Strengthening Sustainable Pathways by Detecting Variability in a Community’s Resilience at the Sub-Local Government Level Using the GCRM

Article

Singh-Peterson, Lila, Popvic, Igor, Karatela, Shamshad, Raj, Nawin and Batt, David. 2025. "Strengthening Sustainable Pathways by Detecting Variability in a Community’s Resilience at the Sub-Local Government Level Using the GCRM." Sustainability. 17 (8). https://doi.org/10.3390/su17083372
Article Title

Strengthening Sustainable Pathways by Detecting Variability in a Community’s Resilience at the Sub-Local Government Level Using the GCRM

ERA Journal ID41498
Article CategoryArticle
AuthorsSingh-Peterson, Lila, Popvic, Igor, Karatela, Shamshad, Raj, Nawin and Batt, David
Journal TitleSustainability
Journal Citation17 (8)
Article Number3372
Number of Pages19
Year2025
PublisherMDPI AG
Place of PublicationSwitzerland
ISSN2071-1050
Digital Object Identifier (DOI)https://doi.org/10.3390/su17083372
Web Address (URL)https://www.mdpi.com/2071-1050/17/8/3372
Abstract

Enhancing community resilience has become increasingly important in preparing for, responding to, and recovering from disaster events. Determining how levels of community resilience vary across a local government area provides nuanced information from which targeted programs and initiatives can be developed, implemented, and evaluated. This study applies the Gympie Regional Community Resilience Metric (GCRM), developed with a local government organisation, and a community disaster sub-group in rural Queensland, Australia, and applies it to a larger, coastal region of Bundaberg, Queensland. Completed survey results returned by 696 households from across the region revealed that the Bundaberg community is generally well-prepared for disasters, with strong social networks and understanding of local risks. However, there are areas for improvement, such as increasing participation in local clubs and addressing the needs of those lacking confidence in obtaining help during disasters. Other findings indicate that the evidence of high levels of local knowledge and disaster experience within the community could provide opportunities to establish neighbourhood networks that aim to share local knowledge and experiences and enhance localised networks of support, particularly for more vulnerable and newer residents.

Keywordsrural resilience; community resilience; disaster management; policy initiatives; risk and resilience; climate change; local government; Australia
Article Publishing Charge (APC) FundingOther
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020410103. Human impacts of climate change and human adaptation
440704. Environment policy
441002. Environmental sociology
Byline AffiliationsSchool of Agriculture and Environmental Science
Centre for Applied Climate Sciences
University of Queensland
Monash University
School of Mathematics, Physics and Computing
Bundaberg Regional Council, Australia
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Singh-Peterson, Lila and Lawrence, Geoffrey. 2016. "The changing face of the Mary Valley: considering the fairness, sustainability and resilience of the agricultural system in a peri-urban setting." Local Environment: the international journal of justice and sustainability. 22 (5), pp. 568-580. https://doi.org/10.1080/13549839.2016.1233953
Interrogating resilience: toward a typology to improve its operationalization
Davidson, Julie L., Jacobson, Chris, Lyth, Anna, Dedekorkut-Howes, Aysin, Baldwin, Claudia L., Ellison, Joanna C., Holbrook, Neil J., Howes, Michael J., Serrao-Neumann, Silvia, Singh-Peterson, Lila and Smith, Timothy F.. 2016. "Interrogating resilience: toward a typology to improve its operationalization." Ecology and Society: a journal of integrative science for resilience and sustainability. 21 (2). https://doi.org/10.5751/es-08450-210227
A multi-scalar, mixed methods framework for assessing rural communities’ capacity for resilience, adaptation, and transformation
Singh-Peterson, Lila and Underhill, Steven J. R. 2016. "A multi-scalar, mixed methods framework for assessing rural communities’ capacity for resilience, adaptation, and transformation." Community Development. 48 (1), pp. 127-140. https://doi.org/10.1080/15575330.2016.1250103
Modelling secondary organic aerosol formation: from chemical mechanistic modelling to empirical modelling
Singh-Peterson, Lila. 2007. Modelling secondary organic aerosol formation: from chemical mechanistic modelling to empirical modelling. PhD Thesis Doctor of Philosophy. University of New South Wales.
Prediction of Sea Level with Vertical Land Movement Correction Using Deep Learning
Raj, Nawin. 2022. "Prediction of Sea Level with Vertical Land Movement Correction Using Deep Learning." Mathematics. 10 (23). https://doi.org/10.3390/math10234533
Development of data-driven models for wind speed forecasting in Australia
Neupane, Ananta, Raj, Nawin, Deo, Ravinesh and Ali, Mumtaz. 2021. "Development of data-driven models for wind speed forecasting in Australia." Deo, R., Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Netherlands. Elsevier. pp. 143-190
Guidance law for a surveillance UAV swarm tracking a high capability malicious UAV
Brown, Jason and Raj, Nawin. 2021. "Guidance law for a surveillance UAV swarm tracking a high capability malicious UAV." 2021 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob 2021). Bandung, Indonesia 08 - 10 Apr 2021 United States. https://doi.org/10.1109/APWiMob51111.2021.9435240
The Impact of Initial Swarm Formation for Tracking of a High Capability Malicious UAV
Brown, Jason and Raj, Nawin. 2021. "The Impact of Initial Swarm Formation for Tracking of a High Capability Malicious UAV." International IOT, Electronics and Mechatronics Conference (IEMTRONICS 2021). Toronto, Canada 21 - 24 Apr 2021 Piscataway, United States. https://doi.org/10.1109/IEMTRONICS52119.2021.9422506
Predictive Tracking of a High Capability Malicious UAV
Brown, Jason and Raj, Nawin. 2021. "Predictive Tracking of a High Capability Malicious UAV." IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC 2021). Las Vegas, United States 27 - 30 Jan 2021 Piscataway, United States. https://doi.org/10.1109/CCWC51732.2021.9376137
Evaluation of multivariate adaptive regression splines and artificial neural network for prediction of mean sea level trend around northern Australian coastlines
Raj, Nawin and Gharineiat, zahra. 2021. "Evaluation of multivariate adaptive regression splines and artificial neural network for prediction of mean sea level trend around northern Australian coastlines." Mathematics. 9 (21), pp. 1-20. https://doi.org/10.3390/math9212696
Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition
Huynh, Anh Ngoc-Lan, Deo, Ravinesh C., Ali, Mumtaz, Abdulla, Shahab and Raj, Nawin. 2021. "Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition." Applied Energy. 298, pp. 1-19. https://doi.org/10.1016/j.apenergy.2021.117193
Hybrid deep learning method for a week-ahead evapotranspiration forecasting
Ahmed, A. A. Masrur, Deo, Ravinesh C., Feng, Qi, Ghahramani, Afshin, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2022. "Hybrid deep learning method for a week-ahead evapotranspiration forecasting." Stochastic Environmental Research and Risk Assessment. 36 (3), pp. 831-849. https://doi.org/10.1007/s00477-021-02078-x
Particle and particle-like solitary wave dynamics in fluid media
Raj, Nawin. 2015. Particle and particle-like solitary wave dynamics in fluid media. PhD Thesis Doctor of Philosophy. University of Southern Queensland.
Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data
Ahmed, A. A. Masrur, Deo, Ravinesh C., Raj, Nawin, Ghahramani, Afshin, Feng, Qi, Yin, Zhenliang and Yang, Linshan. 2021. "Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data." Remote Sensing. 13 (4), pp. 1-30. https://doi.org/10.3390/rs13040554
LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios
Ahmed, A. A. Masrur, Deo, Ravinesh C., Ghahramani, Afshin, Raj, Nawin, Feng, Qi, Yin, Zhenliang and Yang, Linshan. 2021. "LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios." Stochastic Environmental Research and Risk Assessment. 35, pp. 1851-1881. https://doi.org/10.1007/s00477-021-01969-3
Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity
Ahmed, A. A. Masrur, Deo, Ravinesh C., Feng, Qi, Ghahramani, Afshin, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2021. "Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity." Journal of Hydrology. 599, pp. 1-23. https://doi.org/10.1016/j.jhydrol.2021.126350
An EEMD-BiLSTM algorithm integrated with Boruta random forest optimiser for significant wave height forecasting along coastal areas of Queensland, Australia
Raj, Nawin and Brown, Jason. 2021. "An EEMD-BiLSTM algorithm integrated with Boruta random forest optimiser for significant wave height forecasting along coastal areas of Queensland, Australia." Remote Sensing. 13 (8), pp. 1-20. https://doi.org/10.3390/rs13081456
Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures Using Machine Learning
Gunasekara, C., Lokuge, W., Keskic, M., Raj, N., Law, D. W. and Setunge, S.. 2020. "Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures Using Machine Learning." ACI Materials Journal. 117 (5), pp. 263-278. https://doi.org/10.14359/51727019
Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra, Parisi, Alfio and Raj, Nawin. 2020. "Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks." IEEE Access. 8, pp. 209503-209516. https://doi.org/10.1109/ACCESS.2020.3039002
Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji
Moishin, Mohammed, Deo, Ravinesh C., Prasad, Ramendra, Raj, Nawin and Abdulla, Shahab. 2021. "Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji." Stochastic Environmental Research and Risk Assessment. 35 (7), pp. 1387-1402. https://doi.org/10.1007/s00477-020-01899-6
Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network
Huynh, Anh Ngoc‐Lan, Deo, Ravinesh C., An-Vo, Duc-Anh, Ali, Mumtaz, Raj, Nawin and Abdulla, Shahab. 2020. "Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network." Energies. 13 (14). https://doi.org/10.3390/en13143517
Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction." Renewable and Sustainable Energy Reviews. 113, pp. 1-19. https://doi.org/10.1016/j.rser.2019.109247
Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms." Applied Energy. 253, pp. 1-20. https://doi.org/10.1016/j.apenergy.2019.113541
Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction." Energies. 12 (12), pp. 1-42. https://doi.org/10.3390/en12122407
Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia
Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J. and Raj, Nawin. 2019. "Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia." Journal of Cleaner Production. 216, pp. 288-310. https://doi.org/10.1016/j.jclepro.2019.01.158
Optimization of windspeed prediction using an artificial neural network compared with a genetic programming model
Deo, Ravinesh C., Ghimire, Sujan, Downs, Nathan J. and Raj, Nawin. 2018. "Optimization of windspeed prediction using an artificial neural network compared with a genetic programming model." Kim, Dookie, Roy, Sanjiban Sekhar, Lansivaara, Tim, Deo, Ravinesh C. and Samui, Pijush (ed.) Handbook of research on predictive modeling and optimization methods in science and engineering. Hershey, United States. IGI Global. pp. 328-359
Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region
Mouatadid, Soukayna, Raj, Nawin, Deo, Ravinesh C. and Adamowski, Jan F.. 2018. "Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region." Atmospheric Research. 212, pp. 130-149. https://doi.org/10.1016/j.atmosres.2018.05.012
Self-adaptive differential evolutionary extreme learning machines for long-term solar radiation prediction with remotely-sensed MODIS satellite and Reanalysis atmospheric products in solar-rich cities
Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J. and Raj, Nawin. 2018. "Self-adaptive differential evolutionary extreme learning machines for long-term solar radiation prediction with remotely-sensed MODIS satellite and Reanalysis atmospheric products in solar-rich cities." Remote Sensing of Environment: an interdisciplinary journal. 212, pp. 176-198. https://doi.org/10.1016/j.rse.2018.05.003
Adiabatic decay of internal solitons due to Earth’s rotation within the framework of the Gardner–Ostrovsky equation
Obregon, Maria, Raj, Nawin and Stepanyants, Yury. 2018. "Adiabatic decay of internal solitons due to Earth’s rotation within the framework of the Gardner–Ostrovsky equation." Chaos: an interdisciplinary journal of nonlinear science. 28 (3), pp. 1-11. https://doi.org/10.1063/1.5021864
Adiabatic decay of internal solitons in a rotating ocean
Obregon, M. A., Raj, N. and Stepanyants, Y. A.. 2016. "Adiabatic decay of internal solitons in a rotating ocean." 20th Australasian Fluid Mechanics Conference (AFMC 2016). Perth, Australia 05 - 08 Dec 2016 Australia.
Supporting a Diverse and Sustainable Fruit Industry in Tonga
Singh-Peterson, Lila, Halavatau, Siosiua and Underhill, Steven. 2015. Supporting a Diverse and Sustainable Fruit Industry in Tonga. Sunshine Coast, Australia. University of the Sunshine Coast.
An assessment of community disaster resilience for small, high-risk communities on the Sunshine Coast, Qld
Singh-Peterson, Lila, Salmon, Paul, Goode, Natassia and Gallina, John. 2015. "An assessment of community disaster resilience for small, high-risk communities on the Sunshine Coast, Qld." The Australian Journal of Emergency Management. 30 (1), pp. 35-40.
The Changing Face of Mary documentary
Singh-Peterson, ila, Smit, Sondra, Lawrence, Geoff and Carter, Bill. 2015. The Changing Face of Mary documentary. Sippy Downs, Australia.
Nonlinear vector waves of a flexural mode in a chain model of atomic particles
Nikitenkova, S. P., Raj, N. and Stepanyants, Y. A.. 2015. "Nonlinear vector waves of a flexural mode in a chain model of atomic particles." Communications in Nonlinear Science and Numerical Simulation. 20 (3), pp. 731-742. https://doi.org/10.1016/j.cnsns.2014.05.031
ACIAR Final Report Supporting a diverse and sustainable fruit tree industry in Tonga HORT/2014/090
Underhill, Steven, Singh-Peterson, Lila, Na'ati, Elisiva and Halavatau, Siosiua. 2014. ACIAR Final Report Supporting a diverse and sustainable fruit tree industry in Tonga HORT/2014/090. Sunshine Coast, Australia. University of the Sunshine Coast.
Re-framing community disaster resilience: from a systems perspective: Sunshine Coast case study report
Singh-Peterson, L., Baldwin, C., Dickinson, M, Bohnen, S., Woolcock, G., Malcom, F., Salmon, P., Goode, N. and Gallina, J.. 2014. Re-framing community disaster resilience: from a systems perspective: Sunshine Coast case study report. Sippy downs, Australia. University of the Sunshine Coast.
Nonlinear spectra of shallow water waves
Giovanangeli, J. -P., Kharif, C., Raj, N. and Stepanyants, Y.. 2013. "Nonlinear spectra of shallow water waves." Oceans - San Diego, 2013. San Diego, United States 23 - 26 Sep 2013 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.23919/OCEANS.2013.6741132
Numerical study of nonlinear wave processes by means of discrete chain models
Obregon, M., Raj, N. and Stepanyants, Y.. 2012. "Numerical study of nonlinear wave processes by means of discrete chain models." Gu, Y. T. and Saha, Suvash C. (ed.) 4th International Conference on Computational Methods (ICCM 2012). Gold Coast, Australia 25 - 28 Nov 2012 Brisbane, Australia.
Controversies in Local Economic Development: Stories, Strategies, Solutions by Martin Perry
Singh-Peterson, Lila. 2011. "Controversies in Local Economic Development: Stories, Strategies, Solutions by Martin Perry." Journal of Economic and Social Policy. 14 (3).