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Intelligent interpretation for geological disastersfrom space-air-ground integration perspective /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent interpretation for geological disastersby Weitao Chen ... [et al.].
其他題名:	from space-air-ground integration perspective /
其他作者:	Chen, Weitao.
出版者:	Singapore :Springer Nature Singapore :2023.
面頁冊數:	xii, 233 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Landslide hazard analysisData processing.
電子資源:	https://doi.org/10.1007/978-981-99-5822-1
ISBN:	9789819958221$q(electronic bk.)

Intelligent interpretation for geological disastersfrom space-air-ground integration perspective /
Intelligent interpretation for geological disastersfrom space-air-ground integration perspective /[electronic resource] :by Weitao Chen ... [et al.]. - Singapore :Springer Nature Singapore :2023. - xii, 233 p. :ill., digital ;24 cm.

Chapter 1. Geological disaster: An overview -- Chapter 2. Research methods of geological disasters -- Chapter 3. Principles and methods of intelligent interpretation of geological disasters -- Chapter 4. Intelligent analysis of multi-source long-term landslide ground monitoring data -- Chapter 5. Intelligent monitoring of landslides based on high-resolution optical remote sensing data -- Chapter 6. Deep learning-based remote sensing monitoring of landslide -- Chapter 7. Deep learning-based landslide susceptibility assessment -- Chapter 8. Deep learning-based intelligent recognition of ground fissures -- Chapter 9. Machine learning-based remote sensing monitoring of land subsidence in mining areas -- Chapter 10. Concluding remarks.

This book comprehensively utilizes the new generation of artificial intelligence and remote sensing science and technology to systematically carry out researches on high-precision recognition, monitoring, analysis, and assessment of geological disasters by using different technologies of "ground, airspace, and space-based systems" and different scales of "target-semantic-region". The main contents include: 1) Intelligent interpretation theory and methods of geological disasters, 2) Intelligent analysis of landslide based on long-term ground monitoring data, 3) Deep learning-based remote sensing detection of landslide, 4) Intelligent analysis of landslide evolution based on optical satellite remote sensing data, 5) Intelligent assessment methods of landslide susceptibility, 6) Intelligent recognition of ground figure based on airspace-based remote sensing data, 7) Intelligent monitoring of land subsidence in mining areas based on InSAR technology. The book is of interest to graduate student, scientific, and technological personnel who work in the area of geological disasters, natural hazards, remote sensing, and artificial intelligence.

ISBN: 9789819958221$q(electronic bk.)

Standard No.: 10.1007/978-981-99-5822-1doiSubjects--Topical Terms:

726528
Landslide hazard analysis
--Data processing.

LC Class. No.: QE599.2

Dewey Class. No.: 551.307

Intelligent interpretation for geological disastersfrom space-air-ground integration perspective /
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520 $a This book comprehensively utilizes the new generation of artificial intelligence and remote sensing science and technology to systematically carry out researches on high-precision recognition, monitoring, analysis, and assessment of geological disasters by using different technologies of "ground, airspace, and space-based systems" and different scales of "target-semantic-region". The main contents include: 1) Intelligent interpretation theory and methods of geological disasters, 2) Intelligent analysis of landslide based on long-term ground monitoring data, 3) Deep learning-based remote sensing detection of landslide, 4) Intelligent analysis of landslide evolution based on optical satellite remote sensing data, 5) Intelligent assessment methods of landslide susceptibility, 6) Intelligent recognition of ground figure based on airspace-based remote sensing data, 7) Intelligent monitoring of land subsidence in mining areas based on InSAR technology. The book is of interest to graduate student, scientific, and technological personnel who work in the area of geological disasters, natural hazards, remote sensing, and artificial intelligence.
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