Collaborative Research: Spatial Dynamic Modeling of Exurban Land Markets and Land Use Patterns

合作研究：远郊土地市场和土地利用模式的空间动态建模

• 批准号: 1127044
• 负责人: Elena Irwin
• 金额: $ 13.01万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1127044&HistoricalAwards=false
• 关键词: Collaborative; Research; Spatial; Dynamic; Modeling

Despite recent advances in geosimulation, empirical land-use change modeling, and regional spatial dynamic theories, basic knowledge regarding how regional economic growth and decline impact the spatial and temporal dynamics of exurban land-use patterns remains rudimentary. This is due in large part to a continued reliance on assumptions of instantaneous price adjustments to a long-run spatial equilibrium in conventional urban economic models that omit consideration of short-run dynamics and local spatial interactions. To address these theoretical limitations, this research project will develop a dynamic spatial model of exurban land markets that explicitly accounts for key features of exurban areas to explain observed exurban land-price and development pattern dynamics (Objective 1). The model will incorporate local land use feedbacks, such as open space and congestion spillovers, to investigate how incorporation of these endogenous local spillovers influences land-price and land-use dynamics (Objective 2). The model will also be used to explore the potential impacts of income shocks on exurban land demand, supply, and land-use patterns and the time scales over which these changes occur (Objective 3). The project will accomplish these research objectives by developing a new theoretical model of exurban land markets that accounts for the relative demand and supply of spatially differentiated land. The investigators will use an auction model to derive optimal household bids and an optimal timing model to derive landowner reservation rents. Spatial agent-based computational modeling will be used to simulate market interactions and derive spatially varying market land prices and land development patterns over time. Extensive spatial data on parcel-level land development and residential location decisions will be used to empirically specify the key model parameters and MatLab and C++ codes will be used for implementation. The expectation is that the model will generate new hypotheses regarding the role of spatial arbitrage in exurban land markets and will provide a new theoretical and simulation-based framework for studying spatial land-use dynamics. Rapid exurban growth and the characteristic low density and scattered urbanization patterns that accompany it have greatly extended America's urban footprint and transformed many rural areas. Since the onset of the housing bust in 2006, a new set of challenges has emerged for many exurban areas that appear to have declined more rapidly than their urban and suburban counterparts. Both trends raise essential questions about the sustainability of exurban regions. By developing a dynamic spatial model of exurban land markets, this project will address these fundamental questions of exurban growth, decline, and sustainability. Despite the economic and ecological importance of the exurbs, no one has fully conceptualized or developed a spatial dynamic model of exurban land markets. By doing so, this project will make a fundamental theoretical contribution to land-change science and provide new insights into urban spatial patterns. The empirical applications proposed in this project will generate new knowledge that will have tangible benefits to policy makers confronted with urban sustainability management challenges. By furthering collaboration among scientists from regional science and physics, this project will advance the involvement of spatial scientists in interdisciplinary research and provide new interdisciplinary training opportunities for graduate students in complex systems and spatial economic modeling.

尽管最近在地理模拟，经验的土地利用变化模型，区域空间动态理论的进展，基本知识，区域经济增长和衰退如何影响城市外的土地利用模式的空间和时间动态仍然是基本的。这在很大程度上是由于在传统的城市经济模型中，忽略了对短期动态和地方空间相互作用的考虑，继续依赖于对长期空间平衡的瞬时价格调整的假设。为了解决这些理论上的局限性，本研究项目将开发一个动态的空间模型的郊区土地市场，明确说明郊区的主要特点，解释观察到的郊区土地价格和发展模式的动态（目标1）。该模型将纳入当地的土地利用反馈，如开放空间和拥挤溢出，研究如何纳入这些内生的本地溢出影响土地价格和土地利用动态（目标2）。该模型还将用于探讨收入冲击对郊区土地需求、供应和土地利用模式的潜在影响，以及这些变化发生的时间尺度（目标3）。 该项目将通过开发一个新的郊区土地市场理论模型来实现这些研究目标，该模型将解释空间差异化土地的相对需求和供应。 调查人员将使用拍卖模型来获得最佳家庭出价和最佳时间模型来获得土地所有者保留租金。空间代理为基础的计算模型将被用来模拟市场的相互作用，并得出空间变化的市场土地价格和土地开发模式随着时间的推移。 将使用关于地块级土地开发和住宅选址决策的大量空间数据来根据经验指定关键模型参数，并将使用MatLab和C++代码进行实施。期望该模型将产生新的假设空间套利的作用，在郊区土地市场，并将提供一个新的理论和模拟为基础的框架，研究空间土地利用动态。郊区的快速增长以及随之而来的低密度和分散的城市化模式极大地扩展了美国的城市足迹，并改变了许多农村地区。自2006年房地产泡沫破裂以来，许多郊区出现了一系列新的挑战，这些地区的衰退速度似乎比城市和郊区更快。 这两种趋势都提出了关于郊区可持续性的基本问题。 通过开发郊区土地市场的动态空间模型，本项目将解决郊区增长、衰退和可持续性的基本问题。尽管远郊的经济和生态的重要性，没有人已经完全概念化或开发出一个空间动态模型的远郊土地市场。通过这样做，该项目将为土地变化科学做出基本的理论贡献，并为城市空间格局提供新的见解。本项目中提出的经验应用将产生新的知识，为面临城市可持续性管理挑战的决策者带来切实利益。通过促进区域科学和物理科学家之间的合作，该项目将推动空间科学家参与跨学科研究，并为复杂系统和空间经济建模的研究生提供新的跨学科培训机会。