2 resultados para exploratory spatial data analysis

em Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal


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This study aimed to provide an insight on the ecology of the bottlenose dolphin population in Madeira archipelago. To achieve this, population structure; group dynamics, site-fidelity, residency and movement patterns within and out of the study area; survival and abundance estimates and spatial and temporal distribution and habitat preferences related to physiographic parameters using data collected between 2001-2011, were investigated. Photo-identification data analysis revealed strong evidences that bottlenose dolphins seen in the archipelago of Madeira belong to an open population with regular recruitment of new animals to the area. This population exhibited a typical fission-fusion society, in which short-term acquaintances prevail, with only a few long-lasting associations. Photo-identification methods demonstrated that there is a large variability in residency pattern, with resident, transient and migrant individuals. Only a small number of dolphins were found to be resident (4.3%). Social network diagram as well as SLAR analysis supported the existence of a mixed population of residents, migrants and transients. Mark-recapture methods estimated a high survival rate, within the range of other long-lived cetacean species. The resident community is composed of app. 180 individuals. In addition, around 400 dolphins of different residency patterns were found to use the south area of Madeira Island. Spatial distribution indicated that bottlenose dolphins were regularly found in shallow and closer to shore areas, suggesting the existence of biological processes influenced by bathymetry. Moreover, temporal patterns revealed no strong seasonal fluctuation in the presence of bottlenose dolphins in Madeira archipelago waters. Bottlenose dolphins are listed under the Annex II of the EU habitats Directive that requires the designation of Special Areas of Conservation (SACs) for this species; as such, the knowledge gained through this work can be used by governmental authorities to the establishment and management of areas for the conservation of bottlenose dolphin in Madeira archipelago.

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Online geographic-databases have been growing increasingly as they have become a crucial source of information for both social networks and safety-critical systems. Since the quality of such applications is largely related to the richness and completeness of their data, it becomes imperative to develop adaptable and persistent storage systems, able to make use of several sources of information as well as enabling the fastest possible response from them. This work will create a shared and extensible geographic model, able to retrieve and store information from the major spatial sources available. A geographic-based system also has very high requirements in terms of scalability, computational power and domain complexity, causing several difficulties for a traditional relational database as the number of results increases. NoSQL systems provide valuable advantages for this scenario, in particular graph databases which are capable of modeling vast amounts of inter-connected data while providing a very substantial increase of performance for several spatial requests, such as finding shortestpath routes and performing relationship lookups with high concurrency. In this work, we will analyze the current state of geographic information systems and develop a unified geographic model, named GeoPlace Explorer (GE). GE is able to import and store spatial data from several online sources at a symbolic level in both a relational and a graph databases, where several stress tests were performed in order to find the advantages and disadvantages of each database paradigm.