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.

Research on the vocal culture of Orcinus orca in the Loro Parque, Tenerife: a pilot study

This research is focussed on the study of Orcinus orca's communication system. The analysis of vocalizations emitted by marine mammals has started in the '80s and most studies have been carried out in the wild. In this regard the most studied animal has been common dolphin (Tursiops truncatus) as the numerous presence of captive individuals worldwide made researches easier to be carried out. Studies about Orcinus orca's vocalizations have mainly been carried out in the wild (most in British Columbia) because its maintenance in a controlled environment results to be very difficult, only 17 among parks and oceanaria worldwide have some Orcinus orca (45 overall among which 64% born in captivity). These researches showed that Orcinus orca emit three main different types of sounds, classified as: whistles, clicks and calls. Besides, it was discovered that different groups (pods) produce sounds belonging only to the relevant pod (dialects). It is rare to find two pods sharing some calls. The two pods usually live in adjacent areas and can form a clan. This study was carried out in a controlled environment in the Orca ocean structure (Loro Parque, Tenerife, Spain) where, at the moment (March 2012) 6 individuals are hosted. Here it was developed an automatic sound recording system. Thanks to the use of suitable mathematical algorithms that allow to isolate only "interesting" sound events that differ from the "background noise", it was possible to create a database. The visualization of the sound events collected in the database is carried out with the use of a software. By looking at this output and at the observation register we could match the animal to the sound produced. Three situations were detected and studied: 1) Chosen alone: the animal chooses to go to the recording pool but it is free to move to another pool with other individuals. 2) Put alone: the animal is put alone in the recording pool. 3) With other orcas: more animals are together in the recording pool. The statistic analysis show that animals emit more vocalizations when they are in the situation "Chosen alone". The research will continue in order to observe eventual differences in the individual repertoire of each Orcinus orca.