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Author  |
Robert Power; Bella Robinson; David Alexander; Mahesh Prakash |
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Title |
Predicting Demand for Government Services during Disaster Events |
Type |
Conference Article |
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Year |
2018 |
Publication |
Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. |
Abbreviated Journal |
Iscram Ap 2018 |
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Pages |
89-96 |
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Keywords |
Situation Awareness, Data Integration, Disaster Management, Crisis Coordination |
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Abstract |
Smart Service Queensland (SSQ) is the 'front door' to the Queensland State Government in Australia, providing services and information for citizens and businesses. Services are delivered through online channels, call centres and face-to-face service centres. Rostering to adequately staff the call centres during business as usual demand is well supported using existing workforce planning tools and content management systems alongside real-time telephonic monitoring. However, during times of large scale emergency events, such as floods and tropical cyclones, effective workforce planning heavily relies upon experienced SSQ personnel constantly monitoring and updating call centre staffing levels leading up to and during the disaster event to ensure customer demands are met. Achieving the right balance of call centre servicing without over provisioning is a challenging task. We present a prototype analytics tool that supports the SSQ Forecast Analyst responsible for workforce planning during disaster events and provides initial results of modelling caller behavior during two recent tropical cyclones. The tool provides a single point of reference to a wide collection of relevant datasets, including population demographics and details of the natural and built environment, data feeds describing the emergency event under investigation, relevant social media posts and call centre operations metrics. The tool is an early proof of concept demonstrator highlighting the utility of data integration, web mapping, real-time event monitoring, and predictive modelling. |
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Csiro; Csiro; Csiro; Csiro |
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Publisher |
Massey Univeristy |
Place of Publication |
Albany, Auckland, New Zealand |
Editor |
Kristin Stock; Deborah Bunker |
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Language |
English |
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Track |
Monitoring and Alerting Systems supporting Business as Usual and Emergency Warnings |
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Notes |
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no |
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Call Number |
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Serial |
1668 |
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Author |
Robert Power; Mahesh Prakash; Bella Robinson; Nikhil Garg; Maria Wikstrom; Martijn Mooij |
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Title |
A Climate Resilience Platform for Agriculture |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the ISCRAM Asia Pacific Conference 2022 |
Abbreviated Journal |
Proc. ISCRAM AP 2022 |
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Pages |
164-172 |
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Keywords |
Climate; Climate Change; Adaption; Resilience; Agriculture |
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Abstract |
The changing climate will see an increase in the frequency, scale, and intensity of future natural disasters. While communities and governments need to work together to mitigate the impact of these emergency events, the business community will also need to adapt to ensure the ongoing sustainability of their enterprises. This is especially true of the agricultural sector which is exposed to climate variability. The Climate Services for Agriculture (CSA) tool is an online interactive digital platform bringing together a variety of climate information specifically for farmers and the agricultural sector. It will enable agricultural businesses, planners, and communities to explore various climate related datasets to better understand how the expected future climate may impact different regions and commodities. This will help people to anticipate and plan for the impacts of a variable and changing climate. We present the CSA tool, available at https://climateservicesforag.indraweb.io/, outlining how it is being developed in collaboration with key stakeholders in the Australian farming community, the climate data available and usage scenarios. |
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CSIRO Data61; CSIRO Data61; CSIRO Data61; CSIRO Data61; CSIRO Data61; CSIRO Data61 |
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Publisher |
Massey Unversity |
Place of Publication |
Palmerston North, New Zealand |
Editor |
Thomas J. Huggins, V.L. |
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Language |
English |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-0-473-66845-7 |
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Track |
Building Disaster Resilience |
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no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2490 |
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Author |
Vihan C.N. Weeraratne; Raymond C.Z. Cohen; Mahesh Prakash; Lalitha Ramachandran; Nikhil Garg; Valentijn Pauwels |
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Title |
Assessing Climate Vulnerability Under Future Changes to Climate, Demographics and Infrastructure: A Case Study for the Chapel Street Precinct, Melbourne |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the ISCRAM Asia Pacific Conference 2022 |
Abbreviated Journal |
Proc. ISCRAM AP 2022 |
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Volume |
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Pages |
35-44 |
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Keywords |
Climate Change; Heat; Flood; Vulnerability; Risk; Demographics |
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Abstract |
The Chapel Street Precinct is a busy commercial and residential corridor in the City of Stonnington Local Government Area (LGA) located in metropolitan Melbourne, Australia. Authorities and planners in the LGA are interested in understanding how the changing climate affects the socioeconomic environment of the region. By considering existing climate hazards (such as extreme heat, flood and water availability), infrastructure, and demographic information in the region together with future projections of climate change and demographic changes, a Socioeconomic Vulnerability Index (SVI) was created at a Mesh Block scale to better identify relatively high-risk Mesh Blocks in the region. The climate projections under medium and high future emission scenarios (i.e., representative concentration pathways (RCP)) as per IPCC (Intergovernmental Panel on Climate Change) fifth assessment report (AR5), RCP4.5 and RCP8.5 respectively for 30-year epochs around 2030, 2050 and 2070 were used in the SVI development. The current-day scenario is considered under Baseline conditions for demographic and asset information representing present-day conditions, whereas the baseline climate dataset considers the climate for the 30 year period 1991-2020 to best represent the present-day climate. The multi-model mean of the future climate projections from 6 different climate models were obtained from the Victoria’s Future Climate tool (https://vicfutureclimatetool.indraweb.io), developed by CSIRO (Commonwealth Scientific and Industrial Research Organisation) Data61 together with the Department of Environment, Land, Water and Planning (DELWP) under Data61’s INDRA framework (https://research.csiro.au/indra/). A version of INDRA is currently under development to allow map-based interactivity, experimentation and scrutiny of the vulnerability indices and their subcomponents across the study region. The SVI was created using a weighted indicator approach utilising a range of indicators belonging to 3 categories, exposure, susceptibility, and baseline adaptive capacity. The indicators were first normalised and the final SVI was given a score between 0-1 for each Mesh Block. The worst levels of vulnerability were observed to be for the RCP8.5 2070 scenario. In general, the RCP8.5 scenarios indicated a worse outcome compared to the RCP4.5 scenario. The area along Chapel Street within the precinct which is a densely built-up area high in population was found to be the most vulnerable area in the study region. It is foreseen that decision makers will be able to use the holistic data-driven outcomes of this study to make better informed decisions whilst adapting to climate change. |
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CSIRO Data61 & Monash University; CSIRO Data61; CSIRO Data61; City of Stonnington; CSIRO Data61; Monash University |
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Publisher |
Massey Unversity |
Place of Publication |
Palmerston North, New Zealand |
Editor |
Thomas J. Huggins, V.L. |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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ISSN |
2411-3387 |
ISBN |
978-0-473-66845-7 |
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Track |
Planning and Risk Analysis |
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Conference |
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no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2478 |
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