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Abstract(s)
O Golfo da Guiné é uma região de significativa relevância internacional
pelo elevado potencial geoestratégico que apresenta. Dispõe de grandes reservas de
petróleo e gás natural, de uma privilegiada localização e acessibilidade marítima,
bem como de um grande leque de recursos naturais.
A região caracteriza-se por um clima de instabilidade política, social e económica, condições ideais para o surgimento e proliferação de ameaças à segurança
marítima, destacando-se a Pirataria Marítima pela crescente relevância e impacto
nos últimos anos. Desde 2018, esta região destaca-se por ter o maior número de
ataques no mundo, resultando no aumento da insegurança e instabilidade numa das
principais rotas do comércio marítimo mundial.
O presente trabalho tem como objetivo principal a identificação de padrões,
tendências e situações de maior risco de ocorrência de um ataque de Pirataria Marítima. Para esse efeito, recorreu-se aos dados disponibilizados pela International
Maritime Organization e pela International Maritime Bureau, relativos ao período
entre 2010 e 2021 e foi desenvolvido um modelo geoespacial dos diferentes indicadores de risco para a ocorrência de um ataque, que dispõe de diferentes camadas e
permite uma análise espácio-temporal dos diferentes indicadores, apurando em que
medida é que os esforços internacionais e regionais têm tido um impacto positivo no
combate a este fenómeno.
Para complementar este estudo, foi realizada uma análise estatística dos
dados e construído um modelo de Redes Bayesianas com o objetivo de prever o
nível de ameaça dadas as condições e contexto no momento do ataque. A análise
realizada permitiu a identificação de padrões entre os diferentes ataques e a previsão
efetuada através do modelo de classificação de Redes Bayesianas pode ser utilizada
não só para prever o nível de ameaça, bem como para identificar registos históricos
classificados com um nível inferior ao potencial que este representava.
The Gulf of Guinea is a region of significant international relevance due to its high geostrategic potential. It has large reserves of oil and natural gas, a privileged location and maritime accessibility, as well as a wide range of natural resources. The region is characterized by a climate of political, social and economic instability, ideal conditions for the emergence and proliferation of threats to maritime security, highlighting Maritime Piracy for its growing relevance and impact in recent years. Since 2018, this region has stood out for having the highest number of attacks in the world, resulting in increased insecurity and instability on one of the main routes of world maritime trade. The present work has as main objective the identification of patterns, trends and situations of greater risk of occurrence of a Maritime Piracy attack. For this purpose, it was used data provided by the International Maritime Organization and the International Maritime Bureau, for the period between 2010 and 2021, and was developed a geospatial model of the different risk indicators for the occurrence of an attack, which has different layers and allows a spatio-temporal analysis of the different indicators, ascertaining the extent to which international and regional efforts have had a positive impact on combating this phenomenon. To complement this study, a statistical analysis of the data and a model of Bayesian Networks was built in order to predict the level of threat given the conditions and context at the time of the attack. The analysis carried out, allowed the identification of patterns between the different attacks and the prediction made through the Bayesian Networks classification model can be used not only to predict the level of threat but also to identify historical records classified with a level lower than the potential that this represented.
The Gulf of Guinea is a region of significant international relevance due to its high geostrategic potential. It has large reserves of oil and natural gas, a privileged location and maritime accessibility, as well as a wide range of natural resources. The region is characterized by a climate of political, social and economic instability, ideal conditions for the emergence and proliferation of threats to maritime security, highlighting Maritime Piracy for its growing relevance and impact in recent years. Since 2018, this region has stood out for having the highest number of attacks in the world, resulting in increased insecurity and instability on one of the main routes of world maritime trade. The present work has as main objective the identification of patterns, trends and situations of greater risk of occurrence of a Maritime Piracy attack. For this purpose, it was used data provided by the International Maritime Organization and the International Maritime Bureau, for the period between 2010 and 2021, and was developed a geospatial model of the different risk indicators for the occurrence of an attack, which has different layers and allows a spatio-temporal analysis of the different indicators, ascertaining the extent to which international and regional efforts have had a positive impact on combating this phenomenon. To complement this study, a statistical analysis of the data and a model of Bayesian Networks was built in order to predict the level of threat given the conditions and context at the time of the attack. The analysis carried out, allowed the identification of patterns between the different attacks and the prediction made through the Bayesian Networks classification model can be used not only to predict the level of threat but also to identify historical records classified with a level lower than the potential that this represented.
Description
Keywords
Pirataria Marítima Golfo da Guiné Análise de Padrões Rede Bayesiana Análise Geoespacial