Lu Shasha, Zhou Min, Guan Xingliang, Tao Lizao
School of Economics and Management, Beijing Forestry University, Beijing, 100083, China,
Environ Sci Pollut Res Int. 2015 Mar;22(6):4281-96. doi: 10.1007/s11356-014-3659-0. Epub 2014 Oct 8.
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.
为支持土地利用分配的优化，已开发出大量数学模型；然而，其中很少有模型能同时考虑土地适宜性（如物理特征和空间信息）以及许多因素中存在的各种不确定性（如土地可用性、土地需求、土地利用模式和生态要求）。本文将地理信息系统（GIS）技术纳入区间概率规划（IPP）以进行土地利用规划管理（IPP-LUPM）。利用GIS收集汇总土地利用替代方案的数据，并开发IPP来处理以离散区间和概率分布形式呈现的不确定性。基于GIS，通过土地适宜性评估和空间分析的结果提供不同土地使用者的适宜性地图。从适宜性地图获得的各类土地利用的最大面积，以及各种目标/约束条件（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IPP-LUPM模型优化土地利用面积的输入数据。所提出的模型不仅考虑土地适宜性评价的结果（即地形、地面条件、水文和空间位置），还涉及经济因素、粮食安全和生态环境约束，能有效反映土地利用规划管理系统中不同方面之间的各种相互关系。中国苏州的案例研究结果表明，该模型有助于检验在不确定性下满足（或违反）系统约束的可靠性。此外，它可能识别土地适宜性与系统效益之间的定量关系。基于高度适宜土地的条件安排土地面积的意愿不仅会减少对环境系统的潜在冲突，还会带来较低的经济效益。然而，强烈开发较低适宜性土地面积的愿望不仅会带来较高的经济效益，还会带来违反环境和生态约束的较高风险。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。
