Doctoral Dissertation Research: Integrating Multi-Date Satellite Images and Dynamic Spatial Modeling with GIS in a Rapidly Suburbanized Environment

都市地区的向外扩张仍然是整个地球表面土地利用和土地覆盖变化的最重要形式之一。据估计，在美国，郊区扩张导致每天有超过20平方公里的农田或开放空间被转化为城市用途。对于那些研究都市动态的人和那些必须在这些快速变化的环境中管理资源和提供服务的人来说，监测大都市外围的增长和变化是至关重要的。本博士论文研究项目将通过整合不同时间拍摄的卫星图像信息和地理信息系统上的动态空间模型，研究导致1973年至今佐治亚州亚特兰大市郊区土地利用和土地覆盖变化的过程。卫星图像处理、动态模型开发和校准以及交互式数据可视化将用于评估郊区土地利用和土地覆盖变化的时空特征。将根据人口和社会经济的变化来评价分散和聚集的城市形式的演变。该项目将加强对不同生物物理和社会经济领域的土地利用和土地覆盖变化机制的概念理解，并将增加对新形式的数据集成和变化建模的适用性的见解。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立研究生涯。

Outward expansion of metropolitan areas continues to be one of the most significant forms of land-use and land-cover change across the Earth's surface. Within the United States, suburban expansion is estimated to result in the conversion of more than 20 square km daily of farmland or open space into urban uses each day. Monitoring growth and change along the metropolitan periphery is of critical concern both to those who study metropolitan dynamics and those who must manage resources and provide services in these rapidly changing environments. This doctoral dissertation research project will examine the processes resulting in land-use and land-cover change from 1973 to the present along the outskirts of the Atlanta, Georgia, metropolitan area through the integration of information from satellite images taken at different times and a dynamic spatial model functioning on a geographic information system. Satellite-image processing, dynamic model development and calibration, and interactive data visualization will be used to assess the spatial and temporal characteristics of suburban land-use and land-cover change. The evolution of scattered and clustered urban forms will be evaluated in relation to demographic and socioeconomic changes. This project will enhance conceptual understandings of land-use and land-cover change mechanisms across different biophysical and socioeconomic domains, and it will add insights regarding the applicability of new forms of data integration and modeling of change. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.