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dc.contributor.authorShahrabi, Jamal.en_US
dc.date.accessioned2014-10-21T12:36:23Z
dc.date.available2014-10-21T12:36:23Z
dc.date.issued2004en_US
dc.identifier.otherAAINR02121en_US
dc.identifier.urihttp://hdl.handle.net/10222/54716
dc.descriptionMaritime traffic analysis is growing in importance for many reasons including accident prevention and response planning, coastal zone management and coastal security. To best target measures for prevention, regulation and search and rescue planning, it is essential to characterize activities to determine the highest risk factors. Most decisions are location-sensitive, which has led to increasing use of spatial analysis in the maritime environment. Quantitative spatial data analysis differs from aspatial analysis in both the required data components and analytical tools. In this thesis a comprehensive spatial analysis of fishing incidents and fishing activity is conducted by including spatial factors and processing geo-referenced information.en_US
dc.descriptionThe spatial distribution of fishing incidents and fishing activity is described statistically by common point pattern analysis procedures. This includes descriptive statistics, examination of spatial arrangements among point features and investigation of spatial patterns through evaluating spatial autocorrelation statistics.en_US
dc.descriptionIn this thesis: the existence of spatial factors in fishing incidents was proved; spatial distribution of fishing incidents and fishing activity were quantified; the concentration of fishing incidents and fishing activity in different scales were identified; temporal shifting of clusters of fishing incidents and fishing activity were demonstrated; the probability of fishing incidents relative to fishing activity in all locations were computed; the temporal density of fishing incidents themselves and also relative to fishing activity were compared statistically; space/time interactions of incident patterns across years and quarters were shown; hazardous shipping locations were identified based on various methods; and finally, predictive spatial models of fishing incidents associated with fishing traffic and with fishing regions respectively were developed. (Abstract shortened by UMI.)en_US
dc.descriptionThesis (Ph.D.)--Dalhousie University (Canada), 2004.en_US
dc.languageengen_US
dc.publisherDalhousie Universityen_US
dc.publisheren_US
dc.subjectEngineering, Industrial.en_US
dc.subjectEngineering, Marine and Ocean.en_US
dc.titleSpatial and temporal analyses of maritime fishing and shipping traffic and incidents.en_US
dc.typetexten_US
dc.contributor.degreePh.D.en_US
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