International Journal of Mathematical, Engineering and Management Sciences

ISSN: 2455-7749

Land Use Drivers of Population Dynamics in Tasks of Security Management and Risk Assessment

Ivan Kopachevsky
Scientific Centre for Aerospace Research of the Earth, National Academy of Sciences of Ukraine, 55-b, O. Honchar Street, Kiev, 01601, Ukraine.

Yuriy V. Kostyuchenko
Scientific Centre for Aerospace Research of the Earth, National Academy of Sciences of Ukraine, 55-b, O. Honchar Street, Kiev, 01601, Ukraine.

Otto Stoyka
Kiev Municipal Health Center, Kiev, 103, Kyrylivska Street, Kiev, Ukraine.

DOI https://dx.doi.org/10.33889/IJMEMS.2016.1.1-002

Received on February 26, 2016
  ;
Accepted on March 01, 2016

Abstract

Approach to population data disaggregation in tasks of risk assessment is presented in this paper. The approach is based on analysis of land cover distribution separately in rural and urban areas. Model to analyze a population distribution on regular grid in a study area is proposed. Formal algorithms to estimate disaster losses distributions depending on population distribution, agroecological, socio-economic, and socio-ecological parameters are proposed. Concluding on population vulnerability and losses distribution in depending of land-use factors are proposed.

Keywords- Population density, Disaster losses, Rural and urban areas, Agroecology, Infrastructure accessibility, Resources availability.

Citation

Kopachevsky, I., V. Kostyuchenko, Y., & Stoyka, O. (2016). Land Use Drivers of Population Dynamics in Tasks of Security Management and Risk Assessment. International Journal of Mathematical, Engineering and Management Sciences, 1(1), 18-25. https://dx.doi.org/10.33889/IJMEMS.2016.1.1-002.

Conflict of Interest

Acknowledgements

References

Albersen, P. J., Fischer, G. F., Keyzer, M. A., & Sun, L. (2002). Estimation of Agricultural Production in the LUC-model for China. IIASA Research Report RR-02-03. Laxenburg, Austria: IIASA.

Chen, Y., & Zhou, Y. (2008). Scaling laws and indications of self-organized criticality in urban systems. Chaos, Solitons & Fractals, 35(1), 85-98.

Chen, Y. (2008). A wave-spectrum analysis of urban population density: entropy, fractal, and spatial localization. Discrete Dynamics in Nature and Society, 2008.

Clark, C. (1951). Urban population densities. Journal of the Royal Statistical Society. Series A (General), 114(4), 490-496.

Ermoliev, Y., Makowski, M., & Marti, K. (2012). Robust management of heterogeneous systems under uncertainties. In Managing Safety of Heterogeneous Systems (pp. 1-16). Springer Berlin Heidelberg.

FAO/ADPC (2006). The role of local institutions in reducing vulnerability to recurrent natural disasters and in sustainable livelihoods development. Food and Agriculture Organization of the UN (FAO) and Asian Disaster preparedness Center (ADPC).

Fischer, G. (1996). Simulating the socio-economic and bio geophysical driving forces of land-use and land-cover change: The IIASA land-use change model. Internat. Inst. for Applied Systems Analysis.

Fischer, G., Van Velthuizen, H., Shah, M., & Nachtergaele, F. (2002). Global Agro Ecological Assessment for Agriculture. In in the 21st Century, Rome, Food and Agriculture Organization of the United Nations (FAO), and Laxenburg, International Institute for Applied Systems Analysis (IIASA).

Gommes, R., Das, H., Mariani, L., Challinor, A., Tychon, B., Balaghi, R., & Dawod, M. A. (1981). Agrometeorological forecasting. Guide to Agricultural Meteorological Practices.

Kahn, M. E. (2005). The death toll from natural disasters: the role of income, geography, and institutions. Review of Economics and Statistics, 87(2), 271-284.

Kellenberg, D. K., & Mobarak, A. M. (2008). Does rising income increase or decrease damage risk from natural disasters? Journal of Urban Economics, 63(3), 788-802.

Kostyuchenko, Y. V., Bilous, Y., Movchan, D., Márton, L., & Kopachevsky, I. (2013). Toward methodology of satellite observation utilization for agricultural production risk assessment. IERI Procedia, 5, 21-27.

Kostyuchenko, Y. V. (2015). Geostatistics and Remote Sensing for Extremes Forecasting and Disaster Risk Multiscale Analysis. In Numerical Methods for Reliability and Safety Assessment (pp. 439-458). Springer International Publishing.

Kostyuchenko, Y. V., Movchan, D., Kopachevsky, I., & Bilous, Y. (2015, November). Robust algorithm of multi-source data analysis for evaluation of social vulnerability in risk assessment tasks. In SAI Intelligent Systems Conference (IntelliSys), 2015 (pp. 944-949). IEEE.

Kostyuchenko, Y. V. (2016). Risk Perception Based Approach to Analysis of Social Vulnerability. In Risk Perception: Theories and Approaches. Nova Science Publishers.

Kostyuchenko, Y. V., Kopachevsky, I., Zlateva, P., Stoyka, Yu., and Akymenko, P. (2012). Role of systemic risk in regional ecological long-term threats analysis. In Sustainable Civil Infrastructures – Hazards, Risk, Uncertainty, 2012 (pp.551–556). Research Publishing.

Kostyuchenko, Y. V., & Movchan, D. (2015). Quantitative parameter of risk perception: can we measure a geoethic and socio-economic component in disaster vulnerability?. Geological Society, London, Special Publications, 419(1), 79-86.

Linnerooth-Bayer, J., Mechler, R., & Pflug, G. (2005). Refocusing disaster aid. Science, 309(5737), 1044-1046.

Lutz, W., & Samir, K. C. (2011). Global human capital: Integrating education and population. Science, 333(6042), 587-592.

Marti, K., Ermoliev, Y., Makowski, M., & Pflug, G. (2010). Coping with Uncertainty. Springer.

Movchan, D., Kostyuchenko, Y. V., Marton, L., Frayer, O., & Kyryzyuk, S. (2014). Uncertainty analysis in crop productivity remote estimation for agricultural risks assessment. In Vulnerability, Uncertainty, and Risks Quantification, Mitigation, and Management (pp. 1008-1015). ASCE.

National report On Technogenic and Natural Security in Ukraine in 2009 (2010). Kiev: Chornobylinterinform.

Nelkin, D. (1989). Communicating technological risk: The social construction of risk perception. Annual Review of Public Health, 10(1), 95-113.

Spink, M. J. P., Menegon, V. M., Souza Bernardes, J. D., & Coêlho, A. E. L. (2007). The language of risk in psychology: a social constructionist analysis of a psychological database. Interamerican Journal of Psychology, 41(2), 151-160.

Tian, Y., Yue, T., Zhu, L., & Clinton, N. (2005). Modeling population density using land cover data. Ecological Modelling, 189(1), 72-88.

White, R., & Engelen, G. (1994). Urban systems dynamics and cellular automata: fractal structures between order and chaos. Chaos, Solitons & Fractals, 4(4), 563-583.

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