The Earth Observation (EO) domain can provide valuable information products that can significantly reduce the cost of mapping flood extent and improve the accuracy of mapping and monitoring systems. In this study, Landsat 5, 7, and 8 were utilized to map flood inundation areas. Google Earth Engine (GEE) was used to implement Flood Mapping Algorithm (FMA) and process the Landsat data. FMA relies on developing a “data cube”, which is spatially overlapped pixels of Landsat 5, 7, and 8 imagery captured over a period of time. This data cube is used to identify temporary and permanent water bodies using the Modified Normalized Difference Water Index (MNDWI) and site-specific elevation and land use data. The results were assessed by calculating a confusion matrix for nine flood events spread over the globe. The FMA had a high true positive accuracy ranging from 71–90% and overall accuracy in the range of 74–89%. In short, observations from FMA in GEE can be used as a rapid and robust hindsight tool for mapping flood inundation areas, training AI models, and enhancing existing efforts towards flood mitigation, monitoring, and management.

Antimicrobial resistance (AMR) is a pervasive global health threat linked to human antimicrobial misuse and abuse, food production, and broader environmental contamination. While global agencies promote a multi-sectoral One Health system approach to equitably combat human, animal, and environmental health AMR risks, it is widely acknowledged that the human and animal sectors dominate discussions. Given this disproportionate focus, identification of critical research gaps is needed to develop stewardship plans that equitably address One Health AMR threats. This review used natural language processing and term frequency algorithms to classify 12,638 records from 1990–2020 thematically in order to highlight sectoral prioritization and gaps. It also specifically assessed water-related gaps as water is recognized as both a primary environmental dissemination pathway and key means of intervention. Drawing from systemic health and integrated water management lenses, this review found that themes related to plant, wildlife, and environmental-related AMR threats—in particular, the role that environmental (ambient) waters play in AMR development, transmission, and spread—are under-prioritized as compared to human and food animal health concerns regardless of geographic region or income level. Further prioritization of these themes is needed to strengthen the environmental dimension of One Health AMR responses and systemically protect global health.