Jorge Rocha

Collapsing rotating shells in Myers-Perry-AdS(5) spacetime: A perturbative approach

We study gravitational perturbations sourced by a rotating test shell collapsing into five-dimensional Myers-Perry black holes in anti-de Sitter (AdS). Our attention is restricted to the case in which the two possible angular momenta of the geometry are set equal. In this situation the background is cohomogeneity-1, which amounts to a crucial technical simplification. It is found that the linearized Einstein equations are consistent only when the test shell is corotating with the spacetime. However, it is argued that this is a consequence of the matter on the shell being described by dust or, more precisely, noninteracting test particles. We compute the mass and angular momenta of the perturbed spacetime using a counterterm subtraction method, for which we provide an explicit formula that has not appeared previously in the literature. The results are in agreement with the expected expressions for energy and angular momenta of geodesic particles in AdS

Where to vacation? An agent-based approach to modelling tourist decision-making process

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Mapping risk of Malaria transmission in Mainland Portugal using a mathematical modelling approach

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Geodesic motion in equal angular momenta Myers-Perry-AdS spacetimes

Agent-based models (ABMs) are becoming more relevant in social simulation due to the potential to model complex phenomena that emerge from individual interactions. In tourism research, complexity is a subject of growing interest and researchers start to analyse the tourism system as a complex phenomenon. However, there is little application of ABMs as a tool to explore and predict tourism patterns. The purpose of the paper is to develop an ABM that increases knowledge in tourism research by (i) considering the complexity of tourism phenomenon, (ii) providing tools to explore the complex relations between system components and (iii) giving insights on the functioning of the system and the tourist decision-making process. A theoretical ABM is developed to improve knowledge on tourist decision-making in the selection of a destination to vacation. Tourists’ behaviour, such as individual motivation, and social network influence in the vacation decision-making process are hereby discussed.

A Hybrid CA-ANN-Fuzzy Model for Simulating Coastal Changing Patterns

Malaria is currently one of the world´s major health problems. About a half-million deaths are recorded every year. In Portugal, malaria cases were significantly high until the end of the 1950s but the disease was considered eliminated in 1973. In the past few years, endemic malaria cases have been recorded in some European countries. With the increasing human mobility from countries with endemic malaria to Portugal, there is concern about the resurgence of this disease in the country. Here, we model and map the risk of malaria transmission for mainland Portugal, considering 3 different scenarios of existing imported infections. This risk assessment resulted from entomological studies on An. atroparvus, the only known mosquito capable of transmitting malaria in the study area. We used the malariogenic potential (determined by receptivity, infectivity and vulnerability) applied over geospatial data sets to estimate spatial variation in malaria risk. The results suggest that the risk exists, and the hotspots are concentrated in the northeast region of the country and in the upper and lower Alentejo regions.

Integration of census data, remote sensing, and GIS techniques for land-use and cover classification

nd that the ISCO dives below the ergosurface for black holes rotating close to extremality and merges with the event horizon exactly at extremality, in analogy with the fourdimensional Kerr case. For suciently massive black holes in AdS there exists a spin parameter range in which the background spacetime is stable against super-radiance and the ISCO lies inside the ergoregion. Our results for massless geodesics show that there are no stable circular null orbits outside the horizon, but there exist such orbits inside the horizon, as well as around overextremal spacetimes, i.e., naked singularities. We also discuss how these orbits deform from the static to the rotating case.

Integrating demographic GIS and multisensor remote sensing data in urban land use/cover maps assembly

Shoreline erosion is a problem that causes major concerns to coastal cities worldwide. About 70% of the world’s sandy beaches retreated at a rate of 0.5–1.0 m.year−1. Therefore, the protection against beach loss and appropriate land management along the shoreline are critical issues that need to be addressed. The modelling and simulation of dynamic and complex systems, such as coastal areas, are important for the definition of an innovative planning and management strategy. To explore sandy beaches threatened by shoreline retreat, this works aims to develop a geosimulation hybrid model. The geosimulation (geocomputation) is an emergent field of analysis embracing heuristic search, artificial neural networks and cellular automata, among others. In this chapter we present a method to simulate both the coast line and the land use/cover evolution in a developed costal area reality, by coupling cellular automata (CA) and multi-layer perceptron (MLP) artificial neural network (ANN) with fuzzy set theory (CA–ANN-Fuzzy) in a GIS environment. Such alterations simulation solely by means of cellular automata isn’t suitable, because these models, in its more conventional structure, comprise limitations in the space parameters and transition rules. In this work a neural network is used to calibrate the importance degree that each prediction variable (probability) has in the geographic constraints (weights), i.e. considers spatial and temporal nonlinearities of the driving forces underlying the urban growth processes, while fuzzy set theory captures the uncertainty associated with transition rules. The proposed method predict high shoreline drawbacks in only 14 years, mainly at North (40 meters) and West (20 meters). The model has an overall accuracy of 86% (14% of error in 60 years).

Spatially Explicit Models in Local Dynamics Analysis: The Potential Natural Vegetation (PNV) as a Tool for Beach and Coastal Management

The main purpose of the research presented in this paper is the development and validation, through the application to a case study, of an efficient form of satellite image classification that integrates ancillary information (Census data; the Municipal Mater Plan; the Road Network) and remote sensing data in a Geographic Information System. The developed procedure follows a layered classification approach, being composed by three main stages: 1) Pre- classification stratification; 2) Application of Bayesian and Maximum-likelihood classifiers; 3) Post-classification sorting. Common approaches incorporate the ancillary data before, during or after classification. In the proposes method, all the steps take the auxiliary information into account. The proposed method achieves, globally, much better classification results than the classical, one layer, Minimum Distance and Maximum-likelihood classifiers. Also, it greatly improves the accuracy of those classes where the classification process uses the ancillary data.

Remote Sensing Data and Image Classification Algorithms in the Identification of Beach Patterns

The main purpose of this research consists in the development and validation, through the application to a case study, of an efficient form of satellite image classification, using the most recent scientific and technological developments that have been made in the fields of remote sensing, geographical information systems and statistics in general. These methods should allow the development of applications for environmental planning and land management. Both the test and validation areas presented in this study belong to the Lisbon Metropolitan Area (LMA), selected as a case study due to its large dynamics and constant mutation.

Assessment of Potential Impacts in Tourism of the Increase in the Average Sea Level

The concept of Potential Natural Vegetation (PNV) and its mapping have become extremely important within the scope of habitat restoration in almost every European country. The aim of this study is to predict the PNV in the sites of Natura 2000 Network ‘Sado Estuary’ and ‘Comporta-Gale’ based on the vegetation series and the main environmental variables. The modelling approach is based on the distribution of communities referred to as classification then modelling.