|Title||Redefining the Typology of Land Use in the Age of Big Data|
|Year of Publication||2014|
|Academic Department||Dept. of Urban Studies and Planning|
|University||Massachusetts Institute of Technology|
Land use classification is important as a standard for land use description and management. However, current land use classification systems are problematic. Labels such as "residential use" and "commercial use" do not fully reveal how the land use is used in terms of function, mix use and changes over time. As a result, land use planning is often a natural prompt of segregation; Land use is poorly connected with other fields of urban studies such as transportation and energy consumption. The problems of land use are partly because land use classification has been an expediency rather than of rigorous thought. However, recent researches about land use classification have mainly focused on the methods of estimating land use types, without challenging the conventional instructional definition of land use typology itself. In contrast, this thesis aims to ask a more fundamental question: what are the elements, the principles, and the process to build the land use typology for given purposes. This thesis accordingly proposes the syntax of developing a land use typology, where five basic elements compose the framework of land use description: land use function, land use intensity, land use connectivity, probability and scale. While the elements are abstract concepts, when developing a land use typology, each of them could be defined with specific measures for purposes such as land use planning, land use management, energy analysis, transportation study. After the land use typology is composed with the defined elements, it can be applied to examine land mixed use, land use conflict, land use change and estimation. The syntax then proposes the basic principles and process to develop a satisfied land use typology, with respect to the reliability and validity, the significance and necessity, the measurability and operability, and the adaptability and flexibility. With that, this thesis argues that beyond the theoretical definition, the practical context, such as data availability or planning schema will influence the feasibility of a land use typology. While the scope of the syntax could be limited by practical tools and availability of data, the coming age of big data provides a changing context of land use typology. The followed case study illustrates such a process of developing land use typology with geo-social network data. The case develops a social media based land use typology, collects data for two example cities: Boston, U.S and Shenzhen, China, and applies the defined land use typology to classify their uses of land. As a result, Boston's land use I classified by its function, intensity and the level of mix use; Shenzhen land use is classified by its intensity, connectivity and the level of mix use. Compared with the conventional land use classification systems, the social media based typology provides a more comprehensive description of land use, with its focuses on human activities of the city and multiple dimensions of urban land use. It also has advantages with the flexibility and efficiency of data collection. In conclusion, the syntax of land use typology highlights the process of building land use typology, by defining the basic components of land use typology. It enables many possibilities of land use description with the help of big data, and reserves enough space to go beyond the existing tools and techniques. At last, the thesis proposes for future studies on the different interpretations of the syntax, its application on planning tools and systems, and potential for new types of land use.
Supervised by Jinhua Zhao