Remote Sensing Landslide Recognition Based on Convolutional Neural Network
Joint Authors
Wang, Xiaofei
Wang, Yu
Jian, Junfan
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-09-18
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Landslides are a type of frequent and widespread natural disaster.
It is of great significance to extract location information from the landslide in time.
At present, most articles still select single band or RGB bands as the feature for landslide recognition.
To improve the efficiency of landslide recognition, this study proposed a remote sensing recognition method based on the convolutional neural network of the mixed spectral characteristics.
Firstly, this paper tried to add NDVI (normalized difference vegetation index) and NIRS (near-infrared spectroscopy) to enhance the features.
Then, remote sensing images (predisaster and postdisaster images) with same spatial information but different time series information regarding landslide are taken directly from GF-1 satellite as input images.
By combining the 4 bands (red + green + blue + near-infrared) of the prelandslide remote sensing images with the 4 bands of the postlandslide images and NDVI images, images with 9 bands were obtained, and the band values reflecting the changing characteristics of the landslide were determined.
Finally, a deep learning convolutional neural network (CNN) was introduced to solve the problem.
The proposed method was tested and verified with remote sensing data from the 2015 large-scale landslide event in Shanxi, China, and 2016 large-scale landslide event in Fujian, China.
The results showed that the accuracy of the method was high.
Compared with the traditional methods, the recognition efficiency was improved, proving the effectiveness and feasibility of the method.
American Psychological Association (APA)
Wang, Yu& Wang, Xiaofei& Jian, Junfan. 2019. Remote Sensing Landslide Recognition Based on Convolutional Neural Network. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1197596
Modern Language Association (MLA)
Wang, Yu…[et al.]. Remote Sensing Landslide Recognition Based on Convolutional Neural Network. Mathematical Problems in Engineering No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1197596
American Medical Association (AMA)
Wang, Yu& Wang, Xiaofei& Jian, Junfan. Remote Sensing Landslide Recognition Based on Convolutional Neural Network. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1197596
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197596