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.

Extracting evolutionary information from the spectral decomposition of early-type galaxies.

Holding the major share of stellar mass in galaxies and being also old and passively evolving, early-type galaxies (ETGs) are the primary probes in investigating these various evolution scenarios, as well as being useful means to provide insights on cosmological parameters. In this thesis work I focused specifically on ETGs and on their capability in constraining galaxy formation and evolution; in particular, the principal aims were to derive some of the ETGs evolutionary parameters, such as age, metallicity and star formation history (SFH) and to study their age-redshift and mass-age relations. In order to infer galaxy physical parameters, I used the public code STARLIGHT: this program provides a best fit to the observed spectrum from a combination of many theoretical models defined in user-made libraries. the comparison between the output and input light-weighted ages shows a good agreement starting from SNRs of ∼ 10, with a bias of ∼ 2.2% and a dispersion 3%. Furthermore, also metallicities and SFHs are well reproduced. In the second part of the thesis I performed an analysis on real data, starting from Sloan Digital Sky Survey (SDSS) spectra. I found that galaxies get older with cosmic time and with increasing mass (for a fixed redshift bin); absolute light-weighted ages, instead, result independent from the fitting parameters or the synthetic models used. Metallicities, instead, are very similar from each other and clearly consistent with the ones derived from the Lick indices. The predicted SFH indicates the presence of a double burst of star formation. Velocity dispersions and extinctiona are also well constrained, following the expected behaviours. As a further step, I also fitted single SDSS spectra (with SNR∼ 20), to verify that stacked spectra gave the same results without introducing any bias: this is an important check, if one wants to apply the method at higher z, where stacked spectra are necessary to increase the SNR. Our upcoming aim is to adopt this approach also on galaxy spectra obtained from higher redshift Surveys, such as BOSS (z ∼ 0.5), zCOSMOS (z 1), K20 (z ∼ 1), GMASS (z ∼ 1.5) and, eventually, Euclid (z 2). Indeed, I am currently carrying on a preliminary study to estabilish the applicability of the method to lower resolution, as well as higher redshift (z 2) spectra, just like the Euclid ones.

Searching for outflows signatures in sdss spectra of x-ray selected, obscured agn in the cosmos field

Partendo dal campione di AGN presente nella survey di XMM-COSMOS, abbiamo cercato la sua controparte ottica nel database DR10 della Sloan Digital Sky Survey (SDSS), ed il match ha portato ad una selezione di 200 oggetti, tra cui stelle, galassie e quasar. A partire da questo campione, abbiamo selezionato tutti gli oggetti con un redshift z<0.86 per limitare l’analisi agli AGN di tipo 2, quindi siamo giunti alla selezione finale di un campione di 30 sorgenti. L’analisi spettrale è stata fatta tramite il task SPECFIT, presente in IRAF. Abbiamo creato due tipi di modelli: nel primo abbiamo considerato un’unica componente per ogni riga di emissione, nel secondo invece è stata introdotta un’ulteriore com- ponente limitando la FWHM della prima ad un valore inferiore a 500 km\s. Le righe di emissione di cui abbiamo creato un modello sono le seguenti: Hβ, [NII]λλ 6548,6581, Hα, [SII]λλ 6716,6731 e [OIII]λλ 4959,5007. Nei modelli costruiti abbiamo tenuto conto della fisica atomica per quel che riguarda i rapporti dei flussi teorici dei doppietti dell’azoto e dell’ossigeno, fissandoli a 1:3 per entrambi; nel caso del modello ad una componente abbiamo fissato le FWHM delle righe di emissione; mentre nel caso a due componenti abbiamo fissato le FWHM delle componenti strette e larghe, separatamente. Tenendo conto del chi-quadro ottenuto da ogni fit e dei residui, è stato possibile scegliere tra i due modelli per ogni sorgente. Considerato che la nostra attenzione è focalizzata sulla cinematica dell’ossigeno, abbiamo preso in considerazione solo le sorgenti i cui spettri mostravano la riga suddetta, cioè 25 oggetti. Su questa riga è stata fatta un’analisi non parametrica in modo da utilizzare il metodo proposto da Harrison et al. (2014) per caratterizzare il profilo di riga. Sono state determinate quantità utili come il 2 e il 98 percentili, corrispondenti alle velocità massime proiettate del flusso di materia, e l’ampiezza di riga contenente l’80% dell’emissione. Per indagare sull’eventuale ruolo che ha l’AGN nel guidare questi flussi di materia verso l’esterno, abbiamo calcolato la massa del gas ionizzato presente nel flusso e il tasso di energia cinetica, tenendo conto solo delle componenti larghe della riga di [OIII] λ5007. Per la caratterizzazione energetica abbiamo considerato l’approccio di Cano-Diaz et al (2012) e di Heckman (1990) in modo da poter ottenere un limite inferiore e superiore della potenza cinetica, adottando una media geometrica tra questi due come valore indicativo dell’energetica coinvolta. Confrontando la potenza del flusso di gas con la luminosità bolometrica dell’AGN, si è trovato che l’energia cinetica del flusso di gas è circa lo 0.3-30% della luminosità dell’AGN, consistente con i modelli che considerano l’AGN come principale responsabile nel guidare questi flussi di gas.