شناسایی سریع مناطق آسیب‌دیده پس از وقوع زلزله با استفاده از تصاویر ماهواره‌ای Sentinel2 (مطالعۀ موردی: زلزلۀ سرپل ذهاب)

شناسایی سریع مناطق آسیب‌دیده پس از وقوع زلزله به‌منظور تولید نقشۀ آسیب، اهمیت زیادی در زمینۀ امداد و نجات دارد. در چند سال گذشته استفاده از تصاویر ماهواره‌ای برای تولید نقشۀ تخریب به‌دلیل سرعت زیاد، پوشش وسیع از منطقه و هزینۀ اندک بسیار مورد توجه محققان قرار گرفته است. در این پژوهش، یک روش شناسایی سریع مناطق آسیب‌دیده مبتنی بر روش‌های شناسایی تغییرات ارائه خواهد شد که دربارۀ زلزلۀ سال 1396 سرپل ذهاب اجرا می‌شود. به‌منظور اعتبارسنجی این روش، ابتدا نتایج روش شناسایی تغییرات ارزیابی شد که خروجی‌ها نشان‌دهندۀ صحت زیاد روش در شناسایی مناطق تغییریافته‌اند. از طرف دیگر، نتایج روش شناسایی آسیب که در زلزلۀ سرپل ذهاب اجرا شده با نقشه‌های آسیب تولیدشده توسط سازمان فضایی اروپا اعتبارسنجی شد که نتایج حاکی از صحت 84 درصدی در شناسایی مناطق آسیب‌دیده است. با به‌کارگیری روش پیشنهادی، نقشۀ آسیب برای شهر سرپل ذهاب بسیار سریع و در مدت کمتر از سی دقیقه تولید شد.

Rapid Damage Mapping after an Earthquake using Sentinel2 Images (Case Study: Sarpole Zahab)

Rapid damage mapping after an earthquake in order to produce damage map is important for relief and rescue operations. Recently, the use of remote sensing images for producing damage maps is considered due to their synoptic view and low cost. In this research, a rapid damage mapping approach according to change detection is proposed, which is applied to the 2018 Sarepole Zahab earthquake. In order to assess results, outcomes of the change detection were evaluated using ground truth, which show high accuracy in detecting change areas. On the other hand, our damage map was evaluated using damage map produced by the European Space Agency (ESA), which outcomes depict our proposed method can detect damage areas by an overall accuracy of 84 %. Using the proposed method, damage map of the Sarepole Zahab was generated less than 30 minutes. IntroductionRemote sensing is a useful science and technology for different applications, especially disaster management. Remote sensing can be used to produce building damage maps after the earthquake. Recently, researchers used remote sensing data for producing building damage maps [14]. However, the used approaches are based on training samples. Preparing training samples is a time consuming task. For this reason, scientists would like to develop rapid damage mapping. Tiede et al. proposed a method to map damage areas of the Haiti earthquake using a shadow analysis approach. The proposed approach can produce damage areas after 12 hours [5]. The main goal of this paper is to develop a rapid damage mapping approach based on pre and postevent images in Sarpole Zahab. The developed method benefits from decision making approaches to make a rapid map.MethodologyThe proposed method is done in four steps according to Figure 1. In the first step, some essential preprocessing tasks including georeferencing and radiometric correction are performed. In the second step, difference image is produced and some textural features are extracted from it. In the third step, change and unchanged areas are identified using three change detection approaches. Finally, TOPSIS decision making approach is employed to make a damage map. Fig. 1.  Workflow of the proposed methodResultsSince the proposed method is based on change detection, we applied it to two data sets. Results of change detection over two case studies present in Figure 2. According to validation results, the proposed approach can detect changed and unchanged areas with about 95 % accuracy.   Nearest neaghbour of Region 1Nearest neaghbour of Region 2Spectral angle mapper of Region 1   Spectral angle mapper of Region 2Maximum likelihoo of Region 1Maximum likelihoo of Region 2Fig. 2. Results of change detection approaches over two study areasUsing pre and postevent Sentinel2 images and our proposed approach, damage map of Sarpole Zahab was produced. Figure 3 shows pre and postevent Sentinel2 images and damage map of the study area.   Fig. 3. Pre and postevent Sentinel2 images and damage map of the study areaThe accuracy of our damage detection approach is assessed using damage map produced by European space agency (ESA). Table 1 depicts the confusion matrix regarding the accuracy of our proposed method. Based on this table, the overall accuracy of our proposed approach is about 70 %.Table 1. the confusion matrix of our proposed approachOverall acc.  (%)User acc. (%)Producer acc. (%)DamagedUndamged 68.2643.8568.841846814442Undamaged85.77680.6393556527Damaged ConclusionIn this paper, a rapid damage mapping approach is proposed to detect damage areas from Sarpole Zahab earthquake. The proposed method is based on change detection and unsupervised. From the perspective of change detection, our proposed approach is robust. To assess the capability of the proposed method, it was applied in Sarpole Zahab earthquake. Using pre and postevent Sentinel2 images, the proposed approach can detect damaged areas with an accuracy of 80 %.