S&M Young Researcher Paper Award 2020
Recipients: Ding Jiao, Zao Ni, Jiachou Wang, and Xinxin Li [Winner's comments]
Paper: High Fill Factor Array of Piezoelectric Micromachined
Ultrasonic Transducers with Large Quality Factor

S&M Young Researcher Paper Award 2021
Award Criteria
Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

Instructions to authors
English    日本語

Instructions for manuscript preparation
English    日本語


 Sensors and Materials
 1-23-3-303 Sendagi,
 Bunkyo-ku, Tokyo 113-0022, Japan
 Tel: 81-3-3827-8549
 Fax: 81-3-3827-8547

MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.

MYU Research

(proofreading and recording)

(translation service)

The Art of Writing Scientific Papers

(How to write scientific papers)
(Japanese Only)

Sensors and Materials, Volume 32, Number 11(4) (2020)
Copyright(C) MYU K.K.
pp. 4019-4036
S&M2391 Research Paper of Special Issue
Published in advance: November 20, 2020
Published: November 30, 2020

Automatic Unsupervised Landslide Detection Method Based on Single High-resolution Optical Image for Emergency Response [PDF]

Xi Zhai, Wanzeng Liu, Chuan Yin, Yunlu Peng, Yong Zhao, Ying Yang, Xiuli Zhu, Ran Li, and Tingting Zhao

(Received September 29, 2020; Accepted November 17, 2020)

Keywords: urban landslide detection, high-resolution image, visual salience, reflective characteristics, morphological processing

Urban safety in mountainous areas is continuously seriously threatened by landslide disasters. Recently, many remote-sensing-based methods have been developed for landslide detection. However, many existing methods rely on multitemporal/multisource data, which require tedious data collection work and limit their practical capacity in real-time emergencies. Therefore, in this paper, we propose a novel unsupervised single-image-based landslide detection (USILD) method to automatically and quickly locate landslides and evaluate landslide risks, which can provide timely data for urban landslide responses. This method is designed to take full advantage of the visual salience and reflectance characteristics of landslides to produce a landslide risk map. Morphological processing is used to refine the final maps. The method is implemented and applied to the recent Ludian landslide event, in which hundreds of landslides occurred, on August 3, 2014. High-resolution satellite and aerial images obtained with sensor technology provided suitable experimental materials for this study. The experimental results show that our method can achieve higher accuracy and more automatic processing than other methods such as change detection using image differencing (CDD), change detection using ratio (CDR), k-means, and support vector machine (SVM). Moreover, the method requires no training samples and has a lower computational cost than supervised learning algorithms. Given the high detection accuracy and simple workflow, the proposed method is very promising for practical application in landslide emergency responses.

Corresponding author: Wanzeng Liu, Yong Zhao

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Xi Zhai, Wanzeng Liu, Chuan Yin, Yunlu Peng, Yong Zhao, Ying Yang, Xiuli Zhu, Ran Li, and Tingting Zhao, Automatic Unsupervised Landslide Detection Method Based on Single High-resolution Optical Image for Emergency Response, Sens. Mater., Vol. 32, No. 11, 2020, p. 4019-4036.

Forthcoming Regular Issues

Forthcoming Special Issues

7th Special Issue on the Workshop of Next-generation Front-edge Optical Science Research
Guest editor, Yutaka Fujimoto (Tohoku University) and Takayuki Yanagida (Nara Institute of Science and Technology)

Special issue on Novel Materials and Sensing Technologies on Electronic and Mechanical Devices Part 4(2)
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Hsien-Wei Tseng (Yango University)

Special Issue on Artificial Intelligence and Advanced Technologies for Power and Renewable Energy Systems from IS3C2020
Guest editor, Shiue Der Lu , Meng Hui Wang, Kuei Hsiang Chao, and Her Terng Yau (National Chin-Yi University of Technology) (deadline extended to 28 Feb. 2021)
Conference website
Call for paper

Special Issue on the International Multi-Conference on Engineering and Technology Innovation 2020 (IMETI2020)
Guest editor, Wen-Hsiang Hsieh (National Formosa University)
Conference website

Special Issue on Human-in-the-loop Sensing in Cognitive Robotic Systems
Guest editor, Weiwei Wan (Osaka University), Yiming Jiang (Hunan University), and Daolin Ma (MIT)
Call for paper

Special Issue on Sensing and Data Analysis Technologies for Living Environment, Health Care, Production Management and Engineering/Science Education Applications: Part 2
Guest editor, Chien-Jung Huang (National University of Kaohsiung), Rey-Chue Hwang (I-Shou University), Ja-Hao Chen (Feng Chia University), Ba-Son Nguyen (Research Center for Applied Sciences)
Call for paper

Copyright(C) MYU K.K. All Rights Reserved.