TY - JOUR

T1 - A disaster response model driven by spatial-temporal forecasts

AU - Nikolopoulos, Kostas

AU - Petropoulos, Fotios

AU - Sanchez Rodrigues, Vasco

AU - Pettit, Stephen

AU - Beresford, Anthony

PY - 2022/7

Y1 - 2022/7

N2 - In this research, we propose a disaster response model combining preparedness and responsiveness strategies. The selective response depends on the level of accuracy that our forecasting models can achieve. In order to decide the right geographical space and time window of response, forecasts are prepared and assessed through a spatial-temporal aggregation framework, until we find the optimum level of aggregation. The research considers major earthquake data for the period 1985 – 2014. Building on the produced forecasts, we develop accordingly a disaster response model. The model is dynamic in nature, as it is updated every time a new event is added in the database. Any forecasting model can be optimized though the proposed spatial-temporal forecasting framework, and as such our results can be easily generalized. This is true for both other forecasting methods, as well as in other disaster response contexts.

AB - In this research, we propose a disaster response model combining preparedness and responsiveness strategies. The selective response depends on the level of accuracy that our forecasting models can achieve. In order to decide the right geographical space and time window of response, forecasts are prepared and assessed through a spatial-temporal aggregation framework, until we find the optimum level of aggregation. The research considers major earthquake data for the period 1985 – 2014. Building on the produced forecasts, we develop accordingly a disaster response model. The model is dynamic in nature, as it is updated every time a new event is added in the database. Any forecasting model can be optimized though the proposed spatial-temporal forecasting framework, and as such our results can be easily generalized. This is true for both other forecasting methods, as well as in other disaster response contexts.

U2 - https://doi.org/10.1016/j.ijforecast.2020.01.002

DO - https://doi.org/10.1016/j.ijforecast.2020.01.002

M3 - Article

VL - 38

SP - 1214

EP - 1220

JO - International Journal of Forecasting

JF - International Journal of Forecasting

SN - 0169-2070

IS - 3

ER -