Abstract
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.
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference177 articles.
1. Climate Change Adaptation: The Pivotal Role of Water (2010). UN Waterhttps://www.unwater.org/publications/climate-change-adaptation-pivotal-role-water/#:~:text=Higher%20temperatures%20and%20changes%20in,likely%20to%20be%20adversely%20affected
2. Impacts, Risks, and Adaptation in the United States: The Fourth National Climate Assessment, Volume II
3. Climate Change 2014–Impacts, Adaptation and Vulnerability: Part A: Global and Sectoral Aspects: Working Group II Contribution to the IPCC Fifth Assessment Report,2014
4. Planetary boundaries: Guiding human development on a changing planet
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