nach oben

Social Indicators Research

Erschienen in:

03.11.2016

A GIS-Based Interval Fuzzy Linear Programming for Optimal Land Resource Allocation at a City Scale

verfasst von: Changgang Ma, Min Zhou

Erschienen in: Social Indicators Research | Ausgabe 1/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

A geography information system based interval fuzzy linear programming model for city land resource allocation is developed in this study for dealing with land-use planning. The developed model improves upon the existing land resource allocation model with advantages in uncertainty reflection, model coupling, data availability and spatial analysis. The model can deal with uncertainties expressed as not only discrete interval values but also fuzzy sets. Therefore, it can effectively reflect dynamic, interactive complex, and uncertain characteristics of land-use system without unrealistic simplification. Moreover, the model can be used for supporting spatial allocation of land resources under a variety of ecological, environmental and socio-economic conditions. The developed model is applied to a real case of land resources allocation in Hangzhou City, China. Results demonstrate that the desired system benefit will be between $ [427.66, 549.83] × 10⁹; The model could help decision makers to generate stable and spatial land resources allocation patterns and strategic land use policies, gain in-depth insights into effects of the uncertainties and analyze trade-offs among economic objective, eco-environmental protection and social demands.

Vorheriger Artikel Daily Temporal Pathways: A Latent Class Approach to Time Diary Data

Nächster Artikel The National Wellbeing Index in the IsiXhosa Translation: Focus Group Discussions on How South Africans View the Quality of Their Society

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

Carsjens, G. J., & van der Knnap, W. (2002). Strategic land-use allocation: dealing with spatial relationships and fragmentation of agriculture. Landscape and Urban Planning, 58, 171–179.CrossRef

Chanas, S., & Zielinski, P. (2000). On the equivalence of two optimization methods for fuzzy linear programming problems. European Journal of Operational Research, 121, 56–63.CrossRef

Chang, N. B., & Wang, S. F. (1997). A fuzzy goal programming approach for the optimal planning of metropolitan solid waste management systems. European Journal of Operational Research, 32, 303–321.CrossRef

Cheung, C., & Cheng, J. Y. (2016). Resources and norms as conditions for well-being in Hong Kong. Social Indicators Research, 126, 757–775.CrossRef

FAO. (1993). Guidelines for land use planning Development Series 1, Rome.

Hagoort, M., Geertman, S., & Ottens, H. (2008). Spatial externalities, neighbourhood rules and CA land-use modelling. The Annals of Regional Science, 42, 39–56.CrossRef

Han, H., Hwang, Y. S., Ha, S. R., & Kim, B. S. (2015). Modeling future land use scenarios in South Korea: Applying the IPCC special report on emissions scenarios and the SLEUTH model on a local scale. Environmental Management, 55, 1064–1079.CrossRef

Hosseinali, F., Alesheikh, A. A., & Nourian, F. (2013). Agent-based modeling of urban land-use development, case study: Simulating future scenarios of Qazvin city. Cities, 31, 105–113.CrossRef

Kaiser, E. J., Godschalk, D. R., & Chaping, J. F. S. (1995). Urban land use planning (4th ed.). Urbana, USA: University of Illinois Press.

Kamusoko, C., Aniya, M., Adi, B., & Manjoro, M. (2009). Rural sustainability under threat in Zimbabwe-Simulation of future land use/cover changes in the Bindura district based on the Markov-cellular automata model. Applied Geography, 29, 435–447.CrossRef

Koomen, E., Rietveld, P., & de Nijs, T. (2008). Modelling land-use change for spatial planning support. The Annals of Regional Science, 42, 1–10.CrossRef

Law, E. A., Meijaard, E., Bryan, B. A., Mallawaarachchi, T., Koh, L. P., & Wilsona, K. A. (2015). Better land-use allocation outperforms land sparing and land sharing approaches to conservation in Central Kalimantan, Indonesia. Biological Conservation, 186, 276–286.CrossRef

Liu, L., Huang, G. H., Liu, Y., Fuller, G. A., & Zeng, G. M. (2003). A fuzzy-stochastic robust programming model for regional air quality management under uncertainty. Engineering Optimization, 35, 177–199.CrossRef

Liu, X., Ou, J., Li, X., & Ai, B. (2013). Combining system dynamics and hybrid particle swarm optimization for land use allocation. Ecological Modelling, 257, 11–24.CrossRef

Lu, Y., Cao, M., & Zhang, L. (2015). A vector-based cellular automata model for simulating urban land use change. Chinese Geographical Science, 25, 74–84.CrossRef

Maqsood, I., & Huang, G. H. (2003). A two-stage interval-stochastic programming model for waste management under uncertainty. Journal of the Air and Waste Management Association, 53, 540–552.CrossRef

McNeill, D., Bursztyn, M., Novira, N., Purushothaman, S., Verburg, R., & Rodrigues-Filho, S. (2014). Taking account of governance: The challenge for land-use planning models. Land Use Policy, 37, 6–13.CrossRef

Messina, V., & Bosetti, V. (2003). Uncertainty and option value in land allocation problems. Annals of Operations Research, 124, 165–181.CrossRef

Morse, S. (2016). Measuring the success of sustainable development indices in terms of reporting by the global press. Social Indicators Research, 125, 359–375.CrossRef

Munton, R. (1987). The conflict between conservation and food production in Great Britain. In C. Cocklin, B. Smit, & T. Johnston (Eds.), Demand on rural land. London, England: Westview Press.

Murray-Rust, D., Robinson, D. T., Guillem, E., Karali, E., & Rounsevell, M. (2014). An open framework for agent based modelling of agricultural land use change. Environment Modelling and Software, 61, 19–38.CrossRef

Nguyen, T. T., Verdoodt, A., Tran, V. Y., Delbecque, N., Tran, T. C., & Ranst, E. V. (2015). Design of a GIS and multi-criteria based land evaluation procedure for sustainable land-use planning at the regional level. Agriculture Ecosystems and Environment, 200, 1–11.CrossRef

Nino-Ruiz, M., Bishop, I., & Pettit, C. (2013). Spatial model steering, an exploratory approach to uncertainty awareness in land use allocation. Environment Modelling and Software, 39, 70–80.CrossRef

Oberling, D. F., la Rovere, E. L., & de Oliveira Silva, H. V. (2013). SEA making inroads in land-use planning in Brazil: The case of the Extreme South of Bahia with forestry and biofuels. Land Use Policy, 35, 341–358.CrossRef

Overmars, K. P., Verburg, P. H., & Veldkamp, T. (2007). Comparison of a deductive and an inductive approach to specify land suitability in a spatially explicit land use model. Land Use Policy, 24, 584–599.CrossRef

Pilehforooshha, P., Karimi, M., & Taleai, M. (2014). A GIS-based agricultural land-use allocation model coupling increase and decrease in land demand. Agricultural Systems, 130, 116–125.CrossRef

Qin, X. S., Huang, G. H., Zeng, G. M., Chakma, A., & Huang, Y. F. (2007). An interval-parameter fuzzy nonlinear optimization model for stream water quality management under uncertainty. European Journal of Operational Research, 180, 1331–1357.CrossRef

Rajaei, S. A., & Mansourian, H. (2016). Urban growth and housing quality in Iran. Social Indicators Research,. doi:10.1007/s11205-016-1260-2.

Richard, A. (2004). Modelling land use change with generalized linear models—a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana. Journal of Environmental Management, 72, 91–103.

Rodriguez-Rosa, M., Gallego-Alvarez, I., Vicente-Galindo, M. P., & Galindo-Villardon, M. P. (2016). Are social, economic and environmental well-being equally important in all countries around the world? a study by income levels. Social Indicators Research,. doi:10.1007/s11205-016-1257-x.

Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15, 234–281.CrossRef

Siripun, T. (2001). Dynamic simulation modeling of the land use, economy and environment in Chiang Mai, Thailand using GIS and remote sensing. New York, USA: State University of New York Press.

Stewart, T. J., & Janssen, R. (2014). A multiobjective GIS-based land use planning algorithm. Computers Environment and Urban Systems, 46, 25–34.CrossRef

Svoray, T., Kutiel, P. B., & Bannet, T. (2005). Urban land-use allocation in a editerranean ecotone: Habitat Heterogeneity Model incorporated in a GIS using a multi-criteria mechanism. Landscape and Urban Planning, 72, 337–351.CrossRef

Turner, B. L., Meyer, W. B., & Skole, D. L. (1994). Global land-use/land cover change: towards an integrated study. Ambio, 23, 91–99.

Uday, B. N., de Bie, C., van Keulen, H., Skidmore, A. K., & Harmsen, K. (2006). Review of a land use planning programme through the soft systems methodology. Land Use Policy, 23, 187–203.CrossRef

Verburg, P. H., Eickhout, B., & van Meijl, H. (2008). A multi-scale, multi-model approach for analyzing the future dynamics of European land use. The Annals of Regional Science, 42, 57–77.CrossRef

Verburg, P. H., Tabeau, A., & Hatna, E. (2013). Assessing spatial uncertainties of land allocation using a scenario approach and sensitivity analysis: A study for land use in Europ. Journal of Environmental Management, 127, S132–S144.CrossRef

Verburg, P. H., van Berkel, D. B., van Doorn, D. B., van Eupen, M., & van den Heiligenberg, H. A. (2010). Trajectories of land use change in Europe: a model-based exploration of rural futures. Landscape Ecology, 25, 217–232.CrossRef

Wang, H., Li, X. B., Long, H. L., Qiao, Y. W., & Li, Y. (2011). Development and application of a simulation model for changes in land-use patterns under drought scenarios. Computers and Geosciences, 37, 831–843.CrossRef

Wang, X. H., Yu, S., & Huang, G. H. (2004). Land allocation based on integrated GIS-optimization modeling at a watershed level. Landscape and Urban Planning, 66, 61–74.CrossRef

Wey, W. M., & Wei, W. L. (2016). Urban growth and housing quality in Iran. Social Indicators Research, 126, 161–186.CrossRef

Zhang, J., Fu, M., Zhang, Z., Tao, J., & Fu, W. (2014). A trade-off approach of optimal land allocation between socio-economic development and ecological stability. Ecological Modeling, 272, 175–187.CrossRef

Zhou, M. (2015). An interval fuzzy chance-constrained programming model forsustainable urban land-use planning and land use policy analysis. Land Use Policy, 42, 479–491.CrossRef

Titel: A GIS-Based Interval Fuzzy Linear Programming for Optimal Land Resource Allocation at a City Scale
verfasst von: Changgang Ma
Min Zhou
Publikationsdatum: 03.11.2016
Verlag: Springer Netherlands
Erschienen in: Social Indicators Research / Ausgabe 1/2018
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI: https://doi.org/10.1007/s11205-016-1476-1

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 1/2018

Time in the Development of Indicators on Sustainable Wellbeing: A Local Experiment in Developing Alternative Indicators

Measuring and Monitoring Poverty and Well-Being: A New Approach for the Synthesis of Multidimensionality

Geocentric Behavior Dimension of the Organization’ Performance in the Context of Globalization

The National Wellbeing Index in the IsiXhosa Translation: Focus Group Discussions on How South Africans View the Quality of Their Society

Income Dependency on Non-timber Forest Products: An Empirical Evidence of the Indigenous People in Peninsular Malaysia

Correcting the Underestimation of Top Incomes: Combining Data from Income Tax Reports and the Brazilian 2010 Census