ArticleEnvironmental science and pollution research international2015
An integrated GIS-based interval-probabilistic programming model for land-use planning management under uncertainty--a case study at Suzhou, China.
Article in Environmental science and pollution research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Spatial analysis of production-living-ecological functions and zoning method under symbiosis theory of Henan, China.Environmental science and pollution research international · 2021Article
- Land Suitability Evaluation and an Interval Stochastic Fuzzy Programming-Based Optimization Model for Land-Use Planning and Environmental Policy Analysis.International journal of environmental research and public health · 2019Article
- Distributed mixed-integer fuzzy hierarchical programming for municipal solid waste management. Part I: System identification and methodology development.Environmental science and pollution research international · 2017Article
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4 authors.
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Abstract
A large number of mathematical models have been developed for supporting optimization of land-use allocation; however, few of them simultaneously consider land suitability (e.g., physical features and spatial information) and various uncertainties existing in many factors (e.g., land availabilities, land demands, land-use patterns, and ecological requirements). This paper incorporates geographic information system (GIS) technology into interval-probabilistic programming (IPP) for land-use planning management (IPP-LUPM). GIS is utilized to assemble data for the aggregated land-use alternatives, and IPP is developed for tackling uncertainties presented as discrete intervals and probability distribution. Based on GIS, the suitability maps of different land users are provided by the outcomes of land suitability assessment and spatial analysis. The maximum area of every type of land use obtained from the suitability maps, as well as various objectives/constraints (i.e., land supply, land demand of socioeconomic development, future development strategies, and environmental capacity), is used as input data for the optimization of land-use areas with IPP-LUPM model. The proposed model not only considers the outcomes of land suitability evaluation (i.e., topography, ground conditions, hydrology, and spatial location) but also involves economic factors, food security, and eco-environmental constraints, which can effectively reflect various interrelations among different aspects in a land-use planning management system. The case study results at Suzhou, China, demonstrate that the model can help to examine the reliability of satisfying (or risk of violating) system constraints under uncertainty. Moreover, it may identify the quantitative relationship between land suitability and system benefits. Willingness to arrange the land areas based on the condition of highly suitable land will not only reduce the potential conflicts on the environmental system but also lead to a lower economic benefit. However, a strong desire to develop lower suitable land areas will bring not only a higher economic benefit but also higher risks of violating environmental and ecological constraints. The land manager should make decisions through trade-offs between economic objectives and environmental/ecological objectives.
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