Cargando…
Identification of Landslides in Mountainous Area with the Combination of SBAS-InSAR and Yolo Model
Landslides have been frequently occurring in the high mountainous areas in China and poses serious threats to peoples’ lives and property, economic development, and national security. Detecting and monitoring quiescent or active landslides is important for predicting risks and mitigating losses. How...
Autores principales: | Guo, Haojia, Yi, Bangjin, Yao, Qianxiang, Gao, Peng, Li, Hui, Sun, Jixing, Zhong, Cheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416278/ https://www.ncbi.nlm.nih.gov/pubmed/36015993 http://dx.doi.org/10.3390/s22166235 |
Ejemplares similares
-
Landslide Susceptibility Mapping of Karakorum Highway Combined with the Application of SBAS-InSAR Technology
por: Zhao, Fumeng, et al.
Publicado: (2019) -
Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China
por: Xiao, Bo, et al.
Publicado: (2022) -
Landslide Susceptibility Mapping with Integrated SBAS-InSAR Technique: A Case Study of Dongchuan District, Yunnan (China)
por: Zhu, Zhifu, et al.
Publicado: (2022) -
Monitoring and analysis of ground subsidence in Shanghai based on PS-InSAR and SBAS-InSAR technologies
por: Zhang, Zhihua, et al.
Publicado: (2023) -
SBAS-InSAR based validated landslide susceptibility mapping along the Karakoram Highway: a case study of Gilgit-Baltistan, Pakistan
por: Kulsoom, Isma, et al.
Publicado: (2023)