The last two decades of computer vision technologies in water resource management: A bibliometric analysis

Efficient management of water resources is an important task given the significance of water in daily lives and economic growth. Water resource management is a specific field of study which deals with the efficient management of water resources towards fulfilling the needs of society and preventing from water‐related disasters. Many activities within this domain are getting benefitted with the recent technological advancements. Within many others, computer vision‐based solutions have emerged as disruptive technologies to address complex real‐world problems within the water resource management domain (e.g., flood detection and mapping, satellite‐based water bodies monitoring, monitoring and inspection of hydraulic structures, blockage detection and assessment, drainage inspection and sewer monitoring). However, there are still many aspects within the water resource management domain which can be explored using computer vision technologies. Therefore, it is important to investigate the trends in current research related to these technologies to inform the new researchers in this domain. In this context, this paper presents the bibliometric analysis of the literature from the last two decades where computer vision technologies have been used for addressing problems within the water resource management domain. The analysis is presented in two categories: (a) performance analysis demonstrating highlighted trends in the number of publications, number of citations, top contributing countries, top publishing journals, top contributing institutions and top publishers and (b) science mapping to demonstrate the relation between the bibliographic records based on the co‐occurrence of keywords, co‐authorship analysis, co‐citation analysis and bibliographic coupling analysis. Bibliographic records (i.e., 1059) are exported from the Web of Science (WoS) core collection database using a comprehensive query of keywords. VOSviewer opensource tool is used to generate the network and overlay maps for the science mapping of bibliographic records. Results highlighted important trends and valuable insights related to the use of computer vision technologies in water resource management. An increasing trend in the number of publications and focus on deep learning/artificial intelligence (AI)‐based approaches has been reported from the analysis. Further, flood mapping, crack/fracture detection, coastal flood detection, blockage detection and drainage inspections are highlighted as active areas of research.