| dc.description.abstract | In recent years, extreme climate events, geopolitical crises, and regional security issues have increased year by year, resulting in the rise of large-scale and regional agricultural and food crises worldwide. Making food security, like energy security, financial security, and other major economic security core issues attract attention. It is also an essential part of ＂non-traditional national security＂ outside of the traditional political, military, and diplomatic security issues. When the country faces large-scale natural disasters and poor agricultural harvests, if the people cannot have a subjective sense of security or an objective fact of food security, the people will lose their trust in the government and the ruling team to ensure security. Under this situation, it may lead to political turmoil within the country. Dictatorship and authoritarian regimes may even take national interests as the premise. By striving for a regional security balance, and through traditional political, military, foreign, economic, and trade policy tools, they can form a situation of external power expansion and war, affecting regional stability and peace.
With the diversification of satellite image sources and the increasing abundance of resources, the temporal and geospatial scales of the research scope become wider. The current satellite imagery can quickly provide multi-period and wide-area data across time and geospatial for the acquisition of large-scale agricultural disaster damage data (especially in areas that are not easily or allowed accessible by outsiders). Coupled with the integration of agricultural survey statistics that have been published over the years, the near-real-time analytical information can be obtained, which is cost-effective for large-scale monitoring missions. However, the amount of analysis and calculation of imagery and geospatial data has increased dramatically.
In response to this scientific research development trend and the challenge of extensive data analysis, Google has developed and made public a cloud computing platform called ＂Google Earth Engine (GEE)＂ to provide global-scale geospatial analysis services. Google′s substantial online computing power can effectively solve the need for a large area and long-term monitoring. This research uses this internet resource to analyze Sentinel-1 SAR imagery and Sentinel-2 optical imagery. With this supervised classification and related processing procedures, we can produce the monthly flood coverage maps to verify the feasibility of applying them to the rapid food security assessment in post-disaster regions. | en_US |