Artificial Intelligence in Remote Sensing: Advancements, Challenges, and Future Directions for Sustainable Applications
Dhanapriya M
*
Birla Institute of Technology (BIT), Mesra, Ranchi, Jharkhand – 835215, India.
*Author to whom correspondence should be addressed.
Abstract
This chapter explores how artificial intelligence (AI) can be incorporated into remote sensing, emphasizing how it can revolutionize a number of fields, such as agriculture, urban planning, disaster relief, and environmental monitoring. It gives a summary of how artificial intelligence (AI) methods, especially machine learning and deep learning, improve the handling, interpretation, and use of data from remote sensing. The chapter also explores the main obstacles preventing AI from being widely used in remote sensing, including issues with data accessibility, model interpretability, training complexity, and ethical considerations. It also offers a number of real-world examples that show how AI can be used to provide useful insights and facilitate data-driven decision-making. In addition to outlining future directions for research, development, and responsible implementation, this chapter provides a balanced perspective on the changing role of AI in remote sensing by addressing both the opportunities and limitations.
Keywords: Artificial Intelligence (AI), remote sensing, machine learning, deep learning image analysis, environmental monitoring