DOI: 10.1016/j.cageo.2019.104388
论文题名: Landslide detection based on contour-based deep learning framework in case of national scale of Nepal in 2015
作者: Yu B. ; Chen F. ; Xu C.
刊名: Computers and Geosciences
ISSN: 983004
出版年: 2020
卷: 135 语种: 英语
英文关键词: Deep learning
; Google earth engine
; Image enhancement
; Landslide detection
Scopus关键词: Climate change
; Developing countries
; Engines
; Image enhancement
; Landslides
; Semantics
; Developed countries
; Google earths
; Landslide detection
; Learning frameworks
; Learning models
; Long time series
; Semantic segmentation
; Vegetation index
; Deep learning
; contour map
; detection method
; developing world
; image processing
; Landsat
; landslide
; machine learning
; software
; Nepal
英文摘要: The deadly threat that landslide has brought about is drawing more and more attention to analyze the mechanisms of landslides and the relationship between landslides and climate change. Due to the limited record of historical landslides in developing countries, relevant research is mostly conducted in developed countries. Owing to the publicly available global long time-series Landsat images, such unbalance can be avoided by proposing a practical landslide detection model, especially in terms of national scale. This paper takes the advantage of google earth engine platform to synthesize the annual Landsat images covering the national scale of Nepal into one image and builds an end-to-end contour-based landslide detection deep learning framework. The framework consists of two parts, one is potential landslide detection using vegetation index and degradation of DEM, the other is exact landslide detection using semantic segmentation deep learning model based on the contour regions extracted from the detected potential landslide. The proposed method is applied to detect landslides of Nepal in the year of 2015 and achieves a satisfactory performance with 65% recall and 55.35% precision. The performance is 44% higher accurate than similarly published works, validating its promising applicability in practical landslide detection for national cases. © 2019 Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159765
Appears in Collections: 气候变化与战略
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作者单位: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China; Hainan Key Laboratory of Earth Observation, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Sanya, 572029, China; University of Chinese Academy of Sciences, Beijing, 100049, China; Institute of Crustal Dynamics, China Earthquake Administration, Beijing, 100085, China
Recommended Citation:
Yu B.,Chen F.,Xu C.. Landslide detection based on contour-based deep learning framework in case of national scale of Nepal in 2015[J]. Computers and Geosciences,2020-01-01,135