國立虎尾科技大學 |

InSAR and deep learning in landslides research = intelligent identification, risk assessment and susceptibility mapping /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	InSAR and deep learning in landslides research/ by Yi He.
其他題名:	intelligent identification, risk assessment and susceptibility mapping /
作者:	He, Yi.
出版者:	Singapore :Springer Nature Singapore : : 2025.,
面頁冊數:	xv, 214 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Landslide hazard analysis - China. -
電子資源:	https://doi.org/10.1007/978-981-96-9132-6
ISBN:	9789819691326

InSAR and deep learning in landslides research = intelligent identification, risk assessment and susceptibility mapping /
He, Yi.

InSAR and deep learning in landslides researchintelligent identification, risk assessment and susceptibility mapping /[electronic resource] :by Yi He. - Singapore :Springer Nature Singapore :2025. - xv, 214 p. :ill., digital ;24 cm.

Introduction -- InSAR and deep learning theory -- Deep learning landslide intelligent identification methods -- Landslide susceptibility assessment based on geography consistency constraints -- Landslide susceptibility assessment by integrated multi-model based on static-dynamic data -- Landslide susceptibility assessment based on integrated static-dynamic characteristics of InSAR deformation information.

This book combines remote sensing and deep learning technology to develop a variety of models in the study of different type landslides in a wide range of areas including northwest, southwest and southern China. It explores the application of various deep learning methods in landslide identification and sensitivity mapping. It also explores intelligent landslide monitoring and susceptibility mapping using a variety of data and methods, providing ideas and methods for landslide prevention and mitigation. This book is suitable for professionals in the field of landslide monitoring and graduate students in the fields of remote sensing and geological hazards research to mitigate this most widespread and harmful geological hazards in the world.

ISBN: 9789819691326

Standard No.: 10.1007/978-981-96-9132-6doiSubjects--Topical Terms:

1495568
Landslide hazard analysis
--China.

LC Class. No.: QE599.2

Dewey Class. No.: 551.307

InSAR and deep learning in landslides research = intelligent identification, risk assessment and susceptibility mapping /
LDR:02196nam a2200325 a 4500 001 1166770
003 DE-He213
005 20250723130259.0
006 m d
007 cr nn 008maaau
008 251217s2025 si s 0 eng d
020 $a 9789819691326 $q (electronic bk.)
020 $a 9789819691319 $q (paper)
024 7 $a 10.1007/978-981-96-9132-6 $2 doi
035 $a 978-981-96-9132-6
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 .H432 2025
100 1 $a He, Yi. $3 933912
245 1 0 $a InSAR and deep learning in landslides research $h [electronic resource] : $b intelligent identification, risk assessment and susceptibility mapping / $c by Yi He.
260 $a Singapore : $c 2025. $b Springer Nature Singapore : $b Imprint: Springer,
300 $a xv, 214 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- InSAR and deep learning theory -- Deep learning landslide intelligent identification methods -- Landslide susceptibility assessment based on geography consistency constraints -- Landslide susceptibility assessment by integrated multi-model based on static-dynamic data -- Landslide susceptibility assessment based on integrated static-dynamic characteristics of InSAR deformation information.
520 $a This book combines remote sensing and deep learning technology to develop a variety of models in the study of different type landslides in a wide range of areas including northwest, southwest and southern China. It explores the application of various deep learning methods in landslide identification and sensitivity mapping. It also explores intelligent landslide monitoring and susceptibility mapping using a variety of data and methods, providing ideas and methods for landslide prevention and mitigation. This book is suitable for professionals in the field of landslide monitoring and graduate students in the fields of remote sensing and geological hazards research to mitigate this most widespread and harmful geological hazards in the world.
650 0 $a Landslide hazard analysis $z China. $3 1495568
650 0 $a Landslides $z China $x Remote sensing. $3 1495569
650 0 $a Deep learning (Machine learning) $3 1381171
650 1 4 $a Natural Hazards. $3 784090
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Geographical Information System. $3 1365742
650 2 4 $a Geotechnical Engineering and Applied Earth Sciences. $3 1366420
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-96-9132-6
950 $a Earth and Environmental Science (SpringerNature-11646)