volatile layer. During early spring (Ls < 10°), widespread jet activity is observed by HiRISE while strong spectral signatures of CO2 ice are detected by CRISM. Later, around Ls = 20-40°, activity concentrates at the dune fields where CRISM also detects a spectral enrichment in CO2 ice, consistent with "Kieffer's model" (Kieffer, H.H. [2007]. J. Geophys. Res. 112, E08005. doi:10.1029/2006JE002816) for jet activity. Effects of wind are prominent across the dune fields and seem to strongly influence the sublimation of the volatile layer. Strong winds blowing down the scarps could also be responsible for the significant spatial and temporal variability of the surface ice composition observed close to the NPLD.

Spectroscopy and detectability of liquid brines on mars

Recent geomorphological observations as well as chemical and thermodynamic studies demonstrate that liquid water should be stable today on the Martian surface at some times of the day. In Martian conditions, brines would be particularly more stable than pure water because salts can depress the freezing point and lower the evaporation rate of water. Despite this evidence, no clear spectral signature of liquid has been observed so far by the hyperspectral imaging spectrometers OMEGA and CRISM. However, past spectral analysis lacks a good characterization of brines׳ spectral signatures. This study thus aims to determine how liquid brines can be detected on Mars by spectroscopy. In this way, laboratory experiments were performed for reproducing hydration and dehydration cycles of various brines while measuring their spectral signatures. The resulting spectra first reveal a very similar spectral evolution for the various brine types and pure water, with the main difference observed at the end of the dehydration with the crystallization of various hydrated minerals from brines. The main characteristic of this spectral behavior is an important decoupling between the evolution of albedo and hydration bands depths. During most of the wetting/drying processes, spectra usually display a low albedo associated with shallow water absorption band depths. Strong water absorption band depth and high albedo are respectively only observed when the surface is very wet and when the surface is very dry. These experiments can thus explain why the currently active Martian features attributed to the action of a liquid are only associated with low albedo and very weak spectral signatures. Hydration experiments also reveal that deliquescence occurs easily even at low temperature and moderate soil water vapor pressure and could thus cause seasonal darkening on Mars. These experiments demonstrate that the absence of water absorptions in CRISM in the middle afternoon does not rule out water activity and suggest future spectral investigations to identify water on the Martian surface.

Variación temporal y espacial de parches, corredores y matriz en un humedal ("mallín") del centro-oeste de la provincia de Neuquén

Los procesos naturales, como las actividades humanas, cambian los paisajes. Esta realidad no es ajena a los humedales (mallines) en Patagonia. Los mallines son importantes ecosistemas naturales que sirven como recurso forrajero para la ganadería extensiva. Los mismos representan el 4 de la superficie patagónica. Los períodos húmedos y secos modifican la dinámica hidrológica del mallín. Esto repercute en la evolución de los parches, corredores y matriz, que se agrava con la actividad antrópica. En una secuencia temporal se puede apreciar la fragmentación del hábitat: en la variación y tamaño del número de parches, su forma, conectividad y aislamiento, que entre otros factores inciden sobre numerosos procesos ecológicos. El conocimiento de la dinámica temporal y espacial de los parches, corredores y matriz entre un período húmedo y uno seco en un humedal permite la planificación del uso del recurso vegetación, ya que los patrones espaciales controlan fuertemente sus movimientos, flujos y cambios.

Variación temporal y espacial de parches, corredores y matriz en un humedal ("mallín") del centro-oeste de la provincia de Neuquén

Los procesos naturales, como las actividades humanas, cambian los paisajes. Esta realidad no es ajena a los humedales (mallines) en Patagonia. Los mallines son importantes ecosistemas naturales que sirven como recurso forrajero para la ganadería extensiva. Los mismos representan el 4 de la superficie patagónica. Los períodos húmedos y secos modifican la dinámica hidrológica del mallín. Esto repercute en la evolución de los parches, corredores y matriz, que se agrava con la actividad antrópica. En una secuencia temporal se puede apreciar la fragmentación del hábitat: en la variación y tamaño del número de parches, su forma, conectividad y aislamiento, que entre otros factores inciden sobre numerosos procesos ecológicos. El conocimiento de la dinámica temporal y espacial de los parches, corredores y matriz entre un período húmedo y uno seco en un humedal permite la planificación del uso del recurso vegetación, ya que los patrones espaciales controlan fuertemente sus movimientos, flujos y cambios.

Variación temporal y espacial de parches, corredores y matriz en un humedal ("mallín") del centro-oeste de la provincia de Neuquén

Los procesos naturales, como las actividades humanas, cambian los paisajes. Esta realidad no es ajena a los humedales (mallines) en Patagonia. Los mallines son importantes ecosistemas naturales que sirven como recurso forrajero para la ganadería extensiva. Los mismos representan el 4 de la superficie patagónica. Los períodos húmedos y secos modifican la dinámica hidrológica del mallín. Esto repercute en la evolución de los parches, corredores y matriz, que se agrava con la actividad antrópica. En una secuencia temporal se puede apreciar la fragmentación del hábitat: en la variación y tamaño del número de parches, su forma, conectividad y aislamiento, que entre otros factores inciden sobre numerosos procesos ecológicos. El conocimiento de la dinámica temporal y espacial de los parches, corredores y matriz entre un período húmedo y uno seco en un humedal permite la planificación del uso del recurso vegetación, ya que los patrones espaciales controlan fuertemente sus movimientos, flujos y cambios.

A computer vision approach for weeds identification through Support Vector Machines

This paper outlines an automatic computervision system for the identification of avena sterilis which is a special weed seed growing in cereal crops. The final goal is to reduce the quantity of herbicide to be sprayed as an important and necessary step for precision agriculture. So, only areas where the presence of weeds is important should be sprayed. The main problems for the identification of this kind of weed are its similar spectral signature with respect the crops and also its irregular distribution in the field. It has been designed a new strategy involving two processes: image segmentation and decision making. The image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and weeds. The decision making is based on the SupportVectorMachines and determines if a cell must be sprayed. The main findings of this paper are reflected in the combination of the segmentation and the SupportVectorMachines decision processes. Another important contribution of this approach is the minimum requirements of the system in terms of memory and computation power if compared with other previous works. The performance of the method is illustrated by comparative analysis against some existing strategies.

Detección de patrones y anomalías espectrales del terreno mediante espectrometría de imagen de alta resolución : reconocimiento, optimización y evaluación multiescenario

El objeto de esta Tesis doctoral es el desarrollo de una metodologia para la deteccion automatica de anomalias a partir de datos hiperespectrales o espectrometria de imagen, y su cartografiado bajo diferentes condiciones tipologicas de superficie y terreno. La tecnologia hiperespectral o espectrometria de imagen ofrece la posibilidad potencial de caracterizar con precision el estado de los materiales que conforman las diversas superficies en base a su respuesta espectral. Este estado suele ser variable, mientras que las observaciones se producen en un numero limitado y para determinadas condiciones de iluminacion. Al aumentar el numero de bandas espectrales aumenta tambien el numero de muestras necesarias para definir espectralmente las clases en lo que se conoce como Maldicion de la Dimensionalidad o Efecto Hughes (Bellman, 1957), muestras habitualmente no disponibles y costosas de obtener, no hay mas que pensar en lo que ello implica en la Exploracion Planetaria. Bajo la definicion de anomalia en su sentido espectral como la respuesta significativamente diferente de un pixel de imagen respecto de su entorno, el objeto central abordado en la Tesis estriba primero en como reducir la dimensionalidad de la informacion en los datos hiperespectrales, discriminando la mas significativa para la deteccion de respuestas anomalas, y segundo, en establecer la relacion entre anomalias espectrales detectadas y lo que hemos denominado anomalias informacionales, es decir, anomalias que aportan algun tipo de informacion real de las superficies o materiales que las producen. En la deteccion de respuestas anomalas se asume un no conocimiento previo de los objetivos, de tal manera que los pixeles se separan automaticamente en funcion de su informacion espectral significativamente diferenciada respecto de un fondo que se estima, bien de manera global para toda la escena, bien localmente por segmentacion de la imagen. La metodologia desarrollada se ha centrado en la implicacion de la definicion estadistica del fondo espectral, proponiendo un nuevo enfoque que permite discriminar anomalias respecto fondos segmentados en diferentes grupos de longitudes de onda del espectro, explotando la potencialidad de separacion entre el espectro electromagnetico reflectivo y emisivo. Se ha estudiado la eficiencia de los principales algoritmos de deteccion de anomalias, contrastando los resultados del algoritmo RX (Reed and Xiaoli, 1990) adoptado como estandar por la comunidad cientifica, con el metodo UTD (Uniform Targets Detector), su variante RXD-UTD, metodos basados en subespacios SSRX (Subspace RX) y metodo basados en proyecciones de subespacios de imagen, como OSPRX (Orthogonal Subspace Projection RX) y PP (Projection Pursuit). Se ha desarrollado un nuevo metodo, evaluado y contrastado por los anteriores, que supone una variacion de PP y describe el fondo espectral mediante el analisis discriminante de bandas del espectro electromagnetico, separando las anomalias con el algortimo denominado Detector de Anomalias de Fondo Termico o DAFT aplicable a sensores que registran datos en el espectro emisivo. Se han evaluado los diferentes metodos de deteccion de anomalias en rangos del espectro electromagnetico del visible e infrarrojo cercano (Visible and Near Infrared-VNIR), infrarrojo de onda corta (Short Wavelenght Infrared-SWIR), infrarrojo medio (Meadle Infrared-MIR) e infrarrojo termico (Thermal Infrared-TIR). La respuesta de las superficies en las distintas longitudes de onda del espectro electromagnetico junto con su entorno, influyen en el tipo y frecuencia de las anomalias espectrales que puedan provocar. Es por ello que se han utilizado en la investigacion cubos de datos hiperepectrales procedentes de los sensores aeroportados cuya estrategia y diseno en la construccion espectrometrica de la imagen difiere. Se han evaluado conjuntos de datos de test de los sensores AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) y MASTER (MODIS/ASTER Simulator). Se han disenado experimentos sobre ambitos naturales, urbanos y semiurbanos de diferente complejidad. Se ha evaluado el comportamiento de los diferentes detectores de anomalias a traves de 23 tests correspondientes a 15 areas de estudio agrupados en 6 espacios o escenarios: Urbano - E1, Semiurbano/Industrial/Periferia Urbana - E2, Forestal - E3, Agricola - E4, Geologico/Volcanico - E5 y Otros Espacios Agua, Nubes y Sombras - E6. El tipo de sensores evaluados se caracteriza por registrar imagenes en un amplio rango de bandas, estrechas y contiguas, del espectro electromagnetico. La Tesis se ha centrado en el desarrollo de tecnicas que permiten separar y extraer automaticamente pixeles o grupos de pixeles cuya firma espectral difiere de manera discriminante de las que tiene alrededor, adoptando para ello como espacio muestral parte o el conjunto de las bandas espectrales en las que ha registrado radiancia el sensor hiperespectral. Un factor a tener en cuenta en la investigacion ha sido el propio instrumento de medida, es decir, la caracterizacion de los distintos subsistemas, sensores imagen y auxiliares, que intervienen en el proceso. Para poder emplear cuantitativamente los datos medidos ha sido necesario definir las relaciones espaciales y espectrales del sensor con la superficie observada y las potenciales anomalias y patrones objetivos de deteccion. Se ha analizado la repercusion que en la deteccion de anomalias tiene el tipo de sensor, tanto en su configuracion espectral como en las estrategias de diseno a la hora de registrar la radiacion prodecente de las superficies, siendo los dos tipos principales de sensores estudiados los barredores o escaneres de espejo giratorio (whiskbroom) y los barredores o escaneres de empuje (pushbroom). Se han definido distintos escenarios en la investigacion, lo que ha permitido abarcar una amplia variabilidad de entornos geomorfologicos y de tipos de coberturas, en ambientes mediterraneos, de latitudes medias y tropicales. En resumen, esta Tesis presenta una tecnica de deteccion de anomalias para datos hiperespectrales denominada DAFT en su variante de PP, basada en una reduccion de la dimensionalidad proyectando el fondo en un rango de longitudes de onda del espectro termico distinto de la proyeccion de las anomalias u objetivos sin firma espectral conocida. La metodologia propuesta ha sido probada con imagenes hiperespectrales reales de diferentes sensores y en diferentes escenarios o espacios, por lo tanto de diferente fondo espectral tambien, donde los resultados muestran los beneficios de la aproximacion en la deteccion de una gran variedad de objetos cuyas firmas espectrales tienen suficiente desviacion respecto del fondo. La tecnica resulta ser automatica en el sentido de que no hay necesidad de ajuste de parametros, dando resultados significativos en todos los casos. Incluso los objetos de tamano subpixel, que no pueden distinguirse a simple vista por el ojo humano en la imagen original, pueden ser detectados como anomalias. Ademas, se realiza una comparacion entre el enfoque propuesto, la popular tecnica RX y otros detectores tanto en su modalidad global como local. El metodo propuesto supera a los demas en determinados escenarios, demostrando su capacidad para reducir la proporcion de falsas alarmas. Los resultados del algoritmo automatico DAFT desarrollado, han demostrado la mejora en la definicion cualitativa de las anomalias espectrales que identifican a entidades diferentes en o bajo superficie, reemplazando para ello el modelo clasico de distribucion normal con un metodo robusto que contempla distintas alternativas desde el momento mismo de la adquisicion del dato hiperespectral. Para su consecucion ha sido necesario analizar la relacion entre parametros biofisicos, como la reflectancia y la emisividad de los materiales, y la distribucion espacial de entidades detectadas respecto de su entorno. Por ultimo, el algoritmo DAFT ha sido elegido como el mas adecuado para sensores que adquieren datos en el TIR, ya que presenta el mejor acuerdo con los datos de referencia, demostrando una gran eficacia computacional que facilita su implementacion en un sistema de cartografia que proyecte de forma automatica en un marco geografico de referencia las anomalias detectadas, lo que confirma un significativo avance hacia un sistema en lo que se denomina cartografia en tiempo real. The aim of this Thesis is to develop a specific methodology in order to be applied in automatic detection anomalies processes using hyperspectral data also called hyperspectral scenes, and to improve the classification processes. Several scenarios, areas and their relationship with surfaces and objects have been tested. The spectral characteristics of reflectance parameter and emissivity in the pattern recognition of urban materials in several hyperspectral scenes have also been tested. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) and MASTER (MODIS/ASTER Simulator) have been used in this research. It is assumed that there is not prior knowledge of the targets in anomaly detection. Thus, the pixels are automatically separated according to their spectral information, significantly differentiated with respect to a background, either globally for the full scene, or locally by the image segmentation. Several experiments on different scenarios have been designed, analyzing the behavior of the standard RX anomaly detector and different methods based on subspace, image projection and segmentation-based anomaly detection methods. Results and their consequences in unsupervised classification processes are discussed. Detection of spectral anomalies aims at extracting automatically pixels that show significant responses in relation of their surroundings. This Thesis deals with the unsupervised technique of target detection, also called anomaly detection. Since this technique assumes no prior knowledge about the target or the statistical characteristics of the data, the only available option is to look for objects that are differentiated from the background. Several methods have been developed in the last decades, allowing a better understanding of the relationships between the image dimensionality and the optimization of search procedures as well as the subpixel differentiation of the spectral mixture and its implications in anomalous responses. In other sense, image spectrometry has proven to be efficient in the characterization of materials, based on statistical methods using a specific reflection and absorption bands. Spectral configurations in the VNIR, SWIR and TIR have been successfully used for mapping materials in different urban scenarios. There has been an increasing interest in the use of high resolution data (both spatial and spectral) to detect small objects and to discriminate surfaces in areas with urban complexity. This has come to be known as target detection which can be either supervised or unsupervised. In supervised target detection, algorithms lean on prior knowledge, such as the spectral signature. The detection process for matching signatures is not straightforward due to the complications of converting data airborne sensor with material spectra in the ground. This could be further complicated by the large number of possible objects of interest, as well as uncertainty as to the reflectance or emissivity of these objects and surfaces. An important objective in this research is to establish relationships that allow linking spectral anomalies with what can be called informational anomalies and, therefore, identify information related to anomalous responses in some places rather than simply spotting differences from the background. The development in recent years of new hyperspectral sensors and techniques, widen the possibilities for applications in remote sensing of the Earth. Remote sensing systems measure and record electromagnetic disturbances that the surveyed objects induce in their surroundings, by means of different sensors mounted on airborne or space platforms. Map updating is important for management and decisions making people, because of the fast changes that usually happen in natural, urban and semi urban areas. It is necessary to optimize the methodology for obtaining the best from remote sensing techniques from hyperspectral data. The first problem with hyperspectral data is to reduce the dimensionality, keeping the maximum amount of information. Hyperspectral sensors augment considerably the amount of information, this allows us to obtain a better precision on the separation of material but at the same time it is necessary to calculate a bigger number of parameters, and the precision lowers with the increase in the number of bands. This is known as the Hughes effects (Bellman, 1957) . Hyperspectral imagery allows us to discriminate between a huge number of different materials however some land and urban covers are made up with similar material and respond similarly which produces confusion in the classification. The training and the algorithm used for mapping are also important for the final result and some properties of thermal spectrum for detecting land cover will be studied. In summary, this Thesis presents a new technique for anomaly detection in hyperspectral data called DAFT, as a PP's variant, based on dimensionality reduction by projecting anomalies or targets with unknown spectral signature to the background, in a range thermal spectrum wavelengths. The proposed methodology has been tested with hyperspectral images from different imaging spectrometers corresponding to several places or scenarios, therefore with different spectral background. The results show the benefits of the approach to the detection of a variety of targets whose spectral signatures have sufficient deviation in relation to the background. DAFT is an automated technique in the sense that there is not necessary to adjust parameters, providing significant results in all cases. Subpixel anomalies which cannot be distinguished by the human eye, on the original image, however can be detected as outliers due to the projection of the VNIR end members with a very strong thermal contrast. Furthermore, a comparison between the proposed approach and the well-known RX detector is performed at both modes, global and local. The proposed method outperforms the existents in particular scenarios, demonstrating its performance to reduce the probability of false alarms. The results of the automatic algorithm DAFT have demonstrated improvement in the qualitative definition of the spectral anomalies by replacing the classical model by the normal distribution with a robust method. For their achievement has been necessary to analyze the relationship between biophysical parameters such as reflectance and emissivity, and the spatial distribution of detected entities with respect to their environment, as for example some buried or semi-buried materials, or building covers of asbestos, cellular polycarbonate-PVC or metal composites. Finally, the DAFT method has been chosen as the most suitable for anomaly detection using imaging spectrometers that acquire them in the thermal infrared spectrum, since it presents the best results in comparison with the reference data, demonstrating great computational efficiency that facilitates its implementation in a mapping system towards, what is called, Real-Time Mapping.