Effectiveness of urban construction boundaries in Beijing:an assessment

Based on the remote sensing (RS) and geographic information system (GIS) analysis of the Landsat multispectral scanner (MSS) and thematic mapper (TM) satellite images of 1983, 1993, and 2005, the present research examined the effectiveness of the urban construction boundaries (UCBs) in containing urban growth within the 6th Ring Road of Beijing Municipality. Three indicators on boundary control were proposed, through which the effectiveness of boundary containment, land inventory sufficiency and illegal adjacent development to the UCBs were explored. The results suggested that, first, the UCBs were limited in effectiveness in containing urban growth; second, the area encompassed by the UCBs might not be designed large enough to accommodate new development. The frustration of the urban growth control through the UCBs mainly resulted from the lack of a transparent system for urban land use planning and control to provide sufficient information, the limitation of the traditional land use prediction method to consider contingencies, and the absence of a mechanism to monitor and adjust the UCBs to respond just in time to urban change.

Theoretical foundation of a decision network for urban development

Planning problems are challenging and complex in that they usually involve multiple stakeholders with multi-attribute preferences. Thus few, if any, planning tools are useful in helping planners address such problems. Decision analysis is less useful than expected in dealing with planning problems because it focuses overwhelmingly on making a single decision for a particular decision-maker. In this paper, we describe the theoretical foundation of a planning tool called the ＇decision network＇, which aims to help planners make multiple and linked decisions when facing multiple stakeholders with multi-attribute preferences. The research provides a starting point for a fully fledged technology that is useful for dealing with complex planning problems. We first provide a general formulation of the planning problem that the decision network intends to address. We then introduce an efficient solution algorithm for this problem, with a numerical example to demonstrate how the algorithm works. The proposed solution algorithm is efficient, allowing computerization of the planning tool. We also demonstrate that the diagrammatic representation of the decision network is more efficient than that of a decision tree. Therefore, when dealing with challenging and complex planning problems, using the decision network to make multiple and linked decisions may yield more benefits than making such decisions independently.