Land-use planning adaptation in response to SLR based on a vulnerability analysis

Abstract

Low-lying coastal areas are threatened worldwide by global climate change effects, including sea-level rise (SLR) and frequent storm surges. Identifying vulnerable areas and proposing feasible adaptation strategies for future land-use development are particularly important. Using Bay County, Florida, as a case study, this study develops a technical methodology to develop future land-use adaptation strategies in response to SLR and storm surges. We propose a cellular automata (CA) land-use adaptation model that not only minimizes the impacts of SLR and flooding from storm surge events but also captures inherent spatial growth characteristics by integrating a vulnerability assessment with a land suitability analysis. To assess vulnerability, a series of physical, environmental, and socioeconomic indicators for exposure, sensitivity and adaptation have been developed. In the CA land-use adaptation model, transition rules are generated from an integer programming problem that aims to maximize land-use suitability and to minimize the vulnerability of newly developed land cells. The model is calibrated with actual land-use data from 2000 to 2010. The model validation indicates that the predicted land uses effectively capture direction of spatial growth, with a kappa coefficient of 87.9%. In comparison with the results of a standard land-use development model, in this CA adaptation model successfully projects future developments in low vulnerability areas. This model could effectively help in the development of future land-use adaptation strategies to address the impacts of flooding due to SLR and storm surges.