Research progress in loess landslides forecast and prediction based on assimilating multi-source information

2019 2nd International Conference of Green Buildings and Environmental Management

生态环境科学

Bai, Xuejiao^1^2^3 ; Sang, Lingzhi^1 ; Bai, Guichen^4 ; Kang, Hongxia^1 ; Liu, Zhen^3

China Transport Telecommunications and Information Center, Beijing

100011, China^1

National Engineering Laboratory for Transportation Safety and Emergency Informatics, Beijing

100011, China^2

Faculty of Education, Beijing Normal University, Beijing

100875, China^3

Kangbao Transportation Bureau, Zhangjiakou, 076650, China^4

关键词: Engineering activities;    Forecast and predictions;    Multi-source information fusion;    Multi-source informations;    Prediction model;    Regional economy;    Theoretical methods;    West region of chinas;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/310/5/052045/pdf
DOI  :  10.1088/1755-1315/310/5/052045

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

China's one-third western region disseminated in Qinghai, Ningxia, Shaanxi, Gansu and other provinces witnessed landslide disasters in recent decades over loess and loess-like soils with special composition and properties. Loess landslides occur more frequently with serious constrained in the development of regional economy following the sharp increase in human engineering activity, especially from the launch of China's Grand Strategy of Developing the West region of china. Therefore, the loess landslide forecasting and prediction is a hot topic in the study of environmental geology. This research demonstrates the situation and progress of the landslide forecasting and prediction motivated by the theoretical methods and technological means of landslide forecasting and prediction, the study of remote sensing survey of landslides, the study of multi-source information fusion and the study of loess landslide forecasting and prediction, followed by the prediction model for loess landslide based on assimilating multi-source information with its specific technology route anticipation based on assimilating multi-source information.