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V-BUDEM: A Vector-Based Beijing Urban Development Model for Simulating Urban Growth

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Book cover Geospatial Analysis to Support Urban Planning in Beijing

Part of the book series: GeoJournal Library ((GEJL,volume 116))

Abstract

BUDEM (Beijing Urban Development Model) is a raster-based Cellular Automata (CA) model for supporting city planning and policies evaluation in Beijing. In this chapter, we developed a vector-based version of BUDEM (V-BUDEM). In this model, urban space consists of irregular parcels, and a parcel’s neighborhood is defined as all parcels surrounding it within a certain distance. Additionally, a framework of parcel subdivision was adopted to subdivide existing parcels. After describing the conceptual model of V-BUDEM, including the parcel subdivision framework, we tested it in Beijing’s Yanqing Town for simulating urban growth from 2010 to 2020. Results show the V-BUDEM can be used to predict urban growth scenario, and prove the validity of our parcel subdivision framework. The main contributions of this study are as follows: (1) the model adopts a vector-based CA method using land parcels to represent urban space, composing the landscape a user would perceive as meaningful, and can simulate urban growth in a way more close to real world situation; (2) the model integrates a process of parcel subdivision, and the proposed parcel subdivision framework comprehensively considered the impacts of existing parcel boundaries in the existing land use map and planned parcel boundaries in the urban plan, and developed a straight-forward and automatic parcel subdivision tool, included in the framework as the fourth step, to partition existing large parcels; (3) compared with other urban models, V-BUDEM is developed specifically to identify policies required for implementing the planned urban form desired by planners and decision makers.

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Long, Y., Shen, Z. (2015). V-BUDEM: A Vector-Based Beijing Urban Development Model for Simulating Urban Growth. In: Geospatial Analysis to Support Urban Planning in Beijing. GeoJournal Library, vol 116. Springer, Cham. https://doi.org/10.1007/978-3-319-19342-7_5

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