The integration of artificial intelligence (AI) in remote sensing and satellite image processing has significantly transformed the field, offering advanced tools for data analysis, feature extraction, and environmental monitoring. With the growing availability of high-resolution satellite imagery, AI applications such as machine learning and deep learning have been applied to automate the process of interpreting complex spatial data. This paper intends to explore the current state of AI in remote sensing, focused on some applications such as land cover classification, object detection, climate change monitoring, and disaster management. Additionally, the challenges and future directions for AI-driven remote sensing are discussed, emphasizing the need for better generalizability, data fusion, and improved computational efficiency.
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Ondřej Krejcar
Hamidreza Namazi
Environmental Earth Sciences
Monash University Malaysia
University of Hradec Králové
Škoda (Czechia)
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Krejcar et al. (Thu,) studied this question.
www.synapsesocial.com/papers/69a75e5ec6e9836116a28da7 — DOI: https://doi.org/10.1007/s12665-025-12798-w