Geovisualisation and estimation of a natural hazard extent using GIS and remote Sensing: New Zealand cyclone Gabrielle case study

Despite the global consensus on the increasing frequency of extreme natural events, limited research harnesses the potential of Google Earth Engine (GEE) for geovisualization and flood extent estimation. This study utilizes GEE’s JavaScript APIs, Sentinel-1 data, and a water mask derived from a digital elevation model (DEM) to map Cyclone Gabrielle’s extent. Results, highlighting successful deployment of GEE, reveal 500 ha of cropland and 13,975 ha of urban land affected. The study underscores GEE’s utility for decision-makers and disaster risk reduction, offering valuable insights for effective disaster management and recovery strategies.