Abstract
The interferometric SAR coherence-change technique with coherence filter and polarization (HH and HV) has been used to detect the parts of buildings damaged by the 2015 Gorkha Earthquake. A survey of the building damage was conducted in every house to evaluate the detection accuracy in the Khokana and Sankhu urban areas in the Kathmandu Valley of Nepal. The damaged parts of the urban area were adequately detected using coherence-change (∆γ) values obtained before the earthquake (γ pre) and during the inter-seismic stage of the earthquake (γ int). The use of a coherence filter effectively increased overall accuracy by ~2.1 to 7.0 % with HH polarization. The incorporation of HV polarization marginally increased the accuracy (~0.9 to 1.2 %). It was confirmed that road damage due to liquefaction was also observed using the interferometric SAR coherence-change detection technique. The classification accuracy was lower (27.1–35.1 %) for areas that were damaged. However, higher accuracy (97.8–99.2 %) was achieved for areas that were damage-free, in ∆γ obtained from HH and HV polarization with a coherence filter. This helped to identify the damaged urban areas (using this technique) immediately after occurrence of an earthquake event.
Highlights
In the aftermath of massive disasters affecting buildings, there is a demand for immediate detection of severely damaged urban areas
Synthetic aperture radar (SAR) observations are available for all weather conditions, day and night, and are an effective tool for detecting areas damaged in a disaster
The differences are due to change in soil moisture and change in the dielectric constant of trees (Watanabe et al 2015)
Summary
In the aftermath of massive disasters affecting buildings, there is a demand for immediate detection of severely damaged urban areas. A high-resolution optical image sensor on board a satellite is one of the possible tools to meet this demand. Cloud-free conditions over land occurred in only 22 % of images from a dataset of weather observations from 5400 land stations worldwide (Warren and Eastman 2007), and such data for night time are unavailable. Synthetic aperture radar (SAR) observations are available for all weather conditions, day and night, and are an effective tool for detecting areas damaged in a disaster. The most popular application of SAR for a disaster is to estimate crustal movement during earthquakes and volcanic activity. The wide range of crustal movement induced by the
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