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商品詳細
Artificial Intelligence and Geomatic Technology: Proceedings of the International Conference on Artificial Intelligence and Geomatic Technology.
・ISBN 978-3-032-30545-9 paper EUR 229.99
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| 著者・編者 | Mouncif, Hicham / El Kafhali, Said / El-harti, Abderrazak / El-ghmari, Abderrahmene / Bachaoui, El mostafa / Saadi, Youssef / Goundar, Sam (eds.), |
|---|---|
| シリーズ | (Lecture Notes in Networks and Systems) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2026 |
| ページ数 | 328 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A05-75809＞ |
解説
This book presents the peer-reviewed proceedings of the International Conference on Artificial Intelligence and Geomatic Technology (ICAIGT 2026), bringing together contributions from researchers, engineers, and academics working at the intersection of artificial intelligence and geospatial sciences. Artificial Intelligence and Geomatic Technology are rapidly transforming the way environmental systems, natural resources, and spatial phenomena are monitored, analyzed, and managed. By integrating advances in GeoAI, remote sensing, machine learning, and geospatial analytics, researchers and practitioners are developing innovative solutions to address some of the world's most pressing challenges, including climate change, sustainable agriculture, disaster risk management, water scarcity, and smart environmental monitoring.
The book highlights recent advances in spatial machine learning, Earth observation analytics, hyperspectral data fusion, UAV-based monitoring, environmental modeling, and digital twin technologies.
The chapters provide both methodological innovations and real-world applications, with a particular focus on semi-arid and developing regions where geospatial intelligence and AI-driven decision support systems can significantly contribute to sustainable development and environmental resilience.
The book is organized into four thematic sections covering:
* GeoAI and spatial machine learning.
* Remote sensing and earth observation analytics.
* Natural resource management and geospatial intelligence.
* Digital twins and smart environment monitoring.
By combining theoretical foundations with practical case studies, this book serves as a valuable resource for researchers, graduate students, engineers, and professionals in artificial intelligence, remote sensing, geomatics, environmental sciences, and smart monitoring systems.