GIS and remote sensing for post-dictive analysis of archaeological features. A case study from the Etnean region (Sicily)

This article illustrates the potential of multispectral satellite data for archaeological scope in the volcanic area of Mount Etna (Sicily, Italy). In particular, by adopting a post-dictive approach, GIS and FOSS technology was used to analyse different indices derived from World-View-2 multispectral data. The selected examples (two circular buildings and a wall-structure) illustrate successes and challenges of our method. The results indicate that NIR-1 and RED-EDGE are undoubtedly the most useful, while NDVI and SRI are the best performing indices

Multi-resolution analysis techniques and nonlinear PCA for hybrid pansharpening applications

International audienceHyperspectral images have a higher spectral resolution (i.e., a larger number of bands covering the electromagnetic spectrum), but a lower spatial resolution with respect to multispectral or panchromatic acquisitions. For increasing the capabilities of the data in terms of utilization and interpretation, hyperspectral images having both high spectral and spatial resolution are desired. This can be achieved by combining the hyperspectral image with a high spatial resolution panchromatic image. These techniques are generally known as pansharpening and can be divided into component substitution (CS) and multi-resolution analysis (MRA) based methods. In general, the CS methods result in fused images having high spatial quality but the fused images suffer from spectral distortions. On the other hand, images obtained using MRA techniques are not as sharp as CS methods but they are spectrally consistent. Both substitution and filtering approaches are considered adequate when applied to multispectral and PAN images, but have many drawbacks when the low-resolution image is a hyperspectral image. Thus, one of the main challenges in hyperspectral pansharpening is to improve the spatial resolution while preserving as much as possible of the original spectral information. An effective solution to these problems has been found in the use of hybrid approaches, combining the better spatial information of CS and the more accurate spectral information of MRA techniques. In general, in a hybrid approach a CS technique is used to project the original data into a low dimensionality space. Thus, the PAN image is fused with one or more features by means of MRA approach. Finally the inverse projection is used to obtain the enhanced image in the original data space. These methods, permit to effectively enhance the spatial resolution of the hyperspectral image without relevant spectral distortions and on the same time to reduce the computational load of the entire process. In particular, in this paper we focus our attention on the use of Non-linear Principal Component Analysis (NLPCA) for the projection of the image into a low dimensionality feature space. However, if on one hand the NLPCA has been proved to better represent the intrinsic information of hyperspectral images in the feature space, on the other hand, an analysis of the impact of different fusion techniques applied to the nonlinear principal components in order to define the optimal framework for the hybrid pansharpening has not been carried out yet. More in particular, in this paper we analyze the overall impact of several widely used MRA pansharpening algorithms applied in the nonlinear feature space. The results obtained on both synthetic and real data demonstrate that, an accurate selection of the pansharpening method can lead to an effective improvement of the enhanced hyperspectral image in terms of spectral quality and spatial consistency, as well as a strong reduction in the computational time

DETECTION OF ANOMALIES PRODUCED BY BURIED ARCHAEOLOGICAL STRUCTURES USING NONLINEAR PRINCIPAL COMPONENT ANALYSIS APPLIED TO AIRBORNE HYPERSPECTRAL IMAGE

In this paper, airborne hyperspectral data have been exploited by means of Nonlinear Principal Component Analysis (NLPCA) to test their effectiveness as a tool for archaeological prospection, evaluating their potential for detecting anomalies related to buried archaeological structures. In the literature, the NLPCA was used to decorrelate the information related to a hyperspectral image. The resulting nonlinear principal components (NLPCs) contain information related to different land cover types and biophysical properties, such as vegetation coverage or soil wetness. From this point of view, NLPCA applied to airborne hyperspectral data was exploited to test their effectiveness and capability in highlighting the anomalies related to buried archaeological structures. Each component obtained from the NLPCA has been interpreted in order to assess any tonal anomalies. As a matter of a fact, since every analyzed component exhibited anomalies different in terms of size and intensity, the Separability Index (SI) was applied for measuring the tonal difference of the anomalies with respect to the surrounding area. SI has been evaluated for determining the potential of anomalies detection in each component. The airborne Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) images, collected over the archaeological Park of Selinunte, were analyzed for this purpose. In this area, the presence of remains, not yet excavated, was reported by archaeologists. A previous analysis of this image, carried out to highlight the buried structures, appear to match the archaeological prospection. The results obtained by the present work demonstrate that the use of the NLPCA technique, compared to previous approaches emphasizes the abilit

Seeing the Big Picture: System Architecture Trends in Endoscopy and LED-Based hyperspectral Subsystem Intergration

Early-stage colorectal lesions remain difficult to detect. Early development of neoplasia tends to be small (less than 10 mm) and flat and difficult to distinguish from surrounding mucosa. Additionally, optical diagnosis of neoplasia as benign or malignant is problematic. Low rates of detection of these lesions allow for continued growth in the colorectum and increased risk of cancer formation. Therefore, it is crucial to detect neoplasia and other non-neoplastic lesions to determine risk and guide future treatment. Technology for detection needs to enhance contrast of subtle tissue differences in the colorectum and track multiple biomarkers simultaneously. This work implements one such technology with the potential to achieve the desired multi-contrast outcome for endoscopic screenings: hyperspectral imaging. Traditional endoscopic imaging uses a white light source and a RGB detector to visualize the colorectum using reflected light. Hyperspectral imaging (HSI) acquires an image over a range of individual wavelength bands to create an image hypercube with a wavelength dimension much deeper and more sensitive than that of an RGB image. A hypercube can consist of reflectance or fluorescence (or both) spectra depending on the filtering optics involved. Prior studies using HSI in endoscopy have normally involved ex vivo tissues or xiv optics that created a trade-off between spatial resolution, spectral discrimination and temporal sampling. This dissertation describes the systems design of an alternative HSI endoscopic imaging technology that can provide high spatial resolution, high spectral distinction and video-rate acquisition in vivo. The hyperspectral endoscopic system consists of a novel spectral illumination source for image acquisition dependent on the fluorescence excitation (instead of emission). Therefore, this work represents a novel contribution to the field of endoscopy in combining excitation-scanning hyperspectral imaging and endoscopy. This dissertation describes: 1) systems architecture of the endoscopic system in review of previous iterations and theoretical next-generation options, 2) feasibility testing of a LED-based hyperspectral endoscope system and 3) another LED-based spectral illuminator on a microscope platform to test multi-spectral contrast imaging. The results of the architecture point towards an endoscopic system with more complex imaging and increased computational capabilities. The hyperspectral endoscope platform proved feasibility of a LED-based spectral light source with a multi-furcated solid light guide. Another LED-based design was tested successfully on a microscope platform with a dual mirror array similar to telescope designs. Both feasibility tests emphasized optimization of coupling optics and combining multiple diffuse light sources to a common output. These results should lead to enhanced imagery for endoscopic tissue discrimination and future optical diagnosis for routine colonoscopy

Analysis of biomakers for the biogenic characterization and farming practices identification of prehistoric organic sediments from rock-shelters and caves used as livestock-pens

xvii, 216, xix p.En la presente Tesis Doctoral se ha incidido especialmente en establecer la naturaleza de los animales estabulados a lo largo del tiempo, en abrigos de ontaña de la Sierra de Cantabria y la Sierra de Atapuerca, certificados por excacaciones arqueológicas realizadas entre los años 1964 y 1997. Se han desarrollado para ello nuevos métodos analíticos para la detección de biomarcadores específicos de cada especie animal, se ha datado el origen de las muestras mediante las relaciones entre biomarcadores y finalmente se ha pretendido agrupar todos los datos obtenidos para dar respuestas a las diferentes preguntas que surgen desde la Arqueología: cuál es la naturaleza de la cabaña estabulada, en qué épocas históricas se ha producido esa estabulación y cuáles son las actividades y costumbres pastoriles

Remote Sensing and Geosciences for Archaeology

This book collects more than 20 papers, written by renowned experts and scientists from across the globe, that showcase the state-of-the-art and forefront research in archaeological remote sensing and the use of geoscientific techniques to investigate archaeological records and cultural heritage. Very high resolution satellite images from optical and radar space-borne sensors, airborne multi-spectral images, ground penetrating radar, terrestrial laser scanning, 3D modelling, Geographyc Information Systems (GIS) are among the techniques used in the archaeological studies published in this book. The reader can learn how to use these instruments and sensors, also in combination, to investigate cultural landscapes, discover new sites, reconstruct paleo-landscapes, augment the knowledge of monuments, and assess the condition of heritage at risk. Case studies scattered across Europe, Asia and America are presented: from the World UNESCO World Heritage Site of Lines and Geoglyphs of Nasca and Palpa to heritage under threat in the Middle East and North Africa, from coastal heritage in the intertidal flats of the German North Sea to Early and Neolithic settlements in Thessaly. Beginners will learn robust research methodologies and take inspiration; mature scholars will for sure derive inputs for new research and applications

LIDAR based semi-automatic pattern recognition within an archaeological landscape

LIDAR-Daten bieten einen neuartigen Ansatz zur Lokalisierung und Überwachung des kulturellen Erbes in der Landschaft, insbesondere in schwierig zu erreichenden Gebieten, wie im Wald, im unwegsamen Gelände oder in sehr abgelegenen Gebieten. Die manuelle Lokalisation und Kartierung von archäologischen Informationen einer Kulturlandschaft ist in der herkömmlichen Herangehensweise eine sehr zeitaufwändige Aufgabe des Fundstellenmanagements (Cultural Heritage Management). Um die Möglichkeiten in der Erkennung und bei der Verwaltung des kulturellem Erbes zu verbessern und zu ergänzen, können computergestützte Verfahren einige neue Lösungsansätze bieten, die darüber hinaus sogar die Identifizierung von für das menschliche Auge bei visueller Sichtung nicht erkennbaren Details ermöglichen. Aus archäologischer Sicht ist die vorliegende Dissertation dadurch motiviert, dass sie LIDAR-Geländemodelle mit archäologischen Befunden durch automatisierte und semiautomatisierte Methoden zur Identifizierung weiterer archäologischer Muster zu Bodendenkmalen als digitale „LIDAR-Landschaft“ bewertet. Dabei wird auf möglichst einfache und freie verfügbare algorithmische Ansätze (Open Source) aus der Bildmustererkennung und Computer Vision zur Segmentierung und Klassifizierung der LIDAR-Landschaften zur großflächigen Erkennung archäologischer Denkmäler zurückgegriffen. Die Dissertation gibt dabei einen umfassenden Überblick über die archäologische Nutzung und das Potential von LIDAR-Daten und definiert anhand qualitativer und quantitativer Ansätze den Entwicklungsstand der semiautomatisierten Erkennung archäologischer Strukturen im Rahmen archäologischer Prospektion und Fernerkundungen. Darüber hinaus erläutert sie Best Practice-Beispiele und den einhergehenden aktuellen Forschungsstand. Und sie veranschaulicht die Qualität der Erkennung von Bodendenkmälern durch die semiautomatisierte Segmentierung und Klassifizierung visualisierter LIDAR-Daten. Letztlich identifiziert sie das Feld für weitere Anwendungen, wobei durch eigene, algorithmische Template Matching-Verfahren großflächige Untersuchungen zum kulturellen Erbe ermöglicht werden. Resümierend vergleicht sie die analoge und computergestützte Bildmustererkennung zu Bodendenkmalen, und diskutiert abschließend das weitere Potential LIDAR-basierter Mustererkennung in archäologischen Kulturlandschaften