東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Intelligent interpretation for geolo...

Chen, Weitao.

Linked to FindBook

Google Book

Amazon

博客來

Intelligent interpretation for geological disasters = from space-air-ground integration perspective /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Intelligent interpretation for geological disasters/ by Weitao Chen ... [et al.].
Reminder of title:	from space-air-ground integration perspective /
other author:	Chen, Weitao.
Published:	Singapore :Springer Nature Singapore : : 2023.,
Description:	xii, 233 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Landslide hazard analysis - Data processing. -
Online resource:	https://doi.org/10.1007/978-981-99-5822-1
ISBN:	9789819958221

Intelligent interpretation for geological disasters = from 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

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

2156497
Landslide hazard analysis
--Data processing.

LC Class. No.: QE599.2

Dewey Class. No.: 551.307

Intelligent interpretation for geological disasters = from space-air-ground integration perspective /
LDR:02931nmm a2200325 a 4500 001 2334575
003 DE-He213
005 20230912095355.0
006 m d
007 cr nn 008maaau
008 240402s2023 si s 0 eng d
020 $a 9789819958221 $q (electronic bk.)
020 $a 9789819958214 $q (paper)
024 7 $a 10.1007/978-981-99-5822-1 $2 doi
035 $a 978-981-99-5822-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QE599.2
072 7 $a RNR $2 bicssc
072 7 $a NAT023000 $2 bisacsh
072 7 $a RNR $2 thema
082 0 4 $a 551.307 $2 23
090 $a QE599.2 $b .I61 2023
245 0 0 $a Intelligent interpretation for geological disasters $h [electronic resource] : $b from space-air-ground integration perspective / $c by Weitao Chen ... [et al.].
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2023.
300 $a xii, 233 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
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.
650 0 $a Landslide hazard analysis $x Data processing. $3 2156497
650 0 $a Landslides $x Remote sensing. $3 3242002
650 1 4 $a Natural Hazards. $3 1005730
650 2 4 $a Geographical Information System. $3 3538564
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Geology. $3 516570
700 1 $a Chen, Weitao. $3 3604144
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-99-5822-1
950 $a Earth and Environmental Science (SpringerNature-11646)