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首页> 外文期刊>Environmental Science and Pollution Research >An integrated GIS-based interval-probabilistic programming model for land-use planning management under uncertainty-a case study at Suzhou, China
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An integrated GIS-based interval-probabilistic programming model for land-use planning management under uncertainty-a case study at Suzhou, China

机译:不确定条件下基于GIS的土地利用规划管理综合区间概率规划模型-以苏州为例

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摘要

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.
机译:为了支持土地利用分配的优化,已经开发了大量数学模型。但是,他们中很少有人同时考虑土地的适宜性(例如,物理特征和空间信息)以及许多因素(例如,土地可利用性,土地需求,土地使用方式和生态需求)中存在的各种不确定性。本文将地理信息系统(GIS)技术纳入间隔概率编程(IPP)中,以进行土地利用规划管理(IPP-LUPM)。地理信息系统用于收集汇总的土地利用替代方案的数据,而国际植检门户网站则用于处理以离散区间和概率分布表示的不确定性。基于GIS,通过土地适宜性评估和空间分析的结果,提供了不同土地使用者的适宜性图。从适宜性图获得的每种土地利用的最大面积,以及各种目标/约束(即土地供应,社会经济发展的土地需求,未来发展战略和环境容量),被用作土地利用的输入数据。 IPP-LUPM模型优化土地利用区域。所提出的模型不仅考虑了土地适宜性评估的结果(即地形,地面条件,水文学和空间位置),而且还涉及经济因素,粮食安全和生态环境约束,这些因素可以有效反映不同方面之间的各种相互关系。在土地利用规划管理系统中。中国苏州的案例研究结果表明,该模型可以帮助检验不确定性下满足(或违反风险)系统约束的可靠性。此外,它可以确定土地适宜性与系统效益之间的定量关系。愿意根据高度合适的土地条件安排土地面积,不仅会减少对环境系统的潜在冲突,而且会导致较低的经济效益。但是,强烈希望开发出适合自己的土地,这不仅会带来更高的经济效益,而且还会带来违反环境和生态约束的更大风险。土地管理者应通过在经济目标与环境/生态目标之间进行权衡来做出决策。

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