Department of Geography and Environmental Studies, University of New Mexico, Albuquerque, NM 87131, USA.
Center for the Advancement of Spatial Informatics Research and Education (ASPIRE), University of New Mexico, Albuquerque, NM 87131, USA.
Sensors (Basel). 2022 Mar 21;22(6):2416. doi: 10.3390/s22062416.
Water features (e.g., water quantity and water quality) are one of the most important environmental factors essential to improving climate-change resilience. Remote sensing (RS) technologies empowered by artificial intelligence (AI) have become one of the most demanded strategies to automating water information extraction and thus intelligent monitoring. In this article, we provide a systematic review of the literature that incorporates artificial intelligence and computer vision methods in the water resources sector with a focus on intelligent water body extraction and water quality detection and monitoring through remote sensing. Based on this review, the main challenges of leveraging AI and RS for intelligent water information extraction are discussed, and research priorities are identified. An interactive web application designed to allow readers to intuitively and dynamically review the relevant literature was also developed.
水特性(例如,水量和水质)是提高气候变化适应能力的最重要的环境因素之一。人工智能 (AI) 赋能的遥感 (RS) 技术已成为自动化水信息提取和智能监测的最受欢迎策略之一。在本文中,我们对文献进行了系统回顾,其中包括人工智能和计算机视觉方法在水资源领域的应用,重点是通过遥感进行智能水体提取以及水质检测和监测。基于这项综述,讨论了利用 AI 和 RS 进行智能水信息提取的主要挑战,并确定了研究重点。还开发了一个交互式网络应用程序,旨在允许读者直观和动态地查看相关文献。