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

尽管地理模拟、经验土地利用变化模型和区域空间动力学理论近年来取得了进展，但关于区域经济增长和衰退如何影响远郊土地利用格局的时空动态的基本知识仍处于初级阶段。这在很大程度上是由于传统城市经济模型继续依赖于对长期空间平衡的瞬时价格调整的假设，而忽略了短期动态和局部空间相互作用的考虑。为了解决这些理论局限性，本研究项目将开发一个动态的郊区土地市场空间模型，该模型明确地解释了郊区地区的关键特征，以解释观察到的郊区土地价格和发展模式动态（目标1）。该模型将纳入地方土地利用反馈，如开放空间和拥堵溢出效应，以研究这些内生的地方溢出效应如何影响地价和土地利用动态（目标2）。该模型还将用于探索收入冲击对郊区土地需求、供应和土地使用模式的潜在影响，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城郊土地市场理论模型来实现这些研究目标，该模型考虑了空间差异土地的相对需求和供应。研究人员将使用拍卖模型来推导最优家庭出价，并使用最优时机模型来推导土地所有者保留租金。基于空间主体的计算模型将用于模拟市场相互作用，并推导出随时间变化的市场土地价格和土地开发模式。关于地块级土地开发和住宅选址决策的广泛空间数据将用于经验性地指定关键模型参数，并将使用MatLab和c++代码来实现。期望该模型将产生关于空间套利在城郊土地市场中的作用的新假设，并将为研究空间土地利用动态提供一个新的理论和基于模拟的框架。快速的城郊增长以及伴随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，许多远郊地区出现了一系列新的挑战，这些地区似乎比城市和郊区的同行下降得更快。这两种趋势都对城郊地区的可持续性提出了重要问题。通过建立一个动态的郊区土地市场空间模型，本项目将解决郊区增长、衰退和可持续性的基本问题。尽管远郊在经济和生态方面具有重要意义，但还没有人完全概念化或开发出远郊土地市场的空间动态模型。通过这样做，该项目将为土地变化科学做出基础理论贡献，并为城市空间格局提供新的见解。本项目提出的实证应用将产生新的知识，对面临城市可持续性管理挑战的决策者有切实的好处。通过促进区域科学和物理科学家之间的合作，该项目将促进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。

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.