Next Article in Journal
Hyperspectral Image Super-Resolution via Adaptive Dictionary Learning and Double 1 Constraint
Next Article in Special Issue
Analysis and Classification of Natural and Human-Induced Ground Deformations at Regional Scale (Campania, Italy) Detected by Satellite Synthetic-Aperture Radar Interferometry Archive Datasets
Previous Article in Journal
Improved Mapping of Mountain Shrublands Using the Sentinel-2 Red-Edge Band
Previous Article in Special Issue
PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation
Open AccessArticle

Study on the Intensity and Coherence Information of High-Resolution ALOS-2 SAR Images for Rapid Massive Landslide Mapping at a Pixel Level

1
Graduate School of Engineering, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
2
School of Knowledge Management, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan
3
Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
4
International Research Institute of Disaster Science, Tohoku University, Aoba 468-1-E301, Aramaki, Aoba-ku, Sendai 980-8572, Japan
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(23), 2808; https://doi.org/10.3390/rs11232808
Received: 30 October 2019 / Revised: 20 November 2019 / Accepted: 26 November 2019 / Published: 27 November 2019
A rapid mapping of landslides following a disaster is important for coordinating emergency response and limiting rescue delays. A synthetic aperture radar (SAR) can provide a solution even in harsh weather and at night, due to its independence of weather and light, quick response, no contact and broad coverage. This study aimed to conduct a comprehensive exploration on the intensity and coherence information of three Advanced Land Observing Satellite-2 (ALOS-2) SAR images, for rapid massive landslide mapping in a pixel level, in order to provide a reference for future applications. Applied data were two pre-event and one post-event high-resolution ALOS-2 products. Studied area was in the east of Iburi, Hokkaido, Japan, where massive shallow landslides were triggered in the 2018 Hokkaido Eastern Iburi Earthquake. Potential parameters, including intensity difference (d), co-event correlation coefficient (r), correlation coefficient difference ( r ), co-event coherence ( γ ), and coherence difference ( γ ), were first selected and calculated based on a radar reflection mechanism, to facilitate rapid detection. Qualitative observation was then performed by overlapping ground truth landslides to calculated parameter images. Based on qualitative observation, an absolute value of d ( d a b s 1 ) was applied to facility analyses, and a new parameter ( d a b s 2 ) was proposed to avoid information loss in the calculation. After that, quantitative analyses of the six parameters ( d a b s 1 , d a b s 2 , r, r , γ and γ ) were performed by receiver operating characteristic. d a b s 2 and r were found to be favorable parameters, which had the highest AUC values of 0.82 and 0.75, and correctly classified 69.36% and 64.57% landslide and non-landslide pixels by appropriate thresholds. Finally, a discriminant function was developed, combining three relatively favorable parameters ( d a b s 2 , r , and γ ) with one in each type, and achieved an overall accuracy of 74.31% for landslide mapping. View Full-Text
Keywords: landslide; synthetic aperture radar (SAR); intensity; coherence; ALOS-2 landslide; synthetic aperture radar (SAR); intensity; coherence; ALOS-2
Show Figures

Graphical abstract

MDPI and ACS Style

Ge, P.; Gokon, H.; Meguro, K.; Koshimura, S. Study on the Intensity and Coherence Information of High-Resolution ALOS-2 SAR Images for Rapid Massive Landslide Mapping at a Pixel Level. Remote Sens. 2019, 11, 2808.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop