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.

Adiabatic and local approximations for the kohn-sham potential in the hubbard model

We obtain the exact time-dependent Kohn-Sham potentials Vks for 1D Hubbard chains, driven by a d.c. external field, using the time-dependent electron density and current density obtained from exact many-body time-evolution. The exact Vxc is compared to the adiabatically-exact Vad-xc and the “instantaneous ground state” Vigs-xc. The effectiveness of these two approximations is analyzed. Approximations for the exchange-correlation potential Vxc and its gradient, based on the local density and on the local current density, are also considered and both physical quantities are observed to be far outside the reach of any possible local approximation. Insight into the respective roles of ground-state and excited-state correlation in the time-dependent system, as reflected in the potentials, is provided by the pair correlation function.

Seasonality and diel variation in blue whale D calls recorded in the Southern California Bight

Passive acoustic data have been collected using HARPs (High-frequency Acoustic Recording Packages) and were used to assess (1) the seasonality of blue whale D calls in the Southern California Bight, (2) their interannual abundance during 2007-2012 and (3) their diel variation. This goal has been achieved running the GPL (Generalized Power-Law) automated detector. (1) Blue whale D calls were detected in the Southern California Bight from May through November with a peak in July, even though few detections were from December to April as well. A key predictor for blue whale distribution and movement in the California Current region has been identified with zooplankton aggregations, paying a particular attention to those euphausiid species, such as E. pacifica and T. spinifera, which are blue whale favorite krill. The Southern California Bight experiences seasonal upwelling, resulting in an increase of productivity and prey availability. The summer and early fall have been marked as the most favorable periods. This supports the presence of blue whales in the area at that time, supposing these marine mammals exploit the region as a feeding ground. (2) As to the interannual abundance during 2007-2012, I found a large variability. I observed a great increase of vocalizations in 2007 and 2010, whereas a decrease was shown in the other years, which is well marked in 2009. It is my belief that these fluctuations in abundance of D calls detections through the deployed period are due to the alternation of El Nino and La Nina events, which occurred in those years. (3) The assessment of the daily timing of D calls production shows that D calls are more abundant during the day than during the night with a peak at 12:00 and 13:00. Assuming that D calling is associated with feeding, the daily pattern of D calls may be linked to the prey availability. E. pacifica and T. spinifera are among those species of krill which undertake daily vertical migrations, remaining at depth during the day and slowly coming up towards the surface at night. Because of some anatomical arrangements, these euphausiids are very sensitive to the light. Given that we believe D calls have a social function, I hypothesize that blue whales may recognize the hours at the highest solar incidence as the best moment of the day in terms of prey availability, exploiting this time window to advert their conspecifics.

Sea level trends in the Mediterranean from tide gauges and satellite altimetry

Sea level variation is one of the parameters directly related to climate change. Monitoring sea level rise is an important scientific issue since many populated areas of the world and megacities are located in low-lying regions. At present, sea level is measured by means of two techniques: the tide gauges and the satellite radar altimetry. Tide gauges measure sea-level relatively to a ground benchmark, hence, their measurements are directly affected by vertical ground motions. Satellite radar altimetry measures sea-level relative to a geocentric reference and are not affected by vertical land motions. In this study, the linear relative sea level trends of 35 tide gauge stations distributed across the Mediterranean Sea have been computed over the period 1993-2014. In order to extract the real sea-level variation, the vertical land motion has been estimated using the observations of available GPS stations and removed from the tide gauges records. These GPS-corrected trends have then been compared with satellite altimetry measurements over the same time interval (AVISO data set). A further comparison has been performed, over the period 1993-2013, using the CCI satellite altimetry data set which has been generated using an updated modeling. The absolute sea level trends obtained from satellite altimetry and GPS-corrected tide gauge data are mostly consistent, meaning that GPS data have provided reliable corrections for most of the sites. The trend values range between +2.5 and +4 mm/yr almost everywhere in the Mediterranean area, the largest trends were found in the Northern Adriatic Sea and in the Aegean. These results are in agreement with estimates of the global mean sea level rise over the last two decades. Where GPS data were not available, information on the vertical land motion deduced from the differences between absolute and relative trends are in agreement with the results of other studies.