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Landslides and law: Cyclone Gabrielle raises serious questions about where we've been allowed to build 科技资讯
2023
收藏  |  浏览/下载:6/0  |  提交时间:2023/02/22
Landslides and law: Cyclone Gabrielle raises serious questions about where we've been allowed to build 科技资讯
2023
收藏  |  浏览/下载:8/0  |  提交时间:2023/02/22
Climate Change 2022: Mitigation of Climate Change 科技报告
, 2022
作者:  Jim Skea
JPEG(8Kb)  |  收藏  |  浏览/下载:134/33  |  提交时间:2022/04/06
Canada in a Changing Climate:National Issues Report 科技报告
, 2021
作者:  [unavailable]
Adobe PDF(29033Kb)  |  收藏  |  浏览/下载:56/6  |  提交时间:2021/11/24
Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility 期刊论文
Natural Hazards, 2021, 卷号: 106, 期号: 1
作者:  Sun J.;  Qin S.;  Qiao S.;  Chen Y.;  Su G.;  Cheng Q.;  Zhang Y.;  Guo X.
收藏  |  浏览/下载:25/0  |  提交时间:2021/09/01
Debris flow susceptibility mapping  Integrating model  Physical model  Statistical model  Yongji County  
Landslide inventory and susceptibility models considering the landslide typology using deep learning: Himalayas, India 期刊论文
Natural Hazards, 2021, 卷号: 108, 期号: 1
作者:  Bera S.;  Upadhyay V.K.;  Guru B.;  Oommen T.
收藏  |  浏览/下载:18/0  |  提交时间:2021/09/01
Deep learning  Kalimpong (Himalayas)  Landslide inventory  Landslide typology  Spatial agreement  
National Climate Change Risk Assessment for New Zealand 科技报告
, 2020
作者:  [unavailable]
Adobe PDF(5236Kb)  |  收藏  |  浏览/下载:10/1  |  提交时间:2021/11/24
Assessment of Climate Change over the Indian Region 科技报告
, 2020
作者:  [unavailable]
Adobe PDF(24655Kb)  |  收藏  |  浏览/下载:14/1  |  提交时间:2021/11/24
Climate Change Impacts and Adaptation for Transport Networks and Nodes 科技报告
, 2020
作者:  [unavailable]
Adobe PDF(16508Kb)  |  收藏  |  浏览/下载:4/0  |  提交时间:2021/11/24
Multi-geohazards susceptibility mapping based on machine learning—a case study in Jiuzhaigou, China 期刊论文
Natural Hazards, 2020, 卷号: 102, 期号: 3
作者:  Cao J.;  Zhang Z.;  Du J.;  Zhang L.;  Song Y.;  Sun G.
收藏  |  浏览/下载:19/0  |  提交时间:2021/09/01
Evolution tendency  Geological hazards  Jiuzhaigou  Machine learning  Susceptibility