Impact of the Great East Japan Earthquake and Tsunami on Coastal Vegetation and Landscapes in Northeast Japan: Findings Based on Remotely Sensed Data Analysis

Hara, Kohjiro; Yi, Zhao; Tomita, Mizuki; Kamagata, Noritoshi; Li, Yunqing

doi:10.1007/978-4-431-56448-5_16

Cited by 7 publications

(1 citation statement)

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“…For example, the Great East Japan Earthquake (magnitude 9.0) and subsequent tsunami occurred on March 11, 2011, resulting in 21,000 dead and missing persons (Cabinet Office Govermant of Japan, 2015). This earthquake and tsunami can be regarded as a typical example of a "Large, Infrequent Disturbance" (Tomita et al, 2014), which not only results in loss of lives, but also results in dramatic changes in land cover, and has a major impact on biodiversity and ecosystems (Hara, 2014;Hara et al, 2016). Satellite remote sensing technology is considered to be an effective tool for monitoring natural disasters (Römer et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Land-Cover Maps Using Multiple Classifier System for Post-Disaster Landscape Monitoring

Hirayama

Tomita

Sharma

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Recently, land cover maps created from high resolution satellite images have been used for landscape analysis, in order to understand the impact of natural disasters on biodiversity and ecosystems. Conventional land cover classification methods, however, suffer from problems with isolated pixels (salt and pepper effect). Filtering can remove the isolated pixels, but can also result in loss of accurate information. The purpose of this study is to create a land cover map for landscape analysis of large-scale disturbances caused by the Great East Japan Earthquake of 2011, utilizing a Multiple Classifier System (MCS), which allows for reduction of isolated pixels while maintaining classification accuracy. RapidEye satellite images covering the Pacific Ocean side of the Tohoku district damaged by the earthquake and subsequent tsunami were obtained for 2010, 2011, 2012 and 2016, and land cover classification was implemented using individual classifiers and the MCS method. The results showed that the MCS land cover map was able to reduce the number of isolated pixels significantly (61-71%) compared with the individual classifiers, while maintaining very high accuracy (0.976-0.986) for all four years. These results indicate that MCS land cover maps have a great potential for analyzing disturbances following infrequent largescale natural disasters such as earthquakes and tsunami, and for monitoring the process of recovery afterwards. We expect that the results of this research will be useful in managing the recovery process in the region disturbed by the Great Eastern Japan Earthquake and Tsunami of 2011, and also for developing future Ecosystem-based Disaster Risk Reduction programs for the region.</p>

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Section: Introductionmentioning

confidence: 99%