Athanasios Votsis

Utilizing a cellular automaton model to explore the influence of coastal flood adaptation strategies on Helsinki's urbanization patterns

Abstract A cellular automaton model (SLEUTH-3r) is utilized to explore the impacts of coastal flood risk management strategies on the urbanization parameters of Helsinkis metropolitan area, at a 50-m spatial resolution by 2040. The current urbanization trend is characterized by the consolidation of existing built-up land and loss of interspersed green spaces, whereas the most intense growth is forecast inside the coastal flood risk areas. This baseline is compared to strategies that test various responses of the planning system to real estate market forces and the spatial distribution of flood risks. A set of scenarios translates property price effects of flood risk information into various attraction-repulsion areas in and adjacent to the floodplain, while a second set explores varying degrees of restricting new growth in the flood risk zones without reference to the housing market. The simulations indicate that growth under all scenarios is distributed in a more fragmented manner relative to the baseline, which can be interpreted favorably regarding house prices and increased access to ecosystem services, although the indirect effects should also be considered. Demand for coastal flood-safe properties does not appear to automatically translate to refocusing of development toward those areas, unless planning interventions encourage this redistribution. The character of the planning system with respect to market drivers and the spatial distribution of risks and amenities is thus important. A mixture of market-based measures and moderate zoning interventions may be preferable for flood risk management and provide the necessary precision for adaptation strategies.

Exploring the spatiotemporal behavior of Helsinki’s housing prices with fractal geometry and co-integration

Fractal geometry and co-integration are combined for exploring spatial morphological aspects of quarterly dwelling prices in Helsinki’s region from 1977 to 2011. Curves of fractal scaling behavior are first employed to measure the fractal dimensions of high- and low-price/m2 spatial clusters at multiple scales. Subsequently, the fractal dimensions at indicative neighborhood and citywide scales are modeled with vector error correction specifications. The results identify long-run joint equilibria between the fractal geometries of high- and low-price/m2 clusters at both spatial scales. High-price/m2 clusters exhibit consistently higher fractal dimensions than their low-value counterparts at the neighborhood scale, while this long-run relation is reversed at the citywide scale. Short-run disequilibria and subsequent adjustments are also scale sensitive. The fractal geometry of high-price/m2 clusters leads the dynamics at the neighborhood scale, while low-price/m2 clusters lead at the citywide scale. The system’s responses to exogenous shocks take longer time to stabilize at the neighborhood scale compared to the citywide scale, but in both scales the non-stationary nature of fractal behavior is evident. These elements indicate that a closer look on spatial economic behavior at more than one spatial and temporal scale at a time can reveal non-trivial information in the context of urban research and policy analysis.