Modelizzazione spazio-temporale delle dinamiche di uso del suolo ed analisi comparativa di differenti approcci predittivi. Uso integrato di SIG e telerilevamento nello studio dei processi di deforestazione nella regione La Joyanca in Peten, Guatemala

L’uso frequente dei modelli predittivi per l’analisi di sistemi complessi, naturali o artificiali, sta cambiando il tradizionale approccio alle problematiche ambientali e di rischio. Il continuo miglioramento delle capacità di elaborazione dei computer facilita l’utilizzo e la risoluzione di metodi numerici basati su una discretizzazione spazio-temporale che permette una modellizzazione predittiva di sistemi reali complessi, riproducendo l’evoluzione dei loro patterns spaziali ed calcolando il grado di precisione della simulazione. In questa tesi presentiamo una applicazione di differenti metodi predittivi (Geomatico, Reti Neurali, Land Cover Modeler e Dinamica EGO) in un’area test del Petén, Guatemala. Durante gli ultimi decenni questa regione, inclusa nella Riserva di Biosfera Maya, ha conosciuto una rapida crescita demografica ed un’incontrollata pressione sulle sue risorse naturali. L’area test puó essere suddivisa in sotto-regioni caratterizzate da differenti dinamiche di uso del suolo. Comprendere e quantificare queste differenze permette una migliore approssimazione del sistema reale; é inoltre necessario integrare tutti i parametri fisici e socio-economici, per una rappresentazione più completa della complessità dell’impatto antropico. Data l’assenza di informazioni dettagliate sull’area di studio, quasi tutti i dati sono stati ricavati dall’elaborazione di 11 immagini ETM+, TM e SPOT; abbiamo poi realizzato un’analisi multitemporale dei cambi uso del suolo passati e costruito l’input per alimentare i modelli predittivi. I dati del 1998 e 2000 sono stati usati per la fase di calibrazione per simulare i cambiamenti nella copertura terrestre del 2003, scelta come data di riferimento per la validazione dei risultati. Quest’ultima permette di evidenziare le qualità ed i limiti per ogni modello nelle differenti sub-regioni.

GÉOARCHÉOLOGIE DU VILLAGE: Variabilité des modes d’occupation de la fin du Néolithique à l’âge du Bronze en Italie et en France méridionale. Implications culturelles

Entre la fin du Néolithique et l’âge du Bronze, la présence d’habitats groupés de type village est un phénomène diffus, tant en Italie qu’en France méridionale. Néanmoins, la prise en compte de la variabilité des formes de la stratification des sites interroge. En quoi l’enregistrement sédimentaire des sols d’habitat permet-il d’appréhender la question de l’organisation villageoise et de sa variabilité entre la fin du Néolithique et l’âge du Bronze ? Quelle image cet enregistrement sédimentaire donne-t-il de l’organisation sociale et économique du village ? Afin d’aborder ces questions, nous avons choisi de mener une étude géoarchéologique sur des sites de formes différentes, issus de contextes chrono-culturels et environnementaux variés. La démarche, fondée sur l’emploi de la micromorphologie des sols en tant qu’outil analytique, vise à caractériser l’organisation spatio-temporelle des sols d’occupation à l’échelle du site, selon une approche spatiale des processus de formation de la stratification archéologique. L’élaboration d’un modèle, qui repose sur une classification des micro-faciès sédimentaires selon le système d’activité, et son application à des sites-laboratoires permettent de qualifier les techniques de construction en terre, l’usage du sol et les dynamiques d’occupation propres à chaque site, dans le but de déterminer les comportements socio-économiques et les spécificités du mode de vie villageois enregistrées par les sols. Cette approche permet d’évaluer les constantes et les variables qui qualifient les différents types d’occupation. Le sol, conçu comme matérialité de l’espace villageois, devient ainsi un témoignage direct de la variabilité culturelle et des différentes formes d’organisation des communautés de la fin du Néolithique et de l’âge du Bronze.

Spatio-temporal models of the functional architecture of the visual cortex

In this work I tried to explore many aspects of cognitive visual science, each one based on different academic fields, proposing mathematical models capable to reproduce both neuro-physiological and phenomenological results that were described in the recent literature. The structure of my thesis is mainly composed of three chapters, corresponding to the three main areas of research on which I focused my work. The results of each work put the basis for the following, and their ensemble form an homogeneous and large-scale survey on the spatio-temporal properties of the architecture of the visual cortex of mammals.

A Bayesian changepoint analysis on spatio-temporal point processes

Changepoint analysis is a well established area of statistical research, but in the context of spatio-temporal point processes it is as yet relatively unexplored. Some substantial differences with regard to standard changepoint analysis have to be taken into account: firstly, at every time point the datum is an irregular pattern of points; secondly, in real situations issues of spatial dependence between points and temporal dependence within time segments raise. Our motivating example consists of data concerning the monitoring and recovery of radioactive particles from Sandside beach, North of Scotland; there have been two major changes in the equipment used to detect the particles, representing known potential changepoints in the number of retrieved particles. In addition, offshore particle retrieval campaigns are believed may reduce the particle intensity onshore with an unknown temporal lag; in this latter case, the problem concerns multiple unknown changepoints. We therefore propose a Bayesian approach for detecting multiple changepoints in the intensity function of a spatio-temporal point process, allowing for spatial and temporal dependence within segments. We use Log-Gaussian Cox Processes, a very flexible class of models suitable for environmental applications that can be implemented using integrated nested Laplace approximation (INLA), a computationally efficient alternative to Monte Carlo Markov Chain methods for approximating the posterior distribution of the parameters. Once the posterior curve is obtained, we propose a few methods for detecting significant change points. We present a simulation study, which consists in generating spatio-temporal point pattern series under several scenarios; the performance of the methods is assessed in terms of type I and II errors, detected changepoint locations and accuracy of the segment intensity estimates. We finally apply the above methods to the motivating dataset and find good and sensible results about the presence and quality of changes in the process.

Assessment of gait spatio-temporal parameters in neurological disorders using wearable inertial sensors

Movement analysis carried out in laboratory settings is a powerful, but costly solution since it requires dedicated instrumentation, space and personnel. Recently, new technologies such as the magnetic and inertial measurement units (MIMU) are becoming widely accepted as tools for the assessment of human motion in clinical and research settings. They are relatively easy-to-use and potentially suitable for estimating gait kinematic features, including spatio-temporal parameters. The objective of this thesis regards the development and testing in clinical contexts of robust MIMUs based methods for assessing gait spatio-temporal parameters applicable across a number of different pathological gait patterns. First, considering the need of a solution the least obtrusive as possible, the validity of the single unit based approach was explored. A comparative evaluation of the performance of various methods reported in the literature for estimating gait temporal parameters using a single unit attached to the trunk first in normal gait and then in different pathological gait conditions was performed. Then, the second part of the research headed towards the development of new methods for estimating gait spatio-temporal parameters using shank worn MIMUs on different pathological subjects groups. In addition to the conventional gait parameters, new methods for estimating the changes of the direction of progression were explored. Finally, a new hardware solution and relevant methodology for estimating inter-feet distance during walking was proposed. Results of the technical validation of the proposed methods at different walking speeds and along different paths against a gold standard were reported and showed that the use of two MIMUs attached to the lower limbs associated with a robust method guarantee a much higher accuracy in determining gait spatio-temporal parameters. In conclusion, the proposed methods could be reliably applied to various abnormal gaits obtaining in some cases a comparable level of accuracy with respect to normal gait.

Analysis of heat-related phenomena and their interactions at different spatio-temporal scales

This thesis analyzes the impact of heat extremes in urban and rural environments, considering processes related to severely high temperatures and unusual dryness. The first part deals with the influence of large-scale heatwave events on the local-scale urban heat island (UHI) effect. The temperatures recorded over a 20-year summer period by meteorological stations in 37 European cities are examined to evaluate the variations of UHI during heatwaves with respect to non-heatwave days. A statistical analysis reveals a negligible impact of large-scale extreme temperatures on the local daytime urban climate, while a notable exacerbation of UHI effect at night. A comparison with the UrbClim model outputs confirms the UHI strengthening during heatwave episodes, with an intensity independent of the climate zone. The investigation of the relationship between large-scale temperature anomalies and UHI highlights a smooth and continuous dependence, but with a strong variability. The lack of a threshold behavior in this relationship suggests that large-scale temperature variability can affect the local-scale UHI even in different conditions than during extreme events. The second part examines the transition from meteorological to agricultural drought, being the first stage of the drought propagation process. A multi-year reanalysis dataset involving numerous drought events over the Iberian Peninsula is considered. The behavior of different non-parametric standardized drought indices in drought detection is evaluated. A statistical approach based on run theory is employed, analyzing the main characteristics of drought propagation. The propagation from meteorological to agricultural drought events is found to develop in about 1-2 months. The duration of agricultural drought appears shorter than that of meteorological drought, but the onset is delayed. The propagation probability increases with the severity of the originating meteorological drought. A new combined agricultural drought index is developed to be a useful tool for balancing the characteristics of other adopted indices.

Digital 3D reconstruction as a research environment in art and architecture history: uncertainty classification and visualisation

The dissertation addresses the still not solved challenges concerned with the source-based digital 3D reconstruction, visualisation and documentation in the domain of archaeology, art and architecture history. The emerging BIM methodology and the exchange data format IFC are changing the way of collaboration, visualisation and documentation in the planning, construction and facility management process. The introduction and development of the Semantic Web (Web 3.0), spreading the idea of structured, formalised and linked data, offers semantically enriched human- and machine-readable data. In contrast to civil engineering and cultural heritage, academic object-oriented disciplines, like archaeology, art and architecture history, are acting as outside spectators. Since the 1990s, it has been argued that a 3D model is not likely to be considered a scientific reconstruction unless it is grounded on accurate documentation and visualisation. However, these standards are still missing and the validation of the outcomes is not fulfilled. Meanwhile, the digital research data remain ephemeral and continue to fill the growing digital cemeteries. This study focuses, therefore, on the evaluation of the source-based digital 3D reconstructions and, especially, on uncertainty assessment in the case of hypothetical reconstructions of destroyed or never built artefacts according to scientific principles, making the models shareable and reusable by a potentially wide audience. The work initially focuses on terminology and on the definition of a workflow especially related to the classification and visualisation of uncertainty. The workflow is then applied to specific cases of 3D models uploaded to the DFG repository of the AI Mainz. In this way, the available methods of documenting, visualising and communicating uncertainty are analysed. In the end, this process will lead to a validation or a correction of the workflow and the initial assumptions, but also (dealing with different hypotheses) to a better definition of the levels of uncertainty.