Tropical Cyclone Hazard mapping Using Geospatial Techniques for the Eastern Coastal Region of Bangladesh

Dr Muhammad Al-Amin Hoque1,2, Prof Biswajeet Pradhan1, Mr Ahmed Naser2

1Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney, Australia,

2Department of Geography and Environment, Jagannath University, Dhaka, Bangladesh

 

Tropical cyclones are the most common disasters in Bangladesh striking the country almost every year. The frequency and impacts of tropical cyclones will be higher in Bangladesh under future climate change scenarios. The eastern coastal region of Bangladesh is one of the highly cyclone affected coastal regions. This study aims to develop a multi-criteria integrated cyclone hazard map using geospatial techniques for the eastern coastal region of Bangladesh. Four criteria associated with cyclone hazard impacts were assessed. Thematic layers were prepared for each criterion, and hazard ratings were assigned using geospatial techniques. Finally, a hazard map was developed using a weighted overlay technique integrating all of the criteria layers with their assigned weights using Analytical hierarchy process. Our results indicated that 23% of the study area was located in the very high hazard zone, mostly close to the coast, with 22 % area as high hazard zone and around 18% area was at moderate hazard zone. The area was classified as low and very low hazard zone accounts the 17% and 20%, respectively, mostly towards inland from the coast. The findings of this study can be used by policymakers and administrators to develop effective cyclone impact mitigation plans.


Biography:

Dr Muhammad Al-Amin Hoque is a research fellow at Centre for Advanced Modelling and Geospatial Information Systems, University of Technology Sydney, Australia. His research focuses on the uses of geospatial techniques for mapping and monitoring environmental changes and natural disasters.

The influence of satellite imagery on landscape perception

Mrs Daisy San Martin Saldias1, Dr Karin Reinke1, Dr Blythe McLennan1

1RMIT University, Melbourne, Australia

 

A landscape is an area whose character is the result of the interaction of natural and human factors across time. The perception of landscape involves the process of categorising and differentiating our surrounds according to sensory information and the past experiences of individuals. Increasingly, due to the ubiquitous nature of platforms such as Google Earth, individuals are accessing visual information of their surrounding environment through satellite imagery. This presentation aims to examine how people’s perceptions may be changing in an age when our experiences increasingly occur in digital space, altering the perception paradigm from one where individuals analyse direct objects to one where indirect objects are key in the formation of the mental image of the landscape. This indirect mode of observing the landscape allows comparisons to be made at a global scale, and in doing so potentially change how the area is perceived on the ground. A case study for a region in Chile, South America, is used to explore these ideas with over 50 survey participants providing responses to questions about their landscape, before and after, unstructured exploration of the region using Google Earth.


Biography:

Daisy is a PhD candidate at RMIT University. Her PhD project focuses on the increasing availability of satellite images and how they shape our perception amidst significant change. Daisy has a deep interest in human geography, especially social perception within ecosystems.

Structural vulnerability assessment using an artificial neural network for earthquake hazard in Banda Aceh city, Aceh Province, Indonesia

Mr Ratiranjan Jena1, Prof Biswajeet Pradhan1, Prof Ghassan Beudoun1

1Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney, Australia

 

The vulnerability assessment of earthquake in urban or regional scale comprises of a principal component in mitigating the structural vulnerability due to earthquakes. Challenges exist in the delineation of earthquake fragilities of buildings exposed to the hazard. However, vulnerability or fragility for structural elements can be derived using analytical, expert opinion based methods or empirical methods provide the loss ratio probability, conditionally on a particular level of measured intensity. Therefore, this study proposes a neural network approach for the assessment of structural vulnerability in Banda Aceh city by considering and analysing the factors of building density, size of buildings, building area and building materials. There are some uncertainties that are involved in vulnerability assessment and especially the accurate assessment of earthquake vulnerability is important to obtain the bounds of the expected losses, which has been proved through the neural network methodologies. Our results show that the proposed method is able to estimate the vulnerability of earthquake in Banda Aceh city accurately with an accuracy of 85%. The validation of the resulted structural vulnerability map was conducted using the earthquake events and previously published inventory map.


Biography:

Mr. Ratirankan Jena is a {PhD student at the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Australia. His research focuses on the uses of geospatial techniques for mapping and monitoring environmental changes and natural disasters.

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