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Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
成都山地灾害与环境... [40]
地理科学与资源研究... [17]
地质与地球物理研究所 [3]
重庆绿色智能技术研究... [2]
寒区旱区环境与工程研... [1]
遥感与数字地球研究所 [1]
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OAI收割 [64]
iSwitch采集 [1]
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期刊论文 [62]
SCI/SSCI论文 [1]
会议论文 [1]
学位论文 [1]
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2023 [5]
2022 [10]
2021 [8]
2020 [12]
2019 [3]
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学科主题
Geology [1]
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Exploring a form of pixel-based information value model for flood probability assessment and geo-visualization over an East African basin: a case of Nyabarongo in Rwanda
期刊论文
OAI收割
ENVIRONMENTAL EARTH SCIENCES, 2023, 卷号: 82, 期号: 17, 页码: 21
作者:
Mind'je, Richard
;
Li, Lanhai
;
Kayumba, Patient Mindje
;
Mupenzi, Christophe
;
Mindje, Mapendo
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2023/10/09
Flood
GIS
Information value
Nyabarongo
Pixel
Rwanda
Spatial understanding of historical and future landslide variation in Africa
期刊论文
OAI收割
NATURAL HAZARDS, 2023, 页码: 29
作者:
Nahayo, Lamek
;
Peng, Cui
;
Lei, Yu
;
Tan, Rongzhi
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2023/11/16
Africa
Gain information ratio
Landslide susceptibility
Urbanization
Hydromechanical coupling mechanism and an early warning method for paraglacial debris flows triggered by infiltration: Insights from field monitoring in Tianmo gully, Tibetan Plateau
期刊论文
OAI收割
NATURAL HAZARDS, 2023, 页码: 19
作者:
Yang, Zongji
;
Pang, Bo
;
Dong, Wufan
;
Li, Dehua
;
Shao, Wei
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2023/10/09
Paraglacial debris flow
Hydrological mechanism
Multivariate thresholds
Early warning
Joint Effects and Spatiotemporal Characteristics of the Driving Factors of Landslides in Earthquake Areas
期刊论文
OAI收割
JOURNAL OF EARTH SCIENCE, 2023, 卷号: 34, 期号: 2, 页码: 330-338
作者:
Yang, Jintao
;
Xu, Chong
;
Jin, Xu
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2023/06/10
geodetector
co-seismic landslide
spatial pattern
triggering factors
interaction effects
driving force
engineering geology
Landslide susceptibility prediction improvements based on a semi-integrated supervised machine learning model
期刊论文
OAI收割
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 卷号: N/A
作者:
Yang, Ning
;
Wang, Rui
;
Liu, Zhaofei
;
Yao, Zhijun
  |  
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2023/04/06
Semi-integrated supervision
Machine learning
Landslide susceptibility study
True skill statistic
Integrated model
Non-landslide sample
Spatial and temporal distribution of landslide-dammed lakes in Purlung Tsangpo
期刊论文
OAI收割
ENGINEERING GEOLOGY, 2022, 卷号: 308, 页码: 20
作者:
Wang, Hao
;
Cui, Peng
;
Zhou, Liqin
;
Liu, Weiming
;
Yang, Anna
  |  
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2022/11/09
Purlung Tsangpo
Landslide-dammed lake
Volume estimate
Deglaciation
River incision
Spatial and temporal distribution of landslide-dammed lakes in Purlung Tsangpo
期刊论文
OAI收割
ENGINEERING GEOLOGY, 2022, 卷号: 308, 页码: 20
作者:
Wang, Hao
;
Cui, Peng
;
Zhou, Liqin
;
Liu, Weiming
;
Yang, Anna
  |  
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2022/11/09
Purlung Tsangpo
Landslide-dammed lake
Volume estimate
Deglaciation
River incision
Determining trigger factors of soil mass failure in a hollow: A study based in the Sichuan Province, China
期刊论文
OAI收割
CATENA, 2022, 卷号: 216, 页码: 12
作者:
Habumugisha, Jules Maurice
;
Chen, Ningsheng
;
Rahman, Mahfuzur
;
Habumuremyi, Providence
;
Tuyishimire, Etienne
  |  
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2022/09/30
Hollows
Initial moisture content
Soil mass failure
Clay content
Slope angle
Spatiotemporal distribution characteristics, causes, and prevention advice of fatal geohazards in Jiangxi Province, China
期刊论文
OAI收割
SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 卷号: 834, 页码: 12
作者:
Shao, Chongjian
;
Liu, Yun
;
Lan, Hengxing
;
Li, Langping
;
Liu, Shao
  |  
收藏
  |  
浏览/下载:16/0
  |  
提交时间:2022/09/21
Fatal geohazards
Spatiotemporal patterns
Causes
Prevention advice
Provincial-scale
Jiangxi Province
Space-time susceptibility modeling of hydro-morphological processes at the Chinese national scale
期刊论文
OAI收割
ENGINEERING GEOLOGY, 2022, 卷号: 301, 页码: 19
作者:
Wang, Nan
;
Cheng, Weiming
;
Marconcini, Mattia
;
Bachofer, Felix
;
Liu, Changjun
  |  
收藏
  |  
浏览/下载:18/0
  |  
提交时间:2022/09/21
Hydro-morphological processes
Historical hazard archives
Susceptibility
Spatiotemporal predictive models