Abstract

Abnormally high-priced transactions in urban land speculation bring detrimental effects on economy, environment, and society. Governmental agencies around the world are striving hard to monitor and control land speculation by introducing various policy objectives and tools for an efficient urban development planning. One of the major challenges in controlling land speculation is to quickly identify the spatiotemporal locations of concern (hot spots) by monitoring the spatial clustering pattern changes over time and to alert the appropriate decision-making agencies for timely policy intervention. In this paper, we introduce a framework to rapidly detect the spatiotemporal hot spots of speculative land transactions in near-real-time data by exploiting the prospective monitoring procedures. We applied this method in the city of Hwasung, Republic of Korea, as an empirical illustration and found that the locations Jeongnam, Bongdam, Mado, and Dongtan were identified as hot spots with high, concentrated transaction values. The results indicate that the proposed framework is a capable tool for capturing prospective temporal indicators and pinpointing the localities of land speculation.

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